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Journal articles on the topic 'Robot Networks'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Kim, Jonghoek. "Workspace exploration and protection with multiple robots assisted by sensor networks." International Journal of Advanced Robotic Systems 15, no. 4 (2018): 172988141879217. http://dx.doi.org/10.1177/1729881418792170.

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This article introduces multi-robot strategies making multiple robots explore an unknown environment in a cooperative manner. Our exploration strategies do not require global localization of a robot or a node. Multiple robots build a Voronoi diagram as a topological map of the environment, while deploying sensor nodes which can sense and communicate. As the sensor network built by one robot meets the network built by another robot, both robots can exchange data with each other. The robots then use the merged sensor network to protect the environment. We introduce an intruder capture algorithm

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Kim, Jonghoek. "Constructing 3D Underwater Sensor Networks without Sensing Holes Utilizing Heterogeneous Underwater Robots." Applied Sciences 11, no. 9 (2021): 4293. http://dx.doi.org/10.3390/app11094293.

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This article handles building underwater sensor networks autonomously using multiple surface ships. For building underwater sensor networks in 3D workspace with many obstacles, this article considers surface ships dropping underwater robots into the underwater workspace. We assume that every robot is heterogeneous, such that each robot can have a distinct sensing range while moving with a distinct speed. The proposed strategy works by moving a single robot at a time to spread out the underwater networks until the 3D cluttered workspace is fully covered by sensors of the robots, such that no se

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Ravankar, Abhijeet, Ankit Ravankar, Yukinori Kobayashi, Yohei Hoshino, Chao-Chung Peng, and Michiko Watanabe. "Hitchhiking Based Symbiotic Multi-Robot Navigation in Sensor Networks." Robotics 7, no. 3 (2018): 37. http://dx.doi.org/10.3390/robotics7030037.

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Robot navigation is a complex process that involves real-time localization, obstacle avoidance, map update, control, and path planning. Thus, it is also a computationally expensive process, especially in multi-robot systems. This paper presents a cooperative multi-robot navigation scheme in which a robot can ‘hitchhike’ another robot, i.e., two robots going to the same (or close) destination navigate together in a leader–follower system assisted by visual servoing. Although such cooperative navigation has many benefits compared to traditional approaches with separate navigation, there are many

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Brecelj, Tilen, and Tadej Petrič. "Stable Heteroclinic Channel Networks for Physical Human–Humanoid Robot Collaboration." Sensors 23, no. 3 (2023): 1396. http://dx.doi.org/10.3390/s23031396.

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Human–robot collaboration is one of the most challenging fields in robotics, as robots must understand human intentions and suitably cooperate with them in the given circumstances. But although this is one of the most investigated research areas in robotics, it is still in its infancy. In this paper, human–robot collaboration is addressed by applying a phase state system, guided by stable heteroclinic channel networks, to a humanoid robot. The base mathematical model is first defined and illustrated on a simple three-state system. Further on, an eight-state system is applied to a humanoid robo

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Kim, Jonghoek. "Capturing intruders based on Voronoi diagrams assisted by information networks." International Journal of Advanced Robotic Systems 14, no. 1 (2017): 172988141668269. http://dx.doi.org/10.1177/1729881416682693.

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We consider a scenario of deploying multiple robots to capture all intruders in a cluttered workspace with many obstacles. Here, we say that a robot captures an intruder in the case where the intruder is within the maximum range of a weapon on the robot. All robots use the Voronoi diagram as the topological map of the workspace. Due to obstacles, intruders are confined to move along a passage between obstacles. Suppose the weapons on every robot are powerful enough to cover a passage in the workspace. Then, we can consider a simplified scenario such that robots and intruders are restricted to

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Chen, Dechao, Shuai Li, and Qing Wu. "A Review on Neural Dynamics for Robot Autonomy." International Journal of Robotics and Control 1, no. 1 (2018): 20. http://dx.doi.org/10.5430/ijrc.v1n1p20.

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Exploiting neural networks to solve control problems of robots is becoming commonly and effectively in academia and engineering. Due to the remarkable features like distributed storage, parallelism, easy implementation by hardware, adaptive self-learning capability, and free of off-line training, the solutions of neural networks break the bottlenecks of serial-processing strategies and methods, and serve as significant alternatives for robotic engineers and researchers. Especially, various types and branches of recurrent neural networks (RNNs) have been sequentially developed since the seminal

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Zhang, Jin Xue, and Hai Zhu Pan. "A Task of Miniature Mobile Robot Learning for Obstacle Avoidance through Neural Networks." Applied Mechanics and Materials 151 (January 2012): 498–502. http://dx.doi.org/10.4028/www.scientific.net/amm.151.498.

