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Journal articles on the topic 'Autonomous robot system; Robots; Simulation'
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1
PETTERSSON, JIMMY, and MATTIAS WAHDE. "UFLIBRARY: A SIMULATION LIBRARY IMPLEMENTING THE UTILITY FUNCTION METHOD FOR BEHAVIORAL ORGANIZATION IN AUTONOMOUS ROBOTS." International Journal on Artificial Intelligence Tools 16, no. 03 (2007): 507–36. http://dx.doi.org/10.1142/s0218213007003382.
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A simulation software package (UFLibrary) implementing the utility function (UF) method for behavior selection in autonomous robots, is introduced and described by means of an example involving a simple exploration robot equipped with a repertoire of five different behaviors. The UFLibrary (as indeed the UF method itself) is aimed at providing a rapid yet reliable and generally applicable procedure for generating behavior selection systems for autonomous robots, while at the same time minimizing the amount of hand-coding related to the activation of behaviors. It is demonstrated how the UFLibrary allows a user to rapidly implement individual behaviors and to set up and carry out simulations of a robot in its arena, in order to generate and optimize, by means of an evolutionary algorithm, the behavior selection system of the robot.
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Jimenez, Felix, Teruaki Ando, Masayoshi Kanoh, and Tsuyoshi Nakamura. "Psychological Effects of a Synchronously Reliant Agent on Human Beings." Journal of Advanced Computational Intelligence and Intelligent Informatics 17, no. 3 (2013): 433–42. http://dx.doi.org/10.20965/jaciii.2013.p0433.
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The ability of human symbiosis robots to communicate is indispensable for their coexistence with humans, so studies on the interaction between humans and robots are important. In this paper, we propose amodel robot self-sufficiency system that empathizes with human emotions, a model in which we apply the urge system to an autonomous system of emotions. We carry out simulation experiments on this model and verify the psychological interaction between the software robot and its users.
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Hou, Yew Cheong, Khairul Salleh Mohamed Sahari, Leong Yeng Weng, et al. "Development of collision avoidance system for multiple autonomous mobile robots." International Journal of Advanced Robotic Systems 17, no. 4 (2020): 172988142092396. http://dx.doi.org/10.1177/1729881420923967.
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This article presents a collision avoidance system for multiple robots based on the current autonomous car collision avoidance system. The purpose of the system is to improve the current autonomous car collision avoidance system by including data input of other vehicles’ velocity and positioning via vehicle-to-vehicle communication into the current autonomous car collision avoidance system. There are two TurtleBots used in experimental testing. TurtleBot is used as the robot agent while Google Lightweight Communication and Marshalling is used for inter-robot communication. Additionally, Gazebo software is used to run the simulation. There are two types of collision avoidance system algorithm (collision avoidance system without inter-robot communication and collision avoidance system with inter-robot communication) that are developed and tested in two main road crash scenarios, rear end collision scenario and junction crossing intersection collision scenario. Both algorithms are tested and run both in simulation and experiment setup, each with 10 repetitions for Lead TurtleBot sudden stop, Lead TurtleBot decelerate, Lead TurtleBot slower speed, and straight crossing path conditions. Simulation and experimental results data for each algorithm are recorded and tabulated. A comprehensive comparison of performance between the proposed algorithms is analyzed. The results showed that the proposed system is able to prevent collision between vehicles with an acceptable success rate.
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Kurabayashi, Daisuke, Tatsuki Choh, Jia Cheng, and Tetsuro Funato. "Adaptive Formation Transition of a Swarm of Mobile Robots Based on Phase Gradient." Journal of Robotics and Mechatronics 22, no. 4 (2010): 467–74. http://dx.doi.org/10.20965/jrm.2010.p0467.
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This paper describes an algorithm, inspired by the intelligent property of a slim mold, for adaptive formation transitions of a robot group composed of autonomous, non-labeled robots. In the proposed system, one leader robot that knows the target position guides the other robots; the other robots do not have any global information. Each individual robot is equipped with a nonlinear oscillator and a simple communication system realized by flashing LEDs. In order to control these robots, phase gradients and phase waves are used in a manner similar to those of a slime mold (amoeba). By controlling the directions the followers are heading according to the phase gradients, a swarm of robots can change its formation adaptively in an obstacle course. Not only is the algorithm formulated, but also real hardware is developed and the system design is analyzed. The proposed system was verified through simulations and real implementations of 10 autonomous mobile robots.
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Kurabayashi, Daisuke, and Hajime Asama. "Autonomous Knowledge Acquisition and Revision by Intelligent Data Carriers in a Dynamic Environment." Journal of Robotics and Mechatronics 13, no. 2 (2001): 154–59. http://dx.doi.org/10.20965/jrm.2001.p0154.
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In this paper, we built a device and algorithm for implementation in autonomous robots that can enhance efficiency through autonomous knowledge acquisition and sharing. We also propose an algorithm to adapt our robotic system to dynamic environments. In this robotic system, the ""Intelligent Data Carrier"" provides navigational knowledge for autonomous mobile robots. An IDC summarizes fragmyents of knowledge from individual robots and tells the best direction toward a destination at which a robot wants to arrive. We make models of dynamic environments, and investigate the behaviors of autonomous robots that navigate using an intelligent data carrier system. We also create an algorithm that estimates the validity of knowledge in an IDC and allows the IDC to renew the knowledge autonomously. We verify effectiveness of the proposed algorithm by means of simulations.
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BESSEGHIEUR, Khadir, Wojciech KACZMAREK, and Jarosław PANASIUK. "Multi-robot Control via Smart Phone and Navigation in Robot Operating System." Problems of Mechatronics Armament Aviation Safety Engineering 8, no. 4 (2017): 37–46. http://dx.doi.org/10.5604/01.3001.0010.7316.
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Robot Operating System (ROS) is an open source robot software framework which provides several libraries and tools to easily conduct different robot applications like autonomous navigation and robot teleoperation. Most of the available packages across the ROS community are addressed for controlling a single robot. In this paper, we aim to extend some packages so, they can be used in multi-robot applications on ROS. Mainly, the multi-robot autonomous navigation and multi-robot smart phone teleoperation are addressed in this work. After being extended and compiled, the new packages are assessed in some simulations and experiments with real robots.
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Martinez S., Fredy H., Fernando Martinez S., and Holman Montiel A. "Bacterial quorum sensing applied to the coordination of autonomous robot swarms." Bulletin of Electrical Engineering and Informatics 9, no. 1 (2020): 67–74. http://dx.doi.org/10.11591/eei.v9i1.1538.
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This paper proposes a strategy for the coordination of a swarm of robots in an unknown environment. The basic idea is to achieve the autonomous movement of the group from an initial region to a target region avoiding obstacles. We use a behavior model similar to bacterial Quorum Sensing (QS) as a technique for the coordination of robots. This behavior has been described as a key element in the interaction between bacteria, and we use it as a basic tool for local interaction, both between the robot and between the robot and the environment. The movement of the swarm of robots, or multi-agent robotic system, is shown as an emerging behavior resulting from the interaction of agents (in the context of artificial intelligence) from basic rules of behavior. The proposed strategy was successfully evaluated by simulation on a set of robots.
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Miglino, Orazio, Henrik Hautop Lund, and Stefano Nolfi. "Evolving Mobile Robots in Simulated and Real Environments." Artificial Life 2, no. 4 (1995): 417–34. http://dx.doi.org/10.1162/artl.1995.2.4.417.
