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Journal articles on the topic 'Collaborative mobile robot'

Author: Grafiati

Published: 28 June 2021

Last updated: 29 July 2025

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1

Go, Eutteum, Jun Hyoung Lee, So Yeong Kim, Jong Sup Lee, Hyung Hwan Kim, and Joong Yeon Lim. "Stakeholder Perspectives on Safety Issues in Collaborative Mobile Robots: A Case Study of Quadruped Robot Applications in a Smart Factory." Applied Sciences 14, no. 22 (2024): 10232. http://dx.doi.org/10.3390/app142210232.

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With the development of Industry 4.0, collaborative mobile robots are becoming increasingly prevalent in industrial settings, raising important safety considerations in human–robot interaction environments. This study examines the safety issues in collaborative mobile robotics through a case study of a smart factory utilizing quadruped robots. This research aims to contribute to the development of safety management strategies by identifying potential risk factors and analyzing the differences in risk perception among stakeholders. A survey was conducted among 93 operators in the factory to ide

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Achour, Abdessalem, Hiba Al-Assaad, Yohan Dupuis, and Madeleine El Zaher. "Collaborative Mobile Robotics for Semantic Mapping: A Survey." Applied Sciences 12, no. 20 (2022): 10316. http://dx.doi.org/10.3390/app122010316.

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Ensuring safety in human–robot collaboration is one of the main challenges in mobile robotics today. Semantic maps are a potential solution because they provide semantic knowledge in addition to the geometric representation of the environment. They allow robots to perform their basic tasks using geometric representation, mainly localization, path planning and navigation, and additionally allow them to maintain a cognitive interpretation of the environment in order to reason and make decisions based on the context. The goal of this paper is to briefly review semantic mapping for a single mobile

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Engelbrecht, Duanne, Nico Steyn, and Karim Djouani. "Adaptive Virtual Impedance Control of a Mobile Multi-Robot System." Robotics 10, no. 1 (2021): 19. http://dx.doi.org/10.3390/robotics10010019.

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The capabilities of collaborative robotics have transcended the conventional abilities of decentralised robots as it provides benefits such as scalability, flexibility and robustness. Collaborative robots can operate safely in complex human environments without being restricted by the safety cages or barriers that often accompany them. Collaborative robots can be used for various applications such as machine tending, packaging, process tasks and pick and place. This paper proposes an improvement of the current virtual impedance algorithm by developing an adaptive virtual impedance controlled m

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Bonci, Andrea, Pangcheng David Cen Cheng, Marina Indri, Giacomo Nabissi, and Fiorella Sibona. "Human-Robot Perception in Industrial Environments: A Survey." Sensors 21, no. 5 (2021): 1571. http://dx.doi.org/10.3390/s21051571.

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Perception capability assumes significant importance for human–robot interaction. The forthcoming industrial environments will require a high level of automation to be flexible and adaptive enough to comply with the increasingly faster and low-cost market demands. Autonomous and collaborative robots able to adapt to varying and dynamic conditions of the environment, including the presence of human beings, will have an ever-greater role in this context. However, if the robot is not aware of the human position and intention, a shared workspace between robots and humans may decrease productivity

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Chen, Yue, and Yisong Li. "Storage Location Assignment for Improving Human–Robot Collaborative Order-Picking Efficiency in Robotic Mobile Fulfillment Systems." Sustainability 16, no. 5 (2024): 1742. http://dx.doi.org/10.3390/su16051742.

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The robotic mobile fulfillment (RMF) system is a parts-to-picker warehousing system and a sustainable technology used in human–robot collaborative order picking. Storage location assignment (SLA) tactically benefits order-picking efficiency. Most studies focus on the retrieval efficiency of robots to solve SLA problems. To further consider the crucial role played by human pickers in RMF systems, especially in the context that the sustainable performance of human workers should be paid attention to in human–robot collaboration, we solve the SLA problem by aiming to improve human–robot collabora

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Lin, Huei-Yung, and Yi-Chun Huang. "Collaborative Complete Coverage and Path Planning for Multi-Robot Exploration." Sensors 21, no. 11 (2021): 3709. http://dx.doi.org/10.3390/s21113709.