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This paper is concerned with Q-learning , a very popular algorithm for reinforcement learning ,for obstacle avoidance through neural networks. The principle tells that the focus always must be on both ecological nice tasks and behaviours when designing on robot. Many robot systems have used behavior-based systems since the 1980’s.In this paper, the Khepera robot is trained through the proposed algorithm of Q-learning using the neural networks for the task of obstacle avoidance. In experiments with real and simulated robots, the neural networks approach can be used to make it possible for Q-lea

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Yuschenko, A. S., and Yin Shuai. "Dialogue Control of Collaborative Robots Based on Artifi cial Neural Networks." Mekhatronika, Avtomatizatsiya, Upravlenie 22, no. 11 (2021): 567–76. http://dx.doi.org/10.17587/mau.22.567-576.

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Collaborative robotics progress is based on the possibility to apply robots to the wide range activity of peoples. Now the user can control the robot without any special knowledge in robotics and safe. The price of such possibilities is complication of control system of robot which now has to aquire an opportunity of autonomous behavior under human’s control, using the necessary sensors and elements of artificial intelligence. In our research we suppose the collaborative robot as mobile robotic device possible to fulfil some work under the human’s speech demands not only in the same space with

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Tezuka, Hirohisa, Norifumi Katafuchi, Yukihiro Nakamura, et al. "Robot Platform Architecture for Information Sharing and Collaboration Among Multiple Networked Robots." Journal of Robotics and Mechatronics 18, no. 3 (2006): 325–32. http://dx.doi.org/10.20965/jrm.2006.p0325.

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We present a framework for creating an open platform where a variety of robots collaborate via communication networks to provide us with our daily life support. We describe the architecture of the network robot platform, which consists of a connection unit to connect robots to the platform, an area management gateway to manage multiple robot resources, and a robot-user interaction database to share user, robot, and service information, to provide advanced services through multiple robot collaboration. We confirmed its functions using an announcement service as an example of application on the

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Phan Bui, Khoi, Giang Nguyen Truong, and Dat Nguyen Ngoc. "GCTD3: Modeling of Bipedal Locomotion by Combination of TD3 Algorithms and Graph Convolutional Network." Applied Sciences 12, no. 6 (2022): 2948. http://dx.doi.org/10.3390/app12062948.

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In recent years, there has been a lot of research using reinforcement learning algorithms to train 2-legged robots to move, but there are still many challenges. The authors propose the GCTD3 method, which takes the idea of using Graph Convolutional Networks to represent the kinematic link features of the robot, and combines this with the Twin-Delayed Deep Deterministic Policy Gradient algorithm to train the robot to move. Graph Convolutional Networks are very effective in graph-structured problems such as the connection of the joints of the human-like robots. The GCTD3 method shows better resu

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Rios, Jorge D., Daniel Ríos-Rivera, Jesus Hernandez-Barragan, Marco Pérez-Cisneros, and Alma Y. Alanis. "Formation Control of Mobile Robots Based on Pin Control of Complex Networks." Machines 10, no. 10 (2022): 898. http://dx.doi.org/10.3390/machines10100898.

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Robot formation control has several advantages that make it interesting for research. Multiple works have been published in the literature using different control approaches. This work presents the control of different groups of robots to achieve a desired formation based on pinning control of complex networks and coordinate translation. The implemented control law comprises complex network bounding, proportional, and collision avoidance terms. The tests for this proposal were performed via simulation and experimental tests, considering different networks of differential robots. The selected r

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Alam, Nafizul, Sk Hasan, Gazi Abdullah Mashud, and Subodh Bhujel. "Neural Network for Enhancing Robot-Assisted Rehabilitation: A Systematic Review." Actuators 14, no. 1 (2025): 16. https://doi.org/10.3390/act14010016.

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The integration of neural networks into robotic exoskeletons for physical rehabilitation has become popular due to their ability to interpret complex physiological signals. Surface electromyography (sEMG), electromyography (EMG), electroencephalography (EEG), and other physiological signals enable communication between the human body and robotic systems. Utilizing physiological signals for communicating with robots plays a crucial role in robot-assisted neurorehabilitation. This systematic review synthesizes 44 peer-reviewed studies, exploring how neural networks can improve exoskeleton robot-

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Aldana, Carlos I., Rodrigo Munguía, Emmanuel Cruz-Zavala, and Emmanuel Nuño. "Pose Consensus of Multiple Robots with Time-Delays Using Neural Networks." Robotica 37, no. 5 (2019): 883–905. http://dx.doi.org/10.1017/s0263574718001388.