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The problem of the validity of simulation is particularly relevant for methodologies that use machine learning techniques to develop control systems for autonomous robots, as, for instance, the artificial life approach known as evolutionary robotics. In fact, although it has been demonstrated that training or evolving robots in real environments is possible, the number of trials needed to test the system discourages the use of physical robots during the training period. By evolving neural controllers for a Khepera robot in computer simulations and then transferring the agents obtained to the real environment we show that (a) an accurate model of a particular robot-environment dynamics can be built by sampling the real world through the sensors and the actuators of the robot; (b) the performance gap between the obtained behaviors in simulated and real environments may be significantly reduced by introducing a “conservative” form of noise; (c) if a decrease in performance is observed when the system is transferred to a real environment, successful and robust results can be obtained by continuing the evolutionary process in the real environment for a few generations.
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Senda, Kei, Yoshisada Murotsu, Akira Mitsuya, Hirokazu Adachi, Shin'ichi Ito, and Jynya Shitakubo. "Hardware Experiments of Autonomous Space Robot – A Demonstration of Truss Structure Assembly –." Journal of Robotics and Mechatronics 12, no. 4 (2000): 343–50. http://dx.doi.org/10.20965/jrm.2000.p0343.
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This paper addresses an experimental system simulating a free-flying space robot, which has been constructed to study autonomous space robots. The experimental system consists of a space robot model, a frictionless table system, a computer system, and a vision sensor system. The robot model composed of two manipulators and a satellite vehicle can move freely on a two-dimensional planar table without friction by using air-bearings. The robot model has successfully performed the automatic truss structure construction including many jobs, e.g., manipulator berthing, component manipulation, arm trajectory control avoiding collision, assembly considering contact with the environment, etc. The experiment demonstrates the possibility of the automatic construction and the usefulness of space robots.
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Wanasinghe, Thumeera R., George K. I. Mann, and Raymond G. Gosine. "Decentralized Cooperative Localization Approach for Autonomous Multirobot Systems." Journal of Robotics 2016 (2016): 1–18. http://dx.doi.org/10.1155/2016/2560573.
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This study proposes the use of a split covariance intersection algorithm (Split-CI) for decentralized multirobot cooperative localization. In the proposed method, each robot maintains a local cubature Kalman filter to estimate its own pose in a predefined coordinate frame. When a robot receives pose information from neighbouring robots, it employs a Split-CI based approach to fuse this received measurement with its local belief. The computational and communicative complexities of the proposed algorithm increase linearly with the number of robots in the multirobot systems (MRS). The proposed method does not require fully connected synchronous communication channels between robots; in fact, it is applicable for MRS with asynchronous and partially connected communication networks. The pose estimation error of the proposed method is bounded. As the proposed method is capable of handling independent and interdependent information of the estimations separately, it does not generate overconfidence state estimations. The performance of the proposed method is compared with several multirobot localization approaches. The simulation and experiment results demonstrate that the proposed algorithm outperforms the single-robot localization algorithms and achieves approximately the same estimation accuracy as the centralized cooperative localization approach, but with reduced computational and communicative cost.
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Fazlollahtabar, Hamed. "An Effective Mathematical Programming Model for Production Automatic Robot Path Planning." Open Transportation Journal 13, no. 1 (2019): 11–16. http://dx.doi.org/10.2174/1874447801913010011.
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Objective: Path planning for production robots has been investigated. The sequence of the orders to be processed in a certain planning horizon has been planned for the production system. Methods: Production automatic robots are employed to carry parts and products among all production stations and machining centers. The combination of machines in stations and autonomous robot evolves a production network. Results: The problem is to assign orders to robots so that paths are obtained to minimize total waiting times of production system and meanwhile provide collision-free paths. Conclusion: The proposed mathematical formulation is implemented to show the efficiency and effectiveness.
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Samadi Gharajeh, Mohammad, and Hossein B. Jond. "Speed Control for Leader-Follower Robot Formation Using Fuzzy System and Supervised Machine Learning." Sensors 21, no. 10 (2021): 3433. http://dx.doi.org/10.3390/s21103433.
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Mobile robots are endeavoring toward full autonomy. To that end, wheeled mobile robots have to function under non-holonomic constraints and uncertainty derived by feedback sensors and/or internal dynamics. Speed control is one of the main and challenging objectives in the endeavor for efficient autonomous collision-free navigation. This paper proposes an intelligent technique for speed control of a wheeled mobile robot using a combination of fuzzy logic and supervised machine learning (SML). The technique is appropriate for flexible leader-follower formation control on straight paths where a follower robot maintains a safely varying distance from a leader robot. A fuzzy controller specifies the ultimate distance of the follower to the leader using the measurements obtained from two ultrasonic sensors. An SML algorithm estimates a proper speed for the follower based on the ultimate distance. Simulations demonstrated that the proposed technique appropriately adjusts the follower robot’s speed to maintain a flexible formation with the leader robot.
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Lerman, Kristina, Aram Galstyan, Alcherio Martinoli, and Auke Ijspeert. "A Macroscopic Analytical Model of Collaboration in Distributed Robotic Systems." Artificial Life 7, no. 4 (2001): 375–93. http://dx.doi.org/10.1162/106454601317297013.
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In this article, we present a macroscopic analytical model of collaboration in a group of reactive robots. The model consists of a series of coupled differential equations that describe the dynamics of group behavior. After presenting the general model, we analyze in detail a case study of collaboration, the stick-pulling experiment, studied experimentally and in simulation by Ijspeert et al. [Autonomous Robots, 11, 149–171]. The robots' task is to pull sticks out of their holes, and it can be successfully achieved only through the collaboration of two robots. There is no explicit communication or coordination between the robots. Unlike microscopic simulations (sensor-based or using a probabilistic numerical model), in which computational time scales with the robot group size, the macroscopic model is computationally efficient, because its solutions are independent of robot group size. Analysis reproduces several qualitative conclusions of Ijspeert et al.: namely, the different dynamical regimes for different values of the ratio of robots to sticks, the existence of optimal control parameters that maximize system performance as a function of group size, and the transition from superlinear to sublinear performance as the number of robots is increased.
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Ledziński, Damian, Tomasz Marciniak, Mirosław Maszewski, and Dariusz Boroński. "Robot Actions Planning Algorithms in Multi-Agent System." Solid State Phenomena 223 (November 2014): 221–30. http://dx.doi.org/10.4028/www.scientific.net/ssp.223.221.
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In this paper, the basic information about multi-agent systems is given. The authors propose robot control algorithms for managing virtual autonomous warehouses, where the task performed by the robots is transportation between specific locations in the warehouse and a number of distribution points. Algorithms control the work of a single robot, including the cooperation with other robots in the environment as well as collisions avoidance. Different routing algorithms are evaluated through simulations focusing on service time and waiting time of executing tasks. The impact of the proposed algorithms on energy consumption was also checked, since this is important for the working time between battery charges.
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Muscolo, Giovanni Gerardo. "HANDSHAKE: HANDling System for Human Autonomous KEeping." International Journal of Humanoid Robotics 18, no. 01 (2021): 2150003. http://dx.doi.org/10.1142/s0219843621500031.