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In mobile robotics research, the exploration of unknown environments has always been an important topic due to its practical uses in consumer and military applications. One specific interest of recent investigation is the field of complete coverage and path planning (CCPP) techniques for mobile robot navigation. In this paper, we present a collaborative CCPP algorithms for single robot and multi-robot systems. The incremental coverage from the robot movement is maximized by evaluating a new cost function. A goal selection function is then designed to facilitate the collaborative exploration fo

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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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Lv, Taizhi, Juan Zhang, and Yong Chen. "A SLAM Algorithm Based on Edge-Cloud Collaborative Computing." Journal of Sensors 2022 (November 12, 2022): 1–17. http://dx.doi.org/10.1155/2022/7213044.

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Simultaneous localization and mapping (SLAM) is a typical computing-intensive task. Based on its own computing power, a mobile robot has difficult meeting the real-time performance and accuracy requirements for the SLAM process at the same time. Benefiting from the rapid growth of the network data transmission rate, cloud computing technology begins to be applied in the robotics. There is the reliability problem caused by solely relying on cloud computing. To compensate for the insufficient airborne capacity, ensure the real-time performance and reliability, and improve the accuracy, a SLAM al

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Chen, Wenzhou, Shizheng Zhou, Zaisheng Pan, Huixian Zheng, and Yong Liu. "Mapless Collaborative Navigation for a Multi-Robot System Based on the Deep Reinforcement Learning." Applied Sciences 9, no. 20 (2019): 4198. http://dx.doi.org/10.3390/app9204198.

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Compared with the single robot system, a multi-robot system has higher efficiency and fault tolerance. The multi-robot system has great potential in some application scenarios, such as the robot search, rescue and escort tasks, and so on. Deep reinforcement learning provides a potential framework for multi-robot formation and collaborative navigation. This paper mainly studies the collaborative formation and navigation of multi-robots by using the deep reinforcement learning algorithm. The proposed method improves the classical Deep Deterministic Policy Gradient (DDPG) to address the single ro

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Abderrahmane, Tamali, Tamali Mohammed, and Amardjia Nourredine. "An adaptive genetic algorithm for the optimization of multi-mobile robot collaboration." STUDIES IN ENGINEERING AND EXACT SCIENCES 5, no. 2 (2024): e6270. http://dx.doi.org/10.54021/seesv5n2-064.

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The proposed approach utilizes the Robot Operating System (ROS) to simulate multi-robot collaboration across various scenarios, ensuring rigorous testing and validation of the algorithm. Our simulation environment encompasses complex tasks such as 3D digitalization, which demand precise coordination and efficient resource management among robots. The adaptive genetic algorithm (GA) continuously adjusts its parameters to improve performance, making it highly suitable for dynamic and unpredictable environments. Our results demonstrate that the adaptive GA significantly enhances the efficiency an

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Jian, Hanwen. "Path Planning Algorithm for Mobile Robots." Transactions on Computer Science and Intelligent Systems Research 5 (August 12, 2024): 1043–54. http://dx.doi.org/10.62051/ajnbr762.

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Path planning algorithm is a critical technology enabling mobile robots to realize autonomous navigation. In this paper, the path-planning technology of mobile robots is deeply discussed, and the operation mechanism and principle of different algorithms are analyzed in detail. Based on the understanding of the characteristics of mobile robot path planning algorithms, these algorithms are divided into three categories: traditional planning algorithm, intelligent planning algorithm, and sampling-based planning algorithm. This paper reviews and discusses the key research results in recent years,

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Rokhim, Ismail, Nur Jamiludin Ramadhan, and Zainun Najakh. "CURe-Mi mobile manipulator robot for contact-less COVID-19 patients serving missions." IAES International Journal of Robotics and Automation (IJRA) 12, no. 3 (2023): 262. http://dx.doi.org/10.11591/ijra.v12i3.pp262-273.

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Since March 2020, coronavirus disease (COVID-19) has become a major global concern. Even in an emergency, medical personnel should avoid contact with COVID-19 patients. Mobile manipulators are a non-contact alternative to medical personnel for performing healthcare tasks such as distributing supplies to COVID-19-quarantined patients. In this study, patients use an Android application to order mobile manipulator robots, which include the Collaborative Manipulator Robot UR5e and the autonomous mobile robot MiR200 (abbreviated and referred to as CURe-Mi). The HTTP protocol is used for communicati

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Ismail, Rokhim, Jamiludin Ramadhan Nur, and Najakh Zainun. "CURe-Mi mobile manipulator robot for contact-less COVID-19 patients serving missions." IAES International Journal of Robotics and Automation (IJRA) 12, no. 3 (2023): 262–73. https://doi.org/10.11591/ijra.v12i3.pp262-273.