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SummaryThis paper proposes a novel control scheme based on Radial Basis Artificial Neural Network to solve the leader–follower and leaderless pose (position and orientation) consensus problems in the Special Euclidean space of dimension three (SE(3)). The controller is designed for robot networks composed of heterogeneous (kinematically and dynamically different) and uncertain robots with variable time-delays in the interconnection. The paper derives a sufficient condition on the controller gains and the robot interconnection, and using Barbalat’s Lemma, both consensus problems are solved. The

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Lee, Geunho, Seokhoon Yoon, Nak Young Chong, and Henrik Christensen. "A Mobile Sensor Network Forming Concentric Circles Through Local Interaction and Consensus Building." Journal of Robotics and Mechatronics 21, no. 4 (2009): 469–77. http://dx.doi.org/10.20965/jrm.2009.p0469.

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We address the problem of a swarm of autonomous mobile robotic sensors generating geometric shapes to build wireless ad hoc surveillance sensor networks. Robot swarms with limited observation are required to form different shapes under different task conditions. To do this, we propose decentralized coordination enabling a robot swarm dispersed across an area to form a desired shape. Our approach has emphn robots generate a circumscribed circle of a regular emphn-polygon based on local interaction with neighboring robots. The approach also enables a large robot swarm to form concentric circles

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Oya, Makoto, and Taku Okuno. "A Middleware Framework for Loose Robot Communication over the Internet." Journal of Robotics and Mechatronics 17, no. 1 (2005): 11–16. http://dx.doi.org/10.20965/jrm.2005.p0011.

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Paralleling with the expansion of robot technology to social activities such as home use, community work, and entertainment, robot communication technology must expand from closed networks to the Internet. Unlike closed networks, robot communication over the Internet must be based on loose process coupling between robots. Web Services technology fits this requirement, but requires middleware supporting Web Services for robot communication to implement robot application software in this environment. Most existing middleware does not fully conform to this requirement because it mainly targets en

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Wan, Jiuqing, Shaocong Bu, Jinsong Yu, and Liping Zhong. "Distributed simultaneous localization and mapping for mobile robot networks via hybrid dynamic belief propagation." International Journal of Distributed Sensor Networks 13, no. 8 (2017): 155014771772671. http://dx.doi.org/10.1177/1550147717726715.

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This article proposes a hybrid dynamic belief propagation for simultaneous localization and mapping in the mobile robot network. The positions of landmarks and the poses of moving robots at each time slot are estimated simultaneously in an online and distributed manner, by fusing the odometry data of each robot and the measurements of robot–robot or robot–landmark relative distance and angle. The joint belief state of all robots and landmarks is encoded by a factor graph and the marginal posterior probability distribution of each variable is inferred by belief propagation. We show how to calcu

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Wada, Mitsuo. "Neural Networks and the Applications for Robot Control." Journal of Robotics and Mechatronics 2, no. 4 (1990): 219. http://dx.doi.org/10.20965/jrm.1990.p0219.

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It is well known that robots are being skillfully applied and with favorable performance in a variety of fields, for use in the Japanese manufacturing industry in particular, thanks to progress in robot technology. Today, robots are expected to accommodate men and in the near future be utilized in the field of home life in compliance with human beings. Pessimistically speaking, however, it is impossible to deny that conventional robots, such as teaching playback robots (which men must operate directly), are not able to play roles in the future as expected, so that the development of a new cont

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Krejsa, Jiri, Stanislav Vĕchet, and Tomas Ripel. "Neural Network Based Reactive Navigation for Mobile Robot in Dynamic Environment." Solid State Phenomena 198 (March 2013): 108–13. http://dx.doi.org/10.4028/www.scientific.net/ssp.198.108.

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When mobile robots are used among people, the best accepted motion related behavior is a human-like motion of the robot. Such behavior is difficult to obtain with commonly used finite state machine based planners, but can easily be evoked when human controls the robot. The paper presents the way of transforming such knowledge from human controller to reactive planner in the robot navigation module. Reactive planner is based on machine learning, neural networks in particular. The planner consists of two separate neural networks, one serving as predictor of dynamic obstacles behavior, second one

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Patti, Gaetano, Luca Leonardi, and Lucia Lo Bello. "A Novel MAC Protocol for Low Datarate Cooperative Mobile Robot Teams." Electronics 9, no. 2 (2020): 235. http://dx.doi.org/10.3390/electronics9020235.