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This paper presents a novel biped-wheeled-wearable machine, named HANDSHAKE, and obtained by an evolution of two robots presented in other works: one flexible-wheeled leg and one biped-flexible-wheeled robot. A critical design analysis of these two robots helped the author to propose a novel machine able to revolutionize the lower body exoskeletons’ world. Conceptual and functional design, mechanical behavior (kinematics and dynamics), and multibody simulation of the biped-wheeled exoskeleton are presented in this paper, and a first reduced scale prototype is used to show the feasibility of the proposed solution. The simple control architecture used in this work underlines the enormous advantages to use the HANDSHAKE system for people with a complete absence of mobility, which are completely supported by this machine. This is possible thanks to the wheeled feet of the HANDSHAKE system which allow to support more weights respect to the classical exoskeletons, available on market and literature. The proposed machine increases stability, dynamic balance, autonomy, reducing power supply and complexity in comparison with classical exoskeleton systems because the wheeled feet are always in contact with the ground. These advantages, recognized in humanoid robots, may be used also in exoskeletons.
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Dasgupta, Prithviraj, José Baca, K. R. Guruprasad, Angélica Muñoz-Meléndez, and Janyl Jumadinova. "The COMRADE System for Multirobot Autonomous Landmine Detection in Postconflict Regions." Journal of Robotics 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/921370.
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We consider the problem of autonomous landmine detection using a team of mobile robots. Previous research on robotic landmine detection mostly employs a single robot equipped with a landmine detection sensor to detect landmines. We envisage that the quality of landmine detection can be significantly improved if multiple robots are coordinated to detect landmines in a cooperative manner by incrementally fusing the landmine-related sensor information they collect and then use that information to visit locations of potential landmines. Towards this objective, we describe a multirobot system called COMRADES to address different aspects of the autonomous landmine detection problem including distributed area coverage to detect and locate landmines, information aggregation to fuse the sensor information obtained by different robots, and multirobot task allocation (MRTA) to enable different robots to determine a suitable sequence to visit locations of potential landmines while reducing the time required and battery expended. We have used commercially available all-terrain robots called Coroware Explorer that are customized with a metal detector to detect metallic objects including landmines, as well as indoor Corobot robots, both in simulation and in physical experiments, to test the different techniques in COMRADES.
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Farias, Gonzalo, Ernesto Fabregas, Enrique Torres, Gaëtan Bricas, Sebastián Dormido-Canto, and Sebastián Dormido. "A Distributed Vision-Based Navigation System for Khepera IV Mobile Robots." Sensors 20, no. 18 (2020): 5409. http://dx.doi.org/10.3390/s20185409.
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This work presents the development and implementation of a distributed navigation system based on object recognition algorithms. The main goal is to introduce advanced algorithms for image processing and artificial intelligence techniques for teaching control of mobile robots. The autonomous system consists of a wheeled mobile robot with an integrated color camera. The robot navigates through a laboratory scenario where the track and several traffic signals must be detected and recognized by using the images acquired with its on-board camera. The images are sent to a computer server that performs a computer vision algorithm to recognize the objects. The computer calculates the corresponding speeds of the robot according to the object detected. The speeds are sent back to the robot, which acts to carry out the corresponding manoeuvre. Three different algorithms have been tested in simulation and a practical mobile robot laboratory. The results show an average of 84% success rate for object recognition in experiments with the real mobile robot platform.
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Rodriguez y Baena, Ferdinando, and Brian Davies. "Robotic surgery: from autonomous systems to intelligent tools." Robotica 28, no. 2 (2009): 163–70. http://dx.doi.org/10.1017/s0263574709990427.
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SUMMARYA brief history of robotic surgery is provided, which describes the transition from autonomous robots to hands-on systems that are under the direct control of the surgeon. An example of the latter is the Acrobot (for active-constraint robot) system used in orthopaedics, whilst soft-tissue surgery is illustrated by the daVinci telemanipulator system. Non-technological aspects of robotic surgery have often been a major impediment to their widespread clinical use. These are discussed in detail, together with the role of navigation systems, which are considered a major competitor to surgical robots. A detailed description is then given of a registration method for robots to achieve improved accuracy. Registration is a major source of error in robotic surgery, particularly in orthopaedics. The paper describes the design and clinical implementation of a novel method, coined the bounded registration method, applied to minimally invasive registration of the femur. Results of simulations which compare the performance of bounded registration with a standard implementation of the iterative closest point algorithm are also presented, alongside a description of their application in the Acrobot hands-on robot, used clinically for uni-condylar knee arthroplasty.
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Yasuda, Toshiyuki, and Kazuhiro Ohkura. "Autonomous Role Assignment in a Homogeneous Multi-Robot System." Journal of Robotics and Mechatronics 17, no. 5 (2005): 596–604. http://dx.doi.org/10.20965/jrm.2005.p0596.
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This paper describes an approach for controlling an autonomous homogeneous multi-robot system. An extremely important topic for this type of system is the design of an on-line autonomous behavior acquisition mechanism that is capable of developing cooperative roles as well as assigning them to a robot appropriately in a noisy embedded environment. Our approach applies reinforcement learning that adopts the Bayesian discrimination method for segmenting a continuous state space and a continuous action space simultaneously. In addition, a neural network is provided for predicting the average of the other robots’ postures at the next time step in order to stabilize the reinforcement learning environment. The proposed method is validated through computer simulations as well as our hand-made multi-robot system.
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Foster, Kevin L., and Mikel D. Petty. "Estimating the tactical impact of robot swarms using a semi-automated forces system and design of experiments methods." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 18, no. 3 (2021): 247–69. http://dx.doi.org/10.1177/15485129211008532.
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Militaries are developing autonomous robots to conduct missions such as reconnaissance and surveillance. Some of those robots are intended to operate in swarms. Because operational robot swarms are not yet available, doctrine developers will initially use constructive entity-level combat models to develop and test tactics for robot swarms. Design of experiments methods and retrodiction of the 1991 Battle of 73 Easting between US and Iraqi forces were used to calibrate a semi-automated forces system. The calibrated combat model was then used to estimate the tactical impact of a notional Iraqi robot swarm conducting reconnaissance and surveillance in that battle. The calibration ensured that the model’s parameters were accurate, enabling a reliable estimate of the swarm’s tactical impact. Additionally, the design of experiments methods produced estimates of the interaction of the robot swarm’s effect with the technologies of the combatants’ weapon systems. Simulation trials and statistical analysis showed that the tactical benefits of an Iraqi robot swarm were overshadowed by the advantage provided by the US forces’ thermal sights. However, additional trials indicated that if both sides had been equipped with optical sights only, the early warning provided to the Iraqi forces by a robot swarm could have had a significant effect on the battle’s outcome.
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Ando, Teruaki, and Masayoshi Kanoh. "Psychological Effects of a Self-Sufficiency Model Based on Urge System." Journal of Advanced Computational Intelligence and Intelligent Informatics 14, no. 7 (2010): 877–84. http://dx.doi.org/10.20965/jaciii.2010.p0877.
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In recent years, robots to coexist with humans have been developed. Their ability to communicate is indispensable for their coexistence with humans, so studies on the interaction between humans and robots are important. This paper proposes a model of the selfsufficiency system of a robot, in which we apply the urge system to the autonomous system of emotion. In this model, a robot expresses its changing psychological and physiological conditions (physiological load condition) and conveys them sensitively to the user. This is expected to result in a mental interaction effect between the user and the agent. We carry out simulation experiments on this model and verify the psychological interaction between the software robot (agent) and the user. As a result of these experiments, it is recognized that the agents with the ability to properly express physiological load among those with this model implemented have a tendency to receive higher evaluations from their users.
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Adachi, Yoshinobu, and Masayoshi Kakikura. "Research on the Sheepdog Problem Using Cellular Automata." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 9 (2007): 1099–106. http://dx.doi.org/10.20965/jaciii.2007.p1099.