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Since March 2020, coronavirus disease (COVID-19) has become a major global concern. Even in an emergency, medical personnel should avoid contact with COVID-19 patients. Mobile manipulators are a non-contact alternative to medical personnel for performing healthcare tasks such as distributing supplies to COVID-19-quarantined patients. In this study, patients use an Android application to order mobile manipulator robots, which include the Collaborative Manipulator Robot UR5e and the autonomous mobile robot MiR200 (abbreviated and referred to as CURe-Mi). The HTTP protocol is used for communicati

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Muratore, Luca, Arturo Laurenzi, Alessio De Luca, et al. "A Unified Multimodal Interface for the RELAX High-Payload Collaborative Robot." Sensors 23, no. 18 (2023): 7735. http://dx.doi.org/10.3390/s23187735.

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This manuscript introduces a mobile cobot equipped with a custom-designed high payload arm called RELAX combined with a novel unified multimodal interface that facilitates Human–Robot Collaboration (HRC) tasks requiring high-level interaction forces on a real-world scale. The proposed multimodal framework is capable of combining physical interaction, Ultra Wide-Band (UWB) radio sensing, a Graphical User Interface (GUI), verbal control, and gesture interfaces, combining the benefits of all these different modalities and allowing humans to accurately and efficiently command the RELAX mobile cobo

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Mathew, Robins, Robert McGee, Kevin Roche, Shada Warreth, and Nikolaos Papakostas. "Introducing Mobile Collaborative Robots into Bioprocessing Environments: Personalised Drug Manufacturing and Environmental Monitoring." Applied Sciences 12, no. 21 (2022): 10895. http://dx.doi.org/10.3390/app122110895.

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Personalised therapeutic drugs are the future of the medical drug sector. For manufacturers, this will require the flexibility to produce many different unique batches within a given facility. This research paper aims to demonstrate the potential of mobile collaborative robots for improving current manufacturing practices in personalised therapeutics. The benefits and challenges of introducing robots in biologics are explored, including current practices, limitations, likely future practices, and the market outlook. Experiments demonstrating the application of a mobile collaborative robot to p

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Hichri, Bassem, Jean Christophe Fauroux, Lounis Adouane, Youcef Mezouar, and Ioan Doroftei. "Design of Collaborative, Cross & Carry Mobile RoBots "C³Bots"." Advanced Materials Research 837 (November 2013): 588–93. http://dx.doi.org/10.4028/www.scientific.net/amr.837.588.

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This paper presents an introduction aboutC3Botsproject which aims to design collaborative, cross and carry mobile robots. In this project it is considered to design an innovative robotic system based on modular entities with a simple mechanical architecture able to collaborate to ensure object co-manipulation and transport. The resulting multi-robot system is calledC3Bots. In this paper we present the first version of this system using a parallelogram mechanism for co-manipulation and the realized prototypes which are going to be used for first experiments.

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Maroşan, Iosif-Adrian, and George Constantin. "Wireless communication based on Raspberry pi and Codesys for mobile robots using IoT technology." MATEC Web of Conferences 343 (2021): 08008. http://dx.doi.org/10.1051/matecconf/202134308008.

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The industrial environment is going through exponential changes, due to the diversity of technological solutions that appear more and more frequently and the increase of productivity at increasing capacities. Due to this fact in the industrial area the number of devices, processing systems, collaborative robots, mobile robots and industrial equipment is increasing more and more. Consequently, there is a need for communication and connectivity of entities, common physical or virtual functioning and decision making, all of which are fundamental to the transition to the new concept of Industry 4.

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Zenkevich, Stanislav, Anaid Nazarova, and Jianwen Huo. "Control of mobile robot group using collaborative drone." Robotics and Technical Cybernetics 7, no. 3 (2019): 208–14. http://dx.doi.org/10.31776/rtcj.7305.

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MIYAUCHI, Takahiro, Tomohito TAKUBO, Tatsuo ARAI, and Kenichi OHARA. "4215 Collaborative Monitoring Using UFAM and Mobile Robot." Proceedings of the JSME annual meeting 2007.7 (2007): 333–34. http://dx.doi.org/10.1299/jsmemecjo.2007.7.0_333.