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Cooperative mobile robot applications enable robots to perform tasks that are more complex than those that each single robot can perform alone. In this application context, communication networks play a very important role, as they have to cope with strict requirements (e.g., in terms of mobility, reliability, and bounded latencies). Recent cooperative robot applications foresee the support of low datarate communication technologies, that provide, among other benefits, lower energy consumption and easy integration with Wireless Sensor Networks (WSNs). Unfortunately, the state-of-the-art soluti

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Yegana Aliyeva, Yegana Aliyeva, and Agil Mammadli Agil Mammadli. "DEVELOPMENT OF IMAGE PROCESSING ALGORITHM UTILIZING NEURAL NETWORKS AND FUZZY LOGIC." ETM - Equipment, Technologies, Materials 16, no. 04 (2023): 59–66. http://dx.doi.org/10.36962/etm16042023-59.

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Despite their limitations, robots should have the ability to gather information from their surroundings such as location, color, light, and images. This data must then be analyzed automatically, and based on that analysis, the robot should be able to determine an appropriate reaction to its environment. Once a decision has been made, the robot must be able to execute it through the use of actuators and motion systems. Robots are comprised of sensors that collect real-time environmental data, an electronic brain that processes and decides, and movement controls that carry out those decisions. I

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Wang, Ru, and Jun Jia. "Design of small humanoid fighting robot based on target recognition algorithm." International Journal of Advanced Robotic Systems 17, no. 2 (2020): 172988142091066. http://dx.doi.org/10.1177/1729881420910661.

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In the past, robots can only do simple walking, but now robots can perform complex actions such as running, attacking and automatically standing up after falling to the ground. The humanoid robot competition is very interesting and has great significance for the study. The speed and accuracy of robots in domestic competitions still need to be improved. In this article, a design scheme of a small humanoid fighting robot based on the target recognition algorithm is proposed. In this article, a design scheme of a small humanoid fighting robot based on the target recognition algorithm is proposed,

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Hwang, Jungsik, and Kun Chang Lee. "Exploring the effect of a user’s personality traits on tactile communication with a robot using Bayesian networks." Interaction Studies 16, no. 1 (2015): 29–53. http://dx.doi.org/10.1075/is.16.1.02hwa.

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Because robots are physically embodied agents, touch is one of the important modalities through which robots communicate with humans. Among the several factors that affect human-robot interaction, this research focuses on the effect of a user’s personality traits on tactile interactions with a robot. Participants interacted freely with a robot and their tactile interaction patterns were analyzed. Several classifiers were used to examine the effect of a participant’s degree of extroversion on tactile communication patterns with the robot and our results showed that a user’s personality traits a

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G.V Chalapathi Rao, Kandhyanam Mahesh, and Maheshwaram Shiva. "Gradient Based Routing Protocol For Modular Robotics." international journal of engineering technology and management sciences 7, no. 3 (2023): 235–40. http://dx.doi.org/10.46647/ijetms.2023.v07i03.030.

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Advancements in microprocessor-based systems have revolutionized robotics, enabling single-robot and multi-robot systems (MRS) to excel in various applications such as search and rescue, forest fire detection, mining, and disaster management. MRS systems amplify robot capabilities, enabling complex tasks and distributed operations. Effective communication between robots is crucial for optimal performance. This paper explores MRS architectures, emphasizing networking issues and required services for enhanced efficiency. It compares MRS systems to mobile ad hoc networks (MANETs), analyzes robot-

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Kawabata, Kuniaki, Takeshi Sekine, Tatsuya Ishikawa, Hajime Asama, and Isao Endo. "Direct Mobile Robot Teleoperation via Internet." Journal of Robotics and Mechatronics 11, no. 1 (1999): 54–59. http://dx.doi.org/10.20965/jrm.1999.p0054.

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As networks such as the Internet go global, they become an important tool for everyone from engineers to the general public. This makes network-related technology an up-and-coming field. Conventional techniques should be applied for teleservice and teleoperation in global and general-purpose networks. Robots are a promising example of physical agent potentially useful via such networks in the near future. We describe direct teleoperation of a mobile robot via the Internet and experiments involving a real system and network.

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Kružić, Stanko, Josip Musić, Roman Kamnik, and Vladan Papić. "End-Effector Force and Joint Torque Estimation of a 7-DoF Robotic Manipulator Using Deep Learning." Electronics 10, no. 23 (2021): 2963. http://dx.doi.org/10.3390/electronics10232963.

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When a mobile robotic manipulator interacts with other robots, people, or the environment in general, the end-effector forces need to be measured to assess if a task has been completed successfully. Traditionally used force or torque estimation methods are usually based on observers, which require knowledge of the robot dynamics. Contrary to this, our approach involves two methods based on deep neural networks: robot end-effector force estimation and joint torque estimation. These methods require no knowledge of robot dynamics and are computationally effective but require a force sensor under

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Gul, Omer Melih. "Energy Harvesting and Task-Aware Multi-Robot Task Allocation in Robotic Wireless Sensor Networks." Sensors 23, no. 6 (2023): 3284. http://dx.doi.org/10.3390/s23063284.