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The simulation framework we propose for complex path planning problems with multiagent systems focuses on the sheepdog problem for handling distributed autonomous robot systems – an extension of the pursuit problem for handling one prey robot and multiple predator robot. The sheepdog problem involves a more complex issue in which multiple dog robot chase and herd multiple sheep robot. We use the Boids model and cellular automata to model sheep flocking and chase and herd behavior for dog robots. We conduct experiments using a Sheepdog problem simulator and study cooperative behavior.
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Yu, Xiaojun, Zeming Fan, Hao Wan, et al. "Positioning, Navigation, and Book Accessing/Returning in an Autonomous Library Robot using Integrated Binocular Vision and QR Code Identification Systems." Sensors 19, no. 4 (2019): 783. http://dx.doi.org/10.3390/s19040783.
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With rapid advancements in artificial intelligence and mobile robots, some of the tedious yet simple jobs in modern libraries, like book accessing and returning (BAR) operations that had been fulfilled manually before, could be undertaken by robots. Due to the limited accuracies of the existing positioning and navigation (P&N) technologies and the operational errors accumulated within the robot P&N process, however, most of the current robots are not able to fulfill such high-precision operations. To address these practical issues, we propose, for the first time (to the best of our knowledge), to combine the binocular vision and Quick Response (QR) code identification techniques together to improve the robot P&N accuracies, and then construct an autonomous library robot for high-precision BAR operations. Specifically, the binocular vision system is used for dynamic digital map construction and autonomous P&N, as well as obstacle identification and avoiding functions, while the QR code identification technique is responsible for both robot operational error elimination and robotic arm BAR operation determination. Both simulations and experiments are conducted to verify the effectiveness of the proposed technique combination, as well as the constructed robot. Results show that such a technique combination is effective and robust, and could help to significantly improve the P&N and BAR operation accuracies, while reducing the BAR operation time. The implemented autonomous robot is fully-autonomous and cost-effective, and may find applications far beyond libraries with only sophisticated technologies employed.
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TONG, FUNG-LING, and MAX Q. H. MENG. "GENETIC ALGORITHM BASED VISUAL LOCALIZATION FOR A ROBOT PET IN HOME HEALTHCARE SYSTEM." International Journal of Information Acquisition 04, no. 02 (2007): 141–60. http://dx.doi.org/10.1142/s021987890700123x.
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The simultaneous localization and mapping technique is an important requirement in the development autonomous robot. Many localization algorithms for wheeled robots using various sensors have been proposed. In this article, we present a visual localization algorithm for a small home-use robot pet (legged robot). A low-resolution camera is equipped on the robot as the only sensor for localization. Challenges of visual localization for legged robots include: (1) Unmodeled motion errors due to leg slippages are common in legged robot, (2) as the oscillated walking motion of robot leads to fluctuated sensor data, the high degree of freedom of legged robot increases the complexity of the localization problem and (3) camera has limited field of view and image points lack of depth information. In the proposed algorithm, the localization for high-dimensional movement robot is modeled as an optimization. The objective function is then solved by a genetic algorithm. Approaches to (1) increase the efficiency of the search and (2) weaken the influence of noisy feature points to the localization results are presented. Results from simulations show that the proposed algorithm is able to localize the legged robot accurately and efficiently.
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Ampatzis, Christos, Elio Tuci, Vito Trianni, Anders Lyhne Christensen, and Marco Dorigo. "Evolving Self-Assembly in Autonomous Homogeneous Robots: Experiments with Two Physical Robots." Artificial Life 15, no. 4 (2009): 465–84. http://dx.doi.org/10.1162/artl.2009.ampatzis.013.
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This research work illustrates an approach to the design of controllers for self-assembling robots in which the self-assembly is initiated and regulated by perceptual cues that are brought forth by the physical robots through their dynamical interactions. More specifically, we present a homogeneous control system that can achieve assembly between two modules (two fully autonomous robots) of a mobile self-reconfigurable system without a priori introduced behavioral or morphological heterogeneities. The controllers are dynamic neural networks evolved in simulation that directly control all the actuators of the two robots. The neurocontrollers cause the dynamic specialization of the robots by allocating roles between them based solely on their interaction. We show that the best evolved controller proves to be successful when tested on a real hardware platform, the swarm-bot. The performance achieved is similar to the one achieved by existing modular or behavior-based approaches, also due to the effect of an emergent recovery mechanism that was neither explicitly rewarded by the fitness function, nor observed during the evolutionary simulation. Our results suggest that direct access to the orientations or intentions of the other agents is not a necessary condition for robot coordination: Our robots coordinate without direct or explicit communication, contrary to what is assumed by most research works in collective robotics. This work also contributes to strengthening the evidence that evolutionary robotics is a design methodology that can tackle real-world tasks demanding fine sensory-motor coordination.
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Faíña, Andrés, Lars Toft Jacobsen, and Sebastian Risi. "Automating the Incremental Evolution of Controllers for Physical Robots." Artificial Life 23, no. 2 (2017): 142–68. http://dx.doi.org/10.1162/artl_a_00226.
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Evolutionary robotics is challenged with some key problems that must be solved, or at least mitigated extensively, before it can fulfill some of its promises to deliver highly autonomous and adaptive robots. The reality gap and the ability to transfer phenotypes from simulation to reality constitute one such problem. Another lies in the embodiment of the evolutionary processes, which links to the first, but focuses on how evolution can act on real agents and occur independently from simulation, that is, going from being, as Eiben, Kernbach, & Haasdijk [2012, p. 261] put it, “the evolution of things, rather than just the evolution of digital objects.…” The work presented here investigates how fully autonomous evolution of robot controllers can be realized in hardware, using an industrial robot and a marker-based computer vision system. In particular, this article presents an approach to automate the reconfiguration of the test environment and shows that it is possible, for the first time, to incrementally evolve a neural robot controller for different obstacle avoidance tasks with no human intervention. Importantly, the system offers a high level of robustness and precision that could potentially open up the range of problems amenable to embodied evolution.
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Zanlongo, Sebastián A., Peter Dirksmeier, Philip Long, Taskin Padir, and Leonardo Bobadilla. "Scheduling and Path-Planning for Operator Oversight of Multiple Robots." Robotics 10, no. 2 (2021): 57. http://dx.doi.org/10.3390/robotics10020057.
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There is a need for semi-autonomous systems capable of performing both automated tasks and supervised maneuvers. When dealing with multiple robots or robots with high complexity (such as humanoids), we face the issue of effectively coordinating operators across robots. We build on our previous work to present a methodology for designing trajectories and policies for robots such that a few operators can supervise multiple robots. Specifically, we: (1) Analyze the complexity of the problem, (2) Design a procedure for generating policies allowing operators to oversee many robots, (3) Present a method for designing policies and robot trajectories to allow operators to oversee multiple robots, and (4) Include both simulation and hardware experiments demonstrating our methodologies.
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Dirik, Castillo, and Kocamaz. "Gaze-Guided Control of an Autonomous Mobile Robot Using Type-2 Fuzzy Logic." Applied System Innovation 2, no. 2 (2019): 14. http://dx.doi.org/10.3390/asi2020014.