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YOSHIMURA, Kouki, Masaki DAIKU, Susumu TARAO, and Tetsuo TOMIZAWA. "Attempt of Mobile Manipulation by Integrating Collaborative Dual-Arms Robot and Omni-Directional Mobile Robot." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2021 (2021): 1P3—A10. http://dx.doi.org/10.1299/jsmermd.2021.1p3-a10.

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21

Que, Haohua, Haojia Gao, Weihao Shan, Xinghua Yang, and Rong Zhao. "A Lightweight, Centralized, Collaborative, Truncated Signed Distance Function-Based Dense Simultaneous Localization and Mapping System for Multiple Mobile Vehicles." Sensors 24, no. 22 (2024): 7297. http://dx.doi.org/10.3390/s24227297.

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Simultaneous Localization And Mapping (SLAM) algorithms play a critical role in autonomous exploration tasks requiring mobile robots to autonomously explore and gather information in unknown or hazardous environments where human access may be difficult or dangerous. However, due to the resource-constrained nature of mobile robots, they are hindered from performing long-term and large-scale tasks. In this paper, we propose an efficient multi-robot dense SLAM system that utilizes a centralized structure to alleviate the computational and memory burdens on the agents (i.e. mobile robots). To enab

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Sousa, Lucas C., Yago M. R. Silva, Vinícius B. Schettino, et al. "Obstacle Avoidance Technique for Mobile Robots at Autonomous Human-Robot Collaborative Warehouse Environments." Sensors 25, no. 8 (2025): 2387. https://doi.org/10.3390/s25082387.

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This paper presents an obstacle avoidance technique for a mobile robot in human-robot collaborative (HRC) tasks. The proposed solution uses fuzzy logic rules and a convolutional neural network (CNN) in an integrated approach to detect objects during vehicle movement. The goal is to improve the robot’s navigation autonomously and ensure the safety of people and equipment in dynamic environments. Using this technique, it is possible to provide important references to the robot’s internal control system, guiding it to continuously adjust its velocity and yaw in order to avoid obstacles (humans an

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Wang, Xuedong, Yingtao Huang, and Xinyuan Lu. "A Decentralized Consistent Approach for Multi-Robot Simultaneous Localization and Object Tracking." Journal of Physics: Conference Series 2762, no. 1 (2024): 012067. http://dx.doi.org/10.1088/1742-6596/2762/1/012067.

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Abstract This study focuses on the problem of multi-robot simultaneous localization and object tracking (MR-SLOT), which involves the collaborative effort of multiple mobile robots tracking a moving object on a plain. To address this challenge, this paper introduces a fully decentralized approach based on the extended Kalman filter and covariance intersection (CI), denoted as CI-SLOT. In the proposed approach, each robot can precisely track the robot-to-object correlations. Moreover information exchange occurs solely among one-hop communicating robots, and each robot only maintains the latest

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Hendi, Wicaksono Agung Fransisco Jordan. "Semi-decentralized Lyapunov-based formation control of multiple omnidirectional mobile robots." Indonesian Journal of Electrical Engineering and Computer Science 35, no. 2 (2024): 823–33. https://doi.org/10.11591/ijeecs.v35.i2.pp823-833.

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This paper introduces an advanced formation control algorithm based on a Lyapunov approach for coordinating multiple omnidirectional mobile robots in collaborative object transport tasks. The semi-decentralized strategy ensures that the robots maintain a predefined geometric formation, crucial for stability during material transportation, and dynamically adapt to avoid collisions using onboard sensors. Experimental with a physical robot simulator demonstrates successful maintenance of line and triangle formations achieving an average side length maintenance of 1.00 meters with minimal deviatio

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Agung, Hendi Wicaksono, and Fransisco Jordan. "Semi-decentralized Lyapunov-based formation control of multiple omnidirectional mobile robots." Indonesian Journal of Electrical Engineering and Computer Science 35, no. 2 (2024): 823. http://dx.doi.org/10.11591/ijeecs.v35.i2.pp823-833.