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In this work, we investigate an energy-aware multi-robot task-allocation (MRTA) problem in a cluster of the robot network that consists of a base station and several clusters of energy-harvesting (EH) robots. It is assumed that there are M+1 robots in the cluster and M tasks exist in each round. In the cluster, a robot is elected as the cluster head, which assigns one task to each robot in that round. Its responsibility (or task) is to collect the resultant data from the remaining M robots to aggregate and transmit directly to the BS. This paper aims to allocate the M tasks to the remaining M

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R, Smt Thilagavathy, Dr Sumithra Devi K. A, and Saagar, M. P. "Energy Efficient Routing Protocols for Mobile Robots: A Review." Saudi Journal of Engineering and Technology 8, no. 07 (2023): 163–70. http://dx.doi.org/10.36348/sjet.2023.v08i07.002.

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Many vital applications benefit from mobile multi-robot teams, including search and rescue, environmental monitoring, military, unmanned space exploration, hazard detection and analysis. Communication between robots is important for group coordination and information sharing in mobile multi-robot teams. Because many mobile robot applications involve scenarios where communication infrastructure is destroyed or unavailable, mobile robot teams must regularly connect with one another through ADHOC networking. In such situations, low over-head and energy efficient routing systems for sending inform

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Allali, Sarah, and Mahfoud Benchaïba. "Overview of Search and Rescue from Robotics to Wireless Sensors and Robots Networks." International Journal of Robotics Applications and Technologies 4, no. 2 (2016): 16–33. http://dx.doi.org/10.4018/ijrat.2016070102.

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In the recent years, many researchers have shown interest in developing search and rescue system composed of one or multiple robots, which have the mission of finding victims and identifying the potential hazards. To enhance the robotic systems there is a growing trend of integrating wireless sensor networks (WSNs) to robots and multi-robot systems, which gives more awareness of the environments. In the first part of this article, the authors present a review of robotic system and their environments in search and rescue systems. Additionally, they explain challenges related to these systems an

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Braccini, Michele, Andrea Roli, Edoardo Barbieri, and Stuart A. Kauffman. "On the Criticality of Adaptive Boolean Network Robots." Entropy 24, no. 10 (2022): 1368. http://dx.doi.org/10.3390/e24101368.

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Systems poised at a dynamical critical regime, between order and disorder, have been shown capable of exhibiting complex dynamics that balance robustness to external perturbations and rich repertoires of responses to inputs. This property has been exploited in artificial network classifiers, and preliminary results have also been attained in the context of robots controlled by Boolean networks. In this work, we investigate the role of dynamical criticality in robots undergoing online adaptation, i.e., robots that adapt some of their internal parameters to improve a performance metric over time

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Mohammed, Mohammed, Mahmood Abdulrazzaq .., Ruqayah R. Al .., and Salah A. Aliesawi. "Intelligent Enhanced Mobile Robotics Navigation: Integrating Neural Networks with Type-2 Fuzzy Logic for Dynamic Environments." Fusion: Practice and Applications 15, no. 2 (2024): 89–101. http://dx.doi.org/10.54216/fpa.150208.

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Intelligent mobile robots move on uncertain grounds, thus requiring good navigation strategies for things like path tracking and obstacle avoidance. This research uses an Omni-drive mobile robot to autonomously approach given objectives in different situations encountered in static and dynamic environments. The paper compares two distinct controllers – fuzzy logic controller and neural network controller- that lead the mobile robot towards its destination without hitting obstacles. These are responsible for adjusting the linear and angular velocities of a mobile robot which makes adaptive navi

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Jones, Alexander, Vaibhav Gandhi, Adam Y. Mahiddine, and Christian Huyck. "Bridging Neuroscience and Robotics: Spiking Neural Networks in Action." Sensors 23, no. 21 (2023): 8880. http://dx.doi.org/10.3390/s23218880.

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Robots are becoming increasingly sophisticated in the execution of complex tasks. However, an area that requires development is the ability to act in dynamically changing environments. To advance this, developments have turned towards understanding the human brain and applying this to improve robotics. The present study used electroencephalogram (EEG) data recorded from 54 human participants whilst they performed a two-choice task. A build-up of motor activity starting around 400 ms before response onset, also known as the lateralized readiness potential (LRP), was observed. This indicates tha

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Patiño, Kleber, Emanuel Slawiñski, Marco Moran-Armenta, Vicente Mut, Francisco G. Rossomando, and Javier Moreno-Valenzuela. "Neural Networks in the Delayed Teleoperation of a Skid-Steering Robot." Mathematics 13, no. 13 (2025): 2071. https://doi.org/10.3390/math13132071.