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Motion control of mobile robots in a cluttered environment with obstacles is an important problem. It is unsatisfactory to control a robot’s motion using traditional control algorithms in a complex environment in real time. Gaze tracking technology has brought an important perspective to this issue. Gaze guided driving a vehicle based on eye movements supply significant features of nature task to realization. This paper presents an intelligent vision-based gaze guided robot control (GGC) platform that uses a user-computer interface based on gaze tracking enables a user to control the motion of a mobile robot using eyes gaze coordinate as inputs to the system. In this paper, an overhead camera, eyes tracking device, a differential drive mobile robot, vision and interval type-2 fuzzy inference (IT2FIS) tools are utilized. The methodology incorporates two basic behaviors; map generation and go-to-goal behavior. Go-to-goal behavior based on an IT2FIS is more soft and steady progress in data processing with uncertainties to generate better performance. The algorithms are implemented in the indoor environment with the presence of obstacles. Experiments and simulation results indicated that intelligent vision-based gaze guided robot control (GGC) system can be successfully applied and the IT2FIS can successfully make operator intention, modulate speed and direction accordingly.
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Brugali, Davide, and Nico Hochgeschwender. "Software Product Line Engineering for Robotic Perception Systems." International Journal of Semantic Computing 12, no. 01 (2018): 89–107. http://dx.doi.org/10.1142/s1793351x18400056.
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Control systems for autonomous robots are concurrent, distributed, embedded, real-time and data intensive software systems. A real-world robot control system is composed of tens of software components. For each component providing robotic functionality, tens of different implementations may be available. The difficult challenge in robotic system engineering consists in selecting a coherent set of components, which provide the functionality required by the application requirements, taking into account their mutual dependencies. This challenge is exacerbated by the fact that robotics system integrators and application developers are usually not specifically trained in software engineering. In various application domains, software product line (SPL) development has proven to be the most effective approach to face this kind of challenges. In a previous paper [D. Brugali and N. Hochgeschwender, Managing the functional variability of robotic perception systems, in First IEEE Int. Conf. Robotic Computing, 2017, pp. 277–283.] we have presented a model-based approach to the development of SPL for robotic perception systems, which integrates two modeling technologies developed by the authors: The HyperFlex toolkit [L. Gherardi and D. Brugali, Modeling and reusing robotic software architectures: The HyperFlex toolchain, in IEEE Int. Conf. Robotics and Automation, 2014, pp. 6414–6420.] and the Robot Perception Specification Language (RPSL) [N. Hochgeschwender, S. Schneider, H. Voos and G. K. Kraetzschmar, Declarative specification of robot perception architectures, in 4th Int. Conf. Simulation, Modeling, and Programming for Autonomous Robots, 2014, pp. 291–302.]. This paper extends our previous work by illustrating the entire development process of an SPL for robot perception systems with a real case study.
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Lang, Haoxiang, Muhammad Tahir Khan, Kok-Kiong Tan, and Clarence W. W. De Silva. "Application of Visual Servo Control in Autonomous Mobile Rescue Robots." International Journal of Computers Communications & Control 11, no. 5 (2016): 685. http://dx.doi.org/10.15837/ijccc.2016.5.2680.
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Mobile robots that integrate visual servo control for facilitating autonomous grasping nd manipulation are the focus of this paper. In view of mobility, they have wider pplication than traditional fixed-based robots with visual servoing. Visual servoing s widely used in mobile robot navigation. However, there are not so many report or applying it to mobile manipulation. In this paper, challenges and limitations of pplying visual servoing in mobile manipulation are discussed. Next, two classical pproaches (image-based visual servoing (IBVS) and position-based visual servoing (PBVS)) are introduced aloing with their advantages and disadvantages. Simulations n Matlab are carried out using the two methods, there advantages and drawbacks are llustrated and discussed. On this basis, a suggested system in mobile manipulation s proposed including an IBVS with an eye-in-hand camera configuration system. imulations and experimentations are carried with this robot configuration in a earch and rescue scenario, which show good performance.
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Le, Yanqun, Hiroyuki Kojima, and Kazuhiko Matsuda. "Cooperative Obstacle-Avoidance Pushing Transportation of a Planar Object with One Leader and Two Follower Mobile Robots." Journal of Robotics and Mechatronics 17, no. 1 (2005): 77–88. http://dx.doi.org/10.20965/jrm.2005.p0077.
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This paper proposes a cooperative obstacle-avoidance pushing transportation system using one leader and two follower mobile robots. Its usefulness and effectiveness are illustrated and confirmed numerically as well as experimentally. The cooperative obstacle-avoidance pushing transportation control consists of the obstacle configuration measurement phase by the leader mobile robot, the trajectory-planning phase and the pushing transfer control phase by the two follower mobile robots. In the obstacle configuration measurement phase, the leader mobile robot moves by use of the obstacle-avoidance vehicle control method constructed with six infrared sensors and the pattern recognition algorithm, and three waypoints for the trajectory planning of the follower mobile robots are extracted. In the trajectory-planning phase, the two follower mobile robots receive the three modified waypoints from the leader mobile robot through wireless communication systems, and the obstacle-avoidance trajectories by use of cubic spiral and straight-line segments are generated. Then, in the pushing transfer control phase, a planar object is transported with the pushing and constraining forces resulting from the passive compliance mechanisms attached to the follower mobile robots, and the shock is effectively reduced by the passive compliance mechanisms. From the numerical simulation and experimental results using autonomous mobile robots (MK-01X developed by Fuji Heavy Industries Ltd.), it is confirmed that the planar object can be successfully transported by pushing from the start configuration to the goal in spite of the existence of the obstacle.
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Tanaka, Takayuki, Kazuo Yamafuji, and Hidenori Takahashi. "Development of the Intelligent Mobile Robot for Service Use Report 1: Environmental-Adjustable Autonomous Locomotion Control System." Journal of Robotics and Mechatronics 9, no. 4 (1997): 275–82. http://dx.doi.org/10.20965/jrm.1997.p0275.
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We have developed an intelligent mobile robot for use as an office “secretary/ helper” by day and “security maintenance guard” by night. The robot’s autonomous locomotion control system (ALCS) plans its paths, recognizes absolute positions and learns navigation control. To aid the robot in moving more appropriately and smoothly among human beings and obstacles in an office environment, we studied learning by a fuzzy neural network that tunes membership functions for fuzzy locomotion control, i.e., the intelligent robot learns to move autonomously through its surroundings. Results obtained by computer simulation show the proposed method is useful in autonomous robot locomotion control.
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Loianno, Giuseppe, Yash Mulgaonkar, Chris Brunner, et al. "Autonomous flight and cooperative control for reconstruction using aerial robots powered by smartphones." International Journal of Robotics Research 37, no. 11 (2018): 1341–58. http://dx.doi.org/10.1177/0278364918774136.
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Advances in consumer electronics products and the technology seen in personal computers, digital cameras, and smartphones phones have led to the price/performance ratio of sensors and processors falling dramatically over the last decade. In particular, many consumer products are packaged with small cameras, gyroscopes, and accelerometers, all sensors that are needed for autonomous robots in GPS-denied environments. The low mass and small form factor make them particularly well suited for autonomous flight with small flying robots. In this work, we present the first fully autonomous smartphone-based system for quadrotors. We show how multiple quadrotors can be stabilized and controlled to achieve autonomous flight in indoor buildings with application to smart homes, search and rescue, monitoring construction projects, and developing models for architecture design. In our work, the computation for sensing and control runs on an off-the-shelf smartphone, with all the software functionality embedded in a smartphone app. No additional sensors or processors are required for autonomous flight. We are also able to use multiple, coordinated autonomous aerial vehicles to improve the efficiency of our mission. In our framework, multiple vehicles are able to plan safe trajectories avoiding inter-robot collisions, while concurrently building in a cooperative manner a three-dimensional map of the environment. The work allows any consumer with any number of robots equipped with smartphones to autonomously drive a team of quadrotor robots, even without GPS, by downloading our app and cooperatively build three-dimensional maps.