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<p>This paper introduces an advanced formation control algorithm based on a Lyapunov approach for coordinating multiple omnidirectional mobile robots in collaborative object transport tasks. The semi-decentralized strategy ensures that the robots maintain a predefined geometric formation, crucial for stability during material transportation, and dynamically adapt to avoid collisions using onboard sensors. Experimental with a physical robot simulator demonstrates successful maintenance of line and triangle formations achieving an average side length maintenance of 1.00 meters with minimal

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Tan, Bin. "Soccer-Assisted Training Robot Based on Image Recognition Omnidirectional Movement." Wireless Communications and Mobile Computing 2021 (August 16, 2021): 1–10. http://dx.doi.org/10.1155/2021/5532210.

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With the continuous emergence and innovation of computer technology, mobile robots are a relatively hot topic in the field of artificial intelligence. It is an important research area of more and more scholars. The core of mobile robots is to be able to realize real-time perception of the surrounding environment and self-positioning and to conduct self-navigation through this information. It is the key to the robot’s autonomous movement and has strategic research significance. Among them, the goal recognition ability of the soccer robot vision system is the basis of robot path planning, motion

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Xia, Yu, Xiao Wu, Tao Ma, Liucun Zhu, Jingdi Cheng, and Junwu Zhu. "Multi-Robot Collaborative Mapping with Integrated Point-Line Features for Visual SLAM." Sensors 24, no. 17 (2024): 5743. http://dx.doi.org/10.3390/s24175743.

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Simultaneous Localization and Mapping (SLAM) enables mobile robots to autonomously perform localization and mapping tasks in unknown environments. Despite significant progress achieved by visual SLAM systems in ideal conditions, relying solely on a single robot and point features for mapping in large-scale indoor environments with weak-texture structures can affect mapping efficiency and accuracy. Therefore, this paper proposes a multi-robot collaborative mapping method based on point-line fusion to address this issue. This method is designed for indoor environments with weak-texture structure

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Vitolo, Ferdinando, Andrea Rega, Castrese Di Marino, Agnese Pasquariello, Alessandro Zanella, and Stanislao Patalano. "Mobile Robots and Cobots Integration: A Preliminary Design of a Mechatronic Interface by Using MBSE Approach." Applied Sciences 12, no. 1 (2022): 419. http://dx.doi.org/10.3390/app12010419.

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Enabling technologies that drive Industry 4.0 and smart factories are pushing in new equipment and system development also to prevent human workers from repetitive and non-ergonomic tasks inside manufacturing plants. One of these tasks is the order-picking which consists in collecting parts from the warehouse and distributing them among the workstations and vice-versa. That task can be completely performed by a Mobile Manipulator that is composed by an industrial manipulator assembled on a Mobile Robot. Although the Mobile Manipulators implementation brings advantages to industrial application

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He, Zhou, Ruijie Zhang, Ning Ran, and Chan Gu. "Path Planning of Multi-Type Robot Systems with Time Windows Based on Timed Colored Petri Nets." Applied Sciences 12, no. 14 (2022): 6878. http://dx.doi.org/10.3390/app12146878.

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Mobile robots are extensively used to complete repetitive operations in industrial areas such as intelligent transportation, logistics, and manufacturing systems. This paper addresses the path planning problem of multi-type robot systems with time windows based on timed colored Petri nets. The tasks to be completed are divided into three different types: common, exclusive and collaborative. An analytical approach to plan a group of different types of mobile robots is developed to ensure that some specific robots will visit task regions within given time windows. First, a multi-type robot syste

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Yang, Liwei, Lixia Fu, Ping Li, Jianlin Mao, Ning Guo, and Linghao Du. "LF-ACO: an effective formation path planning for multi-mobile robot." Mathematical Biosciences and Engineering 19, no. 1 (2022): 225–52. http://dx.doi.org/10.3934/mbe.2022012.

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<abstract> <p>Multi-robot path planning is a hot problem in the field of robotics. Compared with single-robot path planning, complex problems such as obstacle avoidance and mutual collaboration need to be considered. This paper proposes an efficient leader follower-ant colony optimization (LF-ACO) to solve the collaborative path planning problem. Firstly, a new Multi-factor heuristic functor is proposed, the distance factor heuristic function and the smoothing factor heuristic function. This improves the convergence speed of the algorithm and enhances the smoothness of the initial

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Khan, Rabeea, Zeeshan Yousaf, Asif Memon, Sajid Hussain, and Abdul Muttalib. "Algorithm and Implementation of Human Following Co-bot using 2D LiDAR." Pakistan Journal of Engineering and Technology 4, no. 2 (2021): 89–93. http://dx.doi.org/10.51846/vol4iss2pp89-93.