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Bilateral teleoperation of skid-steering mobile robots with time-varying delays presents significant challenges in ensuring accurate leader–follower coupling. This article presents a novel controller for a bilateral teleoperation system composed of a robot manipulator and a skid-steering mobile robot. The proposed controller leverages neural networks to compensate for ground–robot interactions, uncertain dynamics, and communication delays. The control strategy integrates a shared scheme between damping injection and two neural networks, enhancing the robustness and adaptability of the delayed

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Tai, Lei, Shaohua Li, and Ming Liu. "Autonomous exploration of mobile robots through deep neural networks." International Journal of Advanced Robotic Systems 14, no. 4 (2017): 172988141770357. http://dx.doi.org/10.1177/1729881417703571.

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The exploration problem of mobile robots aims to allow mobile robots to explore an unknown environment. We describe an indoor exploration algorithm for mobile robots using a hierarchical structure that fuses several convolutional neural network layers with decision-making process. The whole system is trained end to end by taking only visual information (RGB-D information) as input and generates a sequence of main moving direction as output so that the robot achieves autonomous exploration ability. The robot is a TurtleBot with a Kinect mounted on it. The model is trained and tested in a real w

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Martinez, Fernando, Fredy Martinez, and Cesar Hernandez. "Acoustic event characterization for service robot using convolutional networks." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (2022): 6684. http://dx.doi.org/10.11591/ijece.v12i6.pp6684-6696.

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<p>This paper presents and discusses the creation of a sound event classification model using deep learning. In the design of service robots, it is necessary to include routines that improve the response of both the robot and the human being throughout the interaction. These types of tasks are critical when the robot is taking care of children, the elderly, or people in vulnerable situations. Certain dangerous situations are difficult to identify and assess by an autonomous system, and yet, the life of the users may depend on these robots. Acoustic signals correspond to events that can b

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Fernando, Martınez, Martınez Fredy, and Hernandez Cesar. "Acoustic event characterization for service robot using convolutional networks." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (2022): 6684–96. https://doi.org/10.11591/ijece.v12i6.pp6684-6696.

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This paper presents and discusses the creation of a sound event classification model using deep learning. In the design of service robots, it is necessary to include routines that improve the response of both the robot and the human being throughout the interaction. These types of tasks are critical when the robot is taking care of children, the elderly, or people in vulnerable situations. Certain dangerous situations are difficult to identify and assess by an autonomous system, and yet, the life of the users may depend on these robots. Acoustic signals correspond to events that can be detecte

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Diryag, Ali, Marko Mitić, and Zoran Miljković. "Neural networks for prediction of robot failures." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 228, no. 8 (2013): 1444–58. http://dx.doi.org/10.1177/0954406213507704.

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It is known that the supervision and learning of robotic executions is not a trivial problem. Nowadays, robots must be able to tolerate and predict internal failures in order to successfully continue performing their tasks. This study presents a novel approach for prediction of robot execution failures based on neural networks. Real data consisting of robot forces and torques recorded immediately after the system failure are used for the neural network training. The multilayer feedforward neural networks are employed in order to find optimal solution for the failure prediction problem. In tota

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Gul, Omer Melih, and Aydan Muserref Erkmen. "Energy-Efficient Cluster-Based Data Collection by a UAV with a Limited-Capacity Battery in Robotic Wireless Sensor Networks." Sensors 20, no. 20 (2020): 5865. http://dx.doi.org/10.3390/s20205865.

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In this work, our motivation focuses on an energy-efficient data collection problem by a mobile sink, an unmanned aerial vehicle (UAV) with limited battery capacity, in a robot network divided into several robot clusters. In each cluster, a cluster head (CH) robot allocates tasks to the remaining robots and collects data from them. Our contribution is to minimize the UAV total energy consumption coupled to minimum cost data collection from CH robots by visiting optimally a portion of the CH robots. The UAV decides the subset of CH robots to visit by considering not only the locations of all CH

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Oya, Makoto, Keitaro Naruse, Masahiko Narita, Taku Okuno, Masahiro Kinoshita, and Yukinori Kakazu. "Loose Robot Communication over the Internet." Journal of Robotics and Mechatronics 16, no. 6 (2004): 626–34. http://dx.doi.org/10.20965/jrm.2004.p0626.