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Fan, Tingxiang, Pinxin Long, Wenxi Liu, and Jia Pan. "Distributed multi-robot collision avoidance via deep reinforcement learning for navigation in complex scenarios." International Journal of Robotics Research 39, no. 7 (2020): 856–92. http://dx.doi.org/10.1177/0278364920916531.
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Developing a safe and efficient collision-avoidance policy for multiple robots is challenging in the decentralized scenarios where each robot generates its paths with limited observation of other robots’ states and intentions. Prior distributed multi-robot collision-avoidance systems often require frequent inter-robot communication or agent-level features to plan a local collision-free action, which is not robust and computationally prohibitive. In addition, the performance of these methods is not comparable with their centralized counterparts in practice. In this article, we present a decentralized sensor-level collision-avoidance policy for multi-robot systems, which shows promising results in practical applications. In particular, our policy directly maps raw sensor measurements to an agent’s steering commands in terms of the movement velocity. As a first step toward reducing the performance gap between decentralized and centralized methods, we present a multi-scenario multi-stage training framework to learn an optimal policy. The policy is trained over a large number of robots in rich, complex environments simultaneously using a policy-gradient-based reinforcement-learning algorithm. The learning algorithm is also integrated into a hybrid control framework to further improve the policy’s robustness and effectiveness. We validate the learned sensor-level collision-3avoidance policy in a variety of simulated and real-world scenarios with thorough performance evaluations for large-scale multi-robot systems. The generalization of the learned policy is verified in a set of unseen scenarios including the navigation of a group of heterogeneous robots and a large-scale scenario with 100 robots. Although the policy is trained using simulation data only, we have successfully deployed it on physical robots with shapes and dynamics characteristics that are different from the simulated agents, in order to demonstrate the controller’s robustness against the simulation-to-real modeling error. Finally, we show that the collision-avoidance policy learned from multi-robot navigation tasks provides an excellent solution for safe and effective autonomous navigation for a single robot working in a dense real human crowd. Our learned policy enables a robot to make effective progress in a crowd without getting stuck. More importantly, the policy has been successfully deployed on different types of physical robot platforms without tedious parameter tuning. Videos are available at https://sites.google.com/view/hybridmrca .
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Nurhafizah Anual, Siti, Mohd Faisal Ibrahim, Nurhana Ibrahim, et al. "GA-based Optimisation of a LiDAR Feedback Autonomous Mobile Robot Navigation System." Bulletin of Electrical Engineering and Informatics 7, no. 3 (2018): 433–41. http://dx.doi.org/10.11591/eei.v7i3.1275.
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Autonomous mobile robots require an efficient navigation system in order to navigate from one location to another location fast and safe without hitting static or dynamic obstacles. A light-detection-and-ranging (LiDAR) based autonomous robot navigation is a multi-component navigation system consists of various parameters to be configured. With such structure and sometimes involving conflicting parameters, the process of determining the best configuration for the system is a non-trivial task. This work presents an optimisation method using Genetic algorithm (GA) to configure such navigation system with tuned parameters automatically. The proposed method can optimise parameters of a few components in a navigation system concurrently. The representation of chromosome and fitness function of GA for this specific robotic problem are discussed. The experimental results from simulation and real hardware show that the optimised navigation system outperforms a manually-tuned navigation system of an indoor mobile robot in terms of navigation time.
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Hoshino, Satoshi, Ryo Takisawa, and Yutaka Kodama. "Swarm Robotic Systems Based on Collective Behavior of Chloroplasts." Journal of Robotics and Mechatronics 29, no. 3 (2017): 602–12. http://dx.doi.org/10.20965/jrm.2017.p0602.
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[abstFig src='/00290003/15.jpg' width='300' text='Swarming chloroplastic robots around light source' ] In this paper, distributed autonomous robots are used to perform area coverage tasks. In order for robots to cover the ground surface of environments, the coordination of a team of robots is a challenge. For this challenge, we present bio-inspired swarm robotic systems. We focus on the collective behavior of chloroplasts toward a light source. On the basis of the mechanism of the chloroplast, we propose robot behavior models that do not use local communication. The emergence of cooperative behavior through the interaction among the swarming robots is a main contribution of this paper. Based on simulation results, the effectiveness of the chloroplastic robots for the coverage task is discussed in terms of flexibility and scalability. Furthermore, the behavioral models are applied to actual mobile robots. Based on the results of experiments, the applicability of the chloroplastic robots to real environments is discussed. As an application of the swarm robotic system, a specific task, sweeping, is given to actual chloroplastic robots.
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Parhi, D. R., and M. K. Singh. "Real-time navigational control of mobile robots using an artificial neural network." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 223, no. 7 (2009): 1713–25. http://dx.doi.org/10.1243/09544062jmes1410.
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This article deals with the reactive control of an autonomous robot, which moves safely in a crowded real-world unknown environment and reaches a specified target by avoiding static as well as dynamic obstacles. The inputs to the proposed neural controller consist of left, right, and front obstacle distance to its locations and the target angle between a robot and a specified target acquired by an array of sensors. A four-layer neural network has been used to design and develop the neural controller to solve the path and time optimization problem of mobile robots, which deals with cognitive tasks such as learning, adaptation, generalization, and optimization. The back-propagation method is used to train the network. This article analyses the kinematical modelling of mobile robots as well as the design of control systems for the autonomous motion of the robot. Training of the neural net and control performances analysis were carried out in a real experimental set-up. The simulation results are compared with the experimental results and they show very good agreement.
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Torres-Torriti, M., T. Arredondo, and P. Castillo-Pizarro. "Survey and comparative study of free simulation software for mobile robots." Robotica 34, no. 4 (2014): 791–822. http://dx.doi.org/10.1017/s0263574714001866.
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SUMMARYIn robotics, simulation has become an essential tool for research, education, and design purposes. Various software tools for mobile robot simulation have been developed and have reached different levels of maturity in recent years. This paper presents a general survey of mobile robot simulation tools and discusses qualitative and quantitative aspects of selection of four major simulators publicly available at no cost: Carmen, Player-Stage-Gazebo, Open Dynamics Engine, and Microsoft Robotics Developer Studio. The comparison of the simulators is aimed at establishing the range of applications for which these are best suited as well as their accuracy for certain simulation tasks. The simulators chosen for detailed comparison were selected considering their level of maturity, modularity, and popularity among engineers and researchers. The qualitative comparison included a discussion of relevant features. The quantitative analysis entailed the development of a detailed dynamical model of a mobile robot on a road with varying slope. This model was used as benchmark to compare the accuracy of each simulator. The validity of the simulated results was also contrasted against measurements obtained from experiments with a real robot. This research and analysis should be very valuable to educators, engineers, and researchers who are always seeking adequate tools for simulating autonomous mobile robots.
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Masaki, Takuya, and Kentarou Kurashige. "Decision Making Under Multi Task Based on Priority for Each Task." International Journal of Artificial Life Research 6, no. 2 (2016): 88–98. http://dx.doi.org/10.4018/ijalr.2016070105.
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In recent years, autonomous robots become to be desired to treat multi-task. A robot must decide a concrete action for plural objectives. Major researches try to realize this by weighted rewards. Weighted rewards can represent a human's intention easily. But weight of each task must change dynamically by a change of surrounding situation or of a robot status. Authors consider an independent learning for each task and selection of one concrete action from candidates of each learning. Authors propose a priority function to calculate priority for each task corresponding to surrounding situation or a robot status and propose a system which do decision making by using the priority function. Authors confirmed the usefulness of proposed method with simulation.