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Co-bots - collaborative robots are designed to interact directly with humans in close proximity. Some human-robot collaborative applications like surveillance, clinical services, media outlets, defense, and social associations, may require an autonomous robot to have the ability to distinguish and track a person and to follow him around. Smart suitcases and smart trolleys are practical applications of human detection and following co-bots. Initially seen as a special case of object tracking, the task of person following with autonomous robots before long turned into a challenging task of its o

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Dai, Yanyan, Seokho Yang, and Kidong Lee. "Sensing and Navigation for Multiple Mobile Robots Based on Deep Q-Network." Remote Sensing 15, no. 19 (2023): 4757. http://dx.doi.org/10.3390/rs15194757.

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In this paper, a novel DRL algorithm based on a DQN is proposed for multiple mobile robots to find optimized paths. The multiple robots’ states are the inputs of the DQN. The DQN estimates the Q-value of the agents’ actions. After selecting the action with the maximum Q-value, the multiple robots’ actions are calculated and sent to them. Then, the robots will explore the area and detect the obstacles. In the area, there are static obstacles. The robots should detect the static obstacles using a LiDAR sensor. The other moving robots are recognized as dynamic obstacles that need to be avoided. T

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Zhao, Ziyan, Junzhi Cheng, Ziyao Fan, Jiaqi Liang, and Shixin Liu. "Human-robot collaborative picking optimization in robotic mobile fulfillment systems." IET Conference Proceedings 2023, no. 49 (2024): 182–88. https://doi.org/10.1049/icp.2024.3657.

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Huang, Zhihao, Chuhong Ou, Zhipeng Guo, Lei Ye, and Jin Li. "Human-Following Strategy for Orchard Mobile Robot Based on the KCF-YOLO Algorithm." Horticulturae 10, no. 4 (2024): 348. http://dx.doi.org/10.3390/horticulturae10040348.

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Autonomous mobile robots play a vital role in the mechanized production of orchards, where human-following is a crucial collaborative function. In unstructured orchard environments, obstacles often obscure the path, and personnel may overlap, leading to significant disruptions to human-following. This paper introduces the KCF-YOLO fusion visual tracking method to ensure stable tracking in interference environments. The YOLO algorithm provides the main framework, and the KCF algorithm intervenes in assistant tracking. A three-dimensional binocular-vision reconstruction method was used to acquir

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Cai, Zhi, Jiahang Liu, Weijian Chi, and Bo Zhang. "A Low-Cost and Robust Multi-Sensor Data Fusion Scheme for Heterogeneous Multi-Robot Cooperative Positioning in Indoor Environments." Remote Sensing 15, no. 23 (2023): 5584. http://dx.doi.org/10.3390/rs15235584.

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The latest development of multi-robot collaborative systems has put forward higher requirements for multi-sensor fusion localization. Current position methods mainly focus on the fusion of the carrier’s own sensor information, and how to fully utilize the information of multiple robots to achieve high-precision positioning is a major challenge. However, due to the comprehensive impact of factors such as poor performance, variety, complex calculations, and accumulation of environmental errors used by commercial robots, the difficulty of high-precision collaborative positioning is further exacer

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Mishra, Shreyansh. "Remote Controlled Agricultural Robot." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 2701–9. http://dx.doi.org/10.22214/ijraset.2024.62180.

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Abstract: The Agri Bot project presents a pioneering endeavor in the realm of autonomous agriculture by seamlessly integrating robotics, IoT, and mobile application development. Utilizing an Arduino UNO microcontroller, ESP32 camera module, servo motors, and various sensors, the system excels in executing precise agricultural tasks such as digging, filling, seed sowing, and fertilizer dispensing. The accompanying mobile application, developed through MIT App Inventor and utilizing Bluetooth communication, provides an intuitive interface for users to remotely oversee and manage the Agri Bot's o

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Lei, Yang, Jian Hou, Peixin Ma, and Mingze Ma. "Voronoi-GRU-Based Multi-Robot Collaborative Exploration in Unknown Environments." Applied Sciences 15, no. 6 (2025): 3313. https://doi.org/10.3390/app15063313.