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As robot technology is disseminated from special fields such as factory production to everyday fields such as home use, community work, and entertainment, working space of robots also expands from dedicated area such as factory sites to ordinary living space. Combining this technology shift and the popularized public Internet suggests the emergence of new robot applications. The Internet, however, as its nature, is not suitable for tight coupling of processes among robots and computers. An approach different from simple expansion of current robot communication technology is thus necessary. Aft

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Gaiduk, A. R., O. V. Martjanov, M. Yu Medvedev, V. Kh Pshikhopov, N. Hamdan, and A. Farhood. "Neural Network Based Control System for Robots Group Operating in 2-d Uncertain Environment." Mekhatronika, Avtomatizatsiya, Upravlenie 21, no. 8 (2020): 470–79. http://dx.doi.org/10.17587/mau.21.470-479.

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This study is devoted to development of a neural network based control system of robots group. The control system performs estimation of an environment state, searching the optimal path planning method, path planning, and changing the trajectories on via the robots interaction. The deep learning neural networks implements the optimal path planning method, and path planning of the robots. The first neural network classifies the environment into two types. For the first type a method of the shortest path planning is used. For the second type a method of the most safety path planning is used. Est

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Čaić, Martina, Gaby Odekerken-Schröder, and Dominik Mahr. "Service robots: value co-creation and co-destruction in elderly care networks." Journal of Service Management 29, no. 2 (2018): 178–205. http://dx.doi.org/10.1108/josm-07-2017-0179.

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Purpose The purpose of this paper is to investigate the potential roles for service robots (i.e. socially assistive robots) in value networks of elderly care. Taking an elderly person’s perspective, it defines robot roles according to their value co-creating/destroying potential for the elderly user (i.e. focal actor), while acknowledging consequences for a network of users around the elderly (i.e. network actors). Design/methodology/approach This qualitative, interpretative study employs in-depth phenomenographic interviews, supported by generative cards activities (i.e. Contextual Value Netw

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Hu, Jie, Qin Li, and Qiang Bai. "Research on Robot Grasping Based on Deep Learning for Real-Life Scenarios." Micromachines 14, no. 7 (2023): 1392. http://dx.doi.org/10.3390/mi14071392.

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The application of robots, especially robotic arms, has been primarily focused on the industrial sector due to their relatively low level of intelligence. However, the rapid development of deep learning has provided a powerful tool for conducting research on highly intelligent robots, thereby offering tremendous potential for the application of robotic arms in daily life scenarios. This paper investigates multi-object grasping in real-life scenarios. We first analyzed and improved the structural advantages and disadvantages of convolutional neural networks and residual networks from a theoreti

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PETRIČ, TADEJ, LUKA PETERNEL, ANDREJ GAMS, BOJAN NEMEC, and LEON ŽLAJPAH. "NAVIGATION METHODS FOR THE SKIING ROBOT." International Journal of Humanoid Robotics 10, no. 04 (2013): 1350029. http://dx.doi.org/10.1142/s0219843613500291.

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In this paper, we propose and evaluate methods for the local navigation using only visual perception for the skiing robot. Our skiing robot, capable of skiing using the carving technique, has no direct control on the velocity of skiing as it cannot break or accelerate, therefore well known navigation methods for nonholonomic mobile robots cannot be directly applied. We consider the following methods: an intuitive method of aiming at the closest gates, a human obstacle avoidance movement model, neural networks learning from a set of human demonstrations, and a global method that uses a predefin

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Yuan, Yezhi, Fan Pei, Yuting Huang, Zhang Jie, Liangyu Li, and Qin Yi. "Research on Medical Robots Based on Convolutional Neural Network: Drug Transportation System and E-commerce for Neurodigestive Diseases." Highlights in Science, Engineering and Technology 87 (March 26, 2024): 239–45. http://dx.doi.org/10.54097/53y3t458.

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The research team designed medical robots for patients with neurodigestive diseases, mainly using convolutional neural networks to achieve robot positioning. We designed the primary model of the drone and used a spatial Cartesian coordinate system as a reference system to conduct positioning research. Finally, by analyzing the current situation of multiple disease relapses and conducting drug related questionnaire surveys, we verified the necessity of drug delivery robots, Convolutional neural networks have been implemented to achieve spatial positioning of robots.

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Tao, Yong, Haitao Liu, Shuo Chen, Jiangbo Lan, Qi Qi, and Wenlei Xiao. "An Off-Line Error Compensation Method for Absolute Positioning Accuracy of Industrial Robots Based on Differential Evolution and Deep Belief Networks." Electronics 12, no. 17 (2023): 3718. http://dx.doi.org/10.3390/electronics12173718.