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Lidoris, Georgios, Florian Rohrmüller, Dirk Wollherr, and Martin Buss. "System interdependence analysis for autonomous robots." International Journal of Robotics Research 30, no. 5 (2011): 601–14. http://dx.doi.org/10.1177/0278364910393040.
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With the increasing complexity of robotic systems, system robustness and efficiency are harder to achieve, since they are determined by the interplay of all of a system’s components. In order to improve the robustness of such systems, it is essential to identify the system components that are crucial for each task and the extent to which they are affected by other components and the environment. Such knowledge will help developers to improve their systems, and can also be directly utilized by the systems themselves, for example, to detect failures and thereby correctly adjust the system’s behavior. In this article a method of system interdependence analysis is presented. The basic idea is to learn and quantitatively evaluate the coherence between performance indicators of different system components, as well as the influence of environmental parameters on the system. To validate the proposed approach, system interdependence analysis is applied to the navigation system of an autonomous mobile robot. Its navigational methods are presented and suitable indicators are derived. The results of using the method, based on experimental data from an extended field experiment, are given.
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Krell, Evan, Alaa Sheta, Arun Prassanth Ramaswamy Balasubramanian, and Scott A. King. "Collision-Free Autonomous Robot Navigation in Unknown Environments Utilizing PSO for Path Planning." Journal of Artificial Intelligence and Soft Computing Research 9, no. 4 (2019): 267–82. http://dx.doi.org/10.2478/jaiscr-2019-0008.
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Abstract The autonomous navigation of robots in unknown environments is a challenge since it needs the integration of a several subsystems to implement different functionality. It needs drawing a map of the environment, robot map localization, motion planning or path following, implementing the path in real-world, and many others; all have to be implemented simultaneously. Thus, the development of autonomous robot navigation (ARN) problem is essential for the growth of the robotics field of research. In this paper, we present a simulation of a swarm intelligence method is known as Particle Swarm Optimization (PSO) to develop an ARN system that can navigate in an unknown environment, reaching a pre-defined goal and become collision-free. The proposed system is built such that each subsystem manipulates a specific task which integrated to achieve the robot mission. PSO is used to optimize the robot path by providing several waypoints that minimize the robot traveling distance. The Gazebo simulator was used to test the response of the system under various envirvector representing a solution to the optimization problem.onmental conditions. The proposed ARN system maintained robust navigation and avoided the obstacles in different unknown environments. vector representing a solution to the optimization problem.
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Looi, Chen Zheng, and Danny Wee Kiat Ng. "A Study on the Effect of Parameters for ROS Motion Planer and Navigation System for Indoor Robot." International Journal of Electrical and Computer Engineering Research 1, no. 1 (2021): 29–36. http://dx.doi.org/10.53375/ijecer.2021.21.
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In the past decades, the service robot industry had risen rapidly. The office assistant robot is one type of service robot used to assist officers in an office environment. For the robot to navigate autonomously in the office, navigation algorithms and motion planners were implemented on these robots. Robot Operating System (ROS) is one of the common platforms to develop these robots. The parameters applied to the motion planners will affect the performance of the Robot. In this study, the global planners, A* and Dijkstra algorithm and local planners, Dynamic Window Approach (DWA) and Time Elastic Band (TEB) algorithms were implemented and tested on a robot in simulation and a real environment. Results from the experiments were used to evaluate and compare the performance of the robot with different planners and parameters. Based on the results obtained, the global planners, A* and Dijkstra algorithm both can achieve the required performance for this application whereas TEB outperforms DWA as the local planner due to its feasibility in avoiding dynamic obstacles in the experiments conducted.
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Monje, Concepción A., Paolo Pierro, and Carlos Balaguer. "Humanoid Robot RH-1 for Collaborative Tasks: A Control Architecture for Human-Robot Cooperation." Applied Bionics and Biomechanics 5, no. 4 (2008): 225–34. http://dx.doi.org/10.1155/2008/382505.
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The full-scale humanoid robot RH-1 has been totally developed in the University Carlos III of Madrid. In this paper we present an advanced control system for this robot so that it can perform tasks in cooperation with humans. The collaborative tasks are carried out in a semi-autonomous way and are intended to be put into operation in real working environments where humans and robots should share the same space. Before presenting the control strategy, the kinematic model and a simplified dynamic model of the robot are presented. All the models and algorithms are verified by several simulations and experimental results.
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Ruan, Kaicheng, Zehao Wu, and Qingsong Xu. "Smart Cleaner: A New Autonomous Indoor Disinfection Robot for Combating the COVID-19 Pandemic." Robotics 10, no. 3 (2021): 87. http://dx.doi.org/10.3390/robotics10030087.
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The COVID-19 pandemic imposes an increasing demand for service robots as a substitute for humans to conduct various types of work in contaminated areas. Such work includes logistics, patient care, and disinfection, which can reduce the risk of human exposure to the highly contagious and deadly virus. This paper presents the design and development of Smart Cleaner, which is a new cost-effective autonomous indoor disinfection robot. It integrates a wheeled mobile robot platform and a hydrogen peroxide atomization device for automated disinfection operation in the complex indoor environment. Through the system integration of various hardware components and software programming, a prototype of the disinfection robot has been fabricated for experimental investigation. A simulation study of the drymist hydrogen peroxide disinfection model was carried out to understand the diffusion of disinfectant in a room environment. The effectiveness of the developed robot was verified in practical scenarios, such as hospital, hotel, office, and laboratory. The effect of disinfection was validated by a qualified third-party testing agency. Results demonstrate the high efficiency of the developed disinfection robot dedicated to autonomous indoor disinfection work.
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Kawasaki, Haruhisa. "Special Issue on Analysis and Simulation Systems for Robotics and Mechatronics." Journal of Robotics and Mechatronics 10, no. 6 (1998): 463. http://dx.doi.org/10.20965/jrm.1998.p0463.
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Superior analysis and simulation systems play an important part in robotics and mechatronics R&D. Developing apparatuses involves repeating planning, trial manufacture, experiments, analysis, and improvement. Simulation and analysis are now executed before trial manufacture, decreasing the number of trial manufacture, shortening development, and cutting development cost. Virtual reality is often applied to simulation, and commercialization without trial manufactures will eventually be possible. Most commercialized simulation software are being improved for general use based on software made by researchers because existing analysis and simulation do not function sufficiently and researchers are often required to develop their own analysis and simulation. Simulation developed for research thus may be used by many technical experts and researchers in the future. This special issue introduces seven reports on basic mechanism analysis developed to survey simulation research. Michisuke Jo et al. developed a mechanism kinetic analysis Motor Drive using FORTRAN and MATLAB. This article, entitled Kinematic Analysis of Mechanisms Using Motor Algebra and Graph Theory, considers kinematic analysis method using the latest drive version. Haruhisa Kawasaki et al. are developing robot analysis ROSAM II using C and Maple V. This article, entitled Symbolic Analysis of Robot Base Parameter Set Using Grobner-Basis, considers base parameter analysis of general robots with closed links. Hajime Morikawa et al. developed a robot simulator kinematically simulated by connecting graphic icons. This article, entitled Network-Based Robot Simulator Using Hierarchical Graphic Icons, considers construction of a robot simulator, kinetic analysis of multiple robot arms, dynamic analysis of forest trimmers, and an example applying remote control to space robots. Shigeki Toyama et al. developed general-use mechanism analysis simulator AI MOTION. This article, entitled Dynamic Autonomous Car Mobile Analysis Simulating Mechanical Systems Analysis, considers an autonomous car travel simulator dynamically modeling tires combined into AI MOTION. The simulator analyzes the connection of tire rigidity, car width, caster radius, and motion performance. Takayoshi Muto et al. developed dynamic behavior simulator BDSP for hydraulic systems. This article, entitled Software Package BDSP Developed to Simulate Hydraulic Systems, considers construction of BDSP that analyzes hydraulic systems using easy block diagrams. The simulator analyzes fluid line, nonlinear elements, and discrete time control. Shinichi Nakajima et al. developed a two-dimensional jaw movement simulator for clarifying the function of muscles in lower jaw motion. This article, entitled Development of 2-D Jaw Movement Simulator(JSN/SI), considers hardware and a control system for chewing food at a required force. Yoshiyuki Sankai et al., in Robot Objective Parallel Calculation and Real-time Control Using a Digital Signal Processor, consider parallel distributed and realtime control by DSP for constructing control in an actual robot. This issue discussed analysis and simulation developed for robotics and mechatronics R&D. Most systems are applicable to general-purpose situations. We hope this issue helps deepen the understanding of the status and applications of simulation research in mechatronics and promotes further development in the field.