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Industrial robots have been increasingly used in the field of intelligent manufacturing. The low absolute positioning accuracy of industrial robots is one of the difficulties in their application. In this paper, an accuracy compensation algorithm for the absolute positioning of industrial robots is proposed based on deep belief networks using an off-line compensation method. A differential evolution algorithm is presented to optimize the networks. Combined with the evidence theory, a position error mapping model is proposed to realize the absolute positioning accuracy compensation of industria

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Schenck, Connor, and Dieter Fox. "Perceiving and reasoning about liquids using fully convolutional networks." International Journal of Robotics Research 37, no. 4-5 (2017): 452–71. http://dx.doi.org/10.1177/0278364917734052.

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Liquids are an important part of many common manipulation tasks in human environments. If we wish to have robots that can accomplish these types of tasks, they must be able to interact with liquids in an intelligent manner. In this paper, we investigate ways for robots to perceive and reason about liquids. That is, a robot asks the questions What in the visual data stream is liquid? and How can I use that to infer all the potential places where liquid might be? We collected two data sets to evaluate these questions, one using a realistic liquid simulator and another using our robot. We used fu

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Boanta, Cătălin, and Cornel Brișan. "Estimation of the Kinematics and Workspace of a Robot Using Artificial Neural Networks." Sensors 22, no. 21 (2022): 8356. http://dx.doi.org/10.3390/s22218356.

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At present, in specific and complex industrial operations, robots have to respect certain requirements and criteria as high kinematic or dynamic performance, specific dimensions of the workspace, or limitation of the dimensions of the mobile elements of the robot. In order to respect these criteria, a proper design of the robots has to be achieved, which requires years of practice and a proper knowledge and experience of a human designer. In order to assist the human designer in the process of designing the robots, several methods (including optimization methods) have been developed. The scien

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Popescu, Aura-Loredana, Nirvana Popescu, Ciprian Dobre, Elena-Simona Apostol, and Decebal Popescu. "IoT and AI-Based Application for Automatic Interpretation of the Affective State of Children Diagnosed with Autism." Sensors 22, no. 7 (2022): 2528. http://dx.doi.org/10.3390/s22072528.

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In the context in which it was demonstrated that humanoid robots are efficient in helping children diagnosed with autism in exploring their affective state, this paper underlines and proves the efficiency of a previously developed machine learning-based mobile application called PandaSays, which was improved and integrated with an Alpha 1 Pro robot, and discusses performance evaluations using deep convolutional neural networks and residual neural networks. The model trained with MobileNet convolutional neural network had an accuracy of 56.25%, performing better than ResNet50 and VGG16. A strat

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Sharma, Rajeev, and Narayan Srinivasa. "A framework for active vision-based robot control using neural networks." Robotica 16, no. 3 (1998): 309–27. http://dx.doi.org/10.1017/s0263574798000381.

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Assembly robots that use an active camera system for visual feedback can achieve greater flexibility, including the ability to operate in an uncertain and changing environment. Incorporating active vision into a robot control loop involves some inherent difficulties, including calibration, and the need for redefining the servoing goal as the camera configuration changes. In this paper, we propose a novel self-organizing neural network that learns a calibration-free spatial representation of 3D point targets in a manner that is invariant to changing camera configurations. This representation is

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Sun, Bo, Jingwei Li, and Guanci Yang. "Multi-robot Cooperation Strategy Based on Wireless Sensor Network." International Journal of Online Engineering (iJOE) 14, no. 11 (2018): 77. http://dx.doi.org/10.3991/ijoe.v14i11.9514.

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<p class="0abstract"><span lang="EN-US">To realize the design of multi-robot cooperative control based on wireless sensor networks, a large number of local control research experiments are carried out on a specific model of mobile robots. Combined with the kinematic model of mobile robot, the motion characteristics of this kind of mobile robot are grasped. On the basis of realizing the multi-target tracking and positioning of wireless sensor network, a multi mobile robot cooperative control system based on the feedback of wireless sensor network is developed, and the synchronous mo

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Pradhan, Buddhadeb, Nirmal Baran Hui, Diptendu Sinha Roy, Gautam Srivastava, and Jerry Chun-Wei Lin. "Game-Theoretic Strategic Coordination and Navigation of Multiple Wheeled Robots." ACM Transactions on Internet Technology 21, no. 4 (2021): 1–15. http://dx.doi.org/10.1145/3450521.

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Multiple robots negotiating in a dynamic workspace may lead to collisions. To avoid such issues, multi-robot navigation and coordination becomes necessary but is computationally very challenging, particularly when there are many robots. This article addresses the problem of multi-robot navigation where individual robots require coordination. Although a few such attempts for modeling multi-robot coordination and navigation have been studied, this work proposes a game-theoretic coordination strategy, also referred to as strategic coordination. We make use of a genetic algorithm tuned fuzzy logic

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