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Zhu, Qidan, Yu Han, Peng Liu, Yao Xiao, Peng Lu, and Chengtao Cai. "Motion Planning of Autonomous Mobile Robot Using Recurrent Fuzzy Neural Network Trained by Extended Kalman Filter." Computational Intelligence and Neuroscience 2019 (January 29, 2019): 1–16. http://dx.doi.org/10.1155/2019/1934575.
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This paper proposes a novel motion planning method for an autonomous ground mobile robot to address dynamic surroundings, nonlinear program, and robust optimization problems. A planner based on the recurrent fuzzy neural network (RFNN) is designed to program trajectory and motion of mobile robots to reach target. And, obstacle avoidance is achieved. In RFNN, inference capability of fuzzy logic and learning capability of neural network are combined to improve nonlinear programming performance. A recurrent frame with self-feedback loops in RFNN enhances stability and robustness of the structure. The extended Kalman filter (EKF) is designed to train weights of RFNN considering the kinematic constraint of autonomous mobile robots as well as target and obstacle constraints. EKF’s characteristics of fast convergence and little limit in training data make it suitable to train the weights in real time. Convergence of the training process is also analyzed in this paper. Optimization technique and update strategy are designed to improve the robust optimization of a system in dynamic surroundings. Simulation experiment and hardware experiment are implemented to prove the effectiveness of the proposed method. Hardware experiment is carried out on a tracked mobile robot. An omnidirectional vision is used to locate the robot in the surroundings. Forecast improvement of the proposed method is then discussed at the end.
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Wahde, M. "A method for behavioural organization for autonomous robots based on evolutionary optimization of utility functions." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 217, no. 4 (2003): 249–58. http://dx.doi.org/10.1177/095965180321700401.
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A method for behavioural organization for autonomous robots, based on evolutionary optimization of utility functions, is introduced and illustrated through several simulation examples. The method is shown to be efficient in generating behavioural organization systems that are both flexible and robust to noise. With this method, the amount of hand-tuning of parameters is minimized and, in principle, the user is only required to define fitness functions for the behaviours directly related to the task of the robot. The utility functions representing the beliefs and intentions of the robot are, in general, obtained through evolutionary optimization. However, if desired, the user also has the freedom to specify utility functions by hand.
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Costa, Daniele, Giacomo Palmieri, Matteo-Claudio Palpacelli, David Scaradozzi, and Massimo Callegari. "Design of a Carangiform Swimming Robot through a Multiphysics Simulation Environment." Biomimetics 5, no. 4 (2020): 46. http://dx.doi.org/10.3390/biomimetics5040046.
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Bio-inspired solutions devised for autonomous underwater robots are currently being investigated by researchers worldwide as a way to improve propulsion. Despite efforts to harness the substantial potential payoffs of marine animal locomotion, biological system performance still has far to go. In order to address this very ambitious objective, the authors of this study designed and manufactured a series of ostraciiform swimming robots over the past three years. However, the pursuit of the maximum propulsive efficiency by which to maximize robot autonomy while maintaining acceptable maneuverability ultimately drove us to improve our design and move from ostraciiform to carangiform locomotion. In order to comply with the tail motion required by the aforementioned swimmers, the authors designed a transmission system capable of converting the continuous rotation of a single motor in the travelling wave-shaped undulations of a multijoint serial mechanism. The propulsive performance of the resulting thruster (i.e., the caudal fin), which constitutes the mechanism end effector, was investigated by means of computational fluid dynamics techniques. Finally, in order to compute the resulting motion of the robot, numerical predictions were integrated into a multibody model that also accounted for the mass distribution inside the robotic swimmer and the hydrodynamic forces resulting from the relative motion between its body and the surrounding fluid. Dynamic analysis allowed the performance of the robotic propulsion to be computed while in the cruising condition.
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Cursi, Francesco, George P. Mylonas, and Petar Kormushev. "Adaptive Kinematic Modelling for Multiobjective Control of a Redundant Surgical Robotic Tool." Robotics 9, no. 3 (2020): 68. http://dx.doi.org/10.3390/robotics9030068.
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Accurate kinematic models are essential for effective control of surgical robots. For tendon driven robots, which are common for minimally invasive surgery, the high nonlinearities in the transmission make modelling complex. Machine learning techniques are a preferred approach to tackle this problem. However, surgical environments are rarely structured, due to organs being very soft and deformable, and unpredictable, for instance, because of fluids in the system, wear and break of the tendons that lead to changes of the system’s behaviour. Therefore, the model needs to quickly adapt. In this work, we propose a method to learn the kinematic model of a redundant surgical robot and control it to perform surgical tasks both autonomously and in teleoperation. The approach employs Feedforward Artificial Neural Networks (ANN) for building the kinematic model of the robot offline, and an online adaptive strategy in order to allow the system to conform to the changing environment. To prove the capabilities of the method, a comparison with a simple feedback controller for autonomous tracking is carried out. Simulation results show that the proposed method is capable of achieving very small tracking errors, even when unpredicted changes in the system occur, such as broken joints. The method proved effective also in guaranteeing accurate tracking in teleoperation.
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Habib, Maki K. "Real Time Mapping and Dynamic Navigation for Mobile Robots." International Journal of Advanced Robotic Systems 4, no. 3 (2007): 35. http://dx.doi.org/10.5772/5681.
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This paper discusses the importance, the complexity and the challenges of mapping mobile robot's unknown and dynamic environment, besides the role of sensors and the problems inherited in map building. These issues remain largely an open research problems in developing dynamic navigation systems for mobile robots. The paper presenst the state of the art in map building and localization for mobile robots navigating within unknown environment, and then introduces a solution for the complex problem of autonomous map building and maintenance method with focus on developing an incremental grid based mapping technique that is suitable for real-time obstacle detection and avoidance. In this case, the navigation of mobile robots can be treated as a problem of tracking geometric features that occur naturally in the environment of the robot. The robot maps its environment incrementally using the concept of occupancy grids and the fusion of multiple ultrasonic sensory information while wandering in it and stay away from all obstacles. To ensure real-time operation with limited resources, as well as to promote extensibility, the mapping and obstacle avoidance modules are deployed in parallel and distributed framework. Simulation based experiments has been conducted and illustrated to show the validity of the developed mapping and obstacle avoidance approach.