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In modern society, the autonomous exploration of unknown environments has attracted extensive attention due to its broad applications, such as in search and rescue operations, planetary exploration, and environmental monitoring. This paper proposes a novel collaborative exploration strategy for multiple mobile robots, aiming to quickly realize the exploration of entire unknown environments. Specifically, we investigate a hierarchical control architecture, comprising an upper decision-making layer and a lower planning and mapping layer. In the upper layer, the next frontier point for each robot

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Yasuda, Motohiro, Hiroshi Ogiya, and Nobuto Matsuhira. "Shared map for multiple teleoperated robot system with RSNP to perform a collaborative task : An exploration experiment by two mobile robots." Abstracts of the international conference on advanced mechatronics : toward evolutionary fusion of IT and mechatronics : ICAM 2015.6 (2015): 41–42. http://dx.doi.org/10.1299/jsmeicam.2015.6.41.

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Sun, Ying, Wenlu Wang, Manman Xu, et al. "Local Path Planning for Mobile Robots Based on Fuzzy Dynamic Window Algorithm." Sensors 23, no. 19 (2023): 8260. http://dx.doi.org/10.3390/s23198260.

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Due to the increased employment of robots in modern society, path planning methods based on human–robot collaborative mobile robots have been the subject of research in both academia and industry. The dynamic window approach used in the research of the robot local path planning problem involves a mixture of fixed weight coefficients, which makes it hard to deal with the changing dynamic environment and the issue of the sub-optimal global planning paths that arise after local obstacle avoidance. By dynamically modifying the combination of weight coefficients, we propose, in this research, the u

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Ponce, Hiram E., Dejanira Araiza, and Pedro Ponce. "A Neuro-Fuzzy Controller for Collaborative Applications in Robotics Using LabVIEW." Applied Computational Intelligence and Soft Computing 2009 (2009): 1–9. http://dx.doi.org/10.1155/2009/657095.

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A neuro-fuzzy controller was designed and implemented using LabVIEW over a mobile robotic platform. The controller is based on fuzzy clusters, neural networks, and search techniques. Also, wireless communication with Bluetooth protocol was used to communicate the robot with the controller running in LabVIEW, allowing a simple collaborative task that consisted in pick and place objects, through knowing the position of the robot and measuring the distance to the objects. The neuro-fuzzy controller was split in two parts: the position controller and the evasion controller against collisions.

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Thirumalairajan, Mr S. "Design and Development of Autonomous Mobile Robot for Material Handling Application." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 5566–94. https://doi.org/10.22214/ijraset.2025.71204.

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In the evolving domain of logistics and supply chain management, efficiency, accuracy, and scalability have become essential to meet growing demands. This project introduces a cutting-edge autonomous mobile robot designed for material handling and inventory management in warehouses. Utilizing advanced technologies, the robot integrates Radio Frequency Identification (RFID) for real-time product identification and tracking, RPLIDAR for navigation and mapping using Simultaneous Localization and Mapping (SLAM), and a Raspberry Pi 4 as the central processing unit. With the Robot Operating System (

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Cañadas-Aránega, Fernando, José C. Moreno, José L. Blanco-Claraco, Antonio Giménez, Francisco Rodríguez, and Julián Sánchez-Hermosilla. "Autonomous collaborative mobile robot for greenhouses: Design, development, and validation tests." Smart Agricultural Technology 9 (December 2024): 100606. http://dx.doi.org/10.1016/j.atech.2024.100606.

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Ghelichi, Zabih, and Srikanth Kilaru. "Analytical models for collaborative autonomous mobile robot solutions in fulfillment centers." Applied Mathematical Modelling 91 (March 2021): 438–57. http://dx.doi.org/10.1016/j.apm.2020.09.059.

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Karcı, Efe Oğuzhan, Ahmet Mustafa Kangal, and Sinan Öncü. "Improvement of Cooperative Localization for Heterogeneous Mobile Robots." Drones 9, no. 7 (2025): 507. https://doi.org/10.3390/drones9070507.

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This research focuses on enhancing cooperative localization for heterogeneous mobile robots composed of a quadcopter and an unmanned ground vehicle. The study employs sensor fusion techniques, particularly the Extended Kalman Filter, to fuse data from various sensors, including GPSs, IMUs, and cameras. By integrating these sensors and optimizing fusion strategies, the research aims to improve the precision and reliability of cooperative localization in complex and dynamic environments. The primary objective is to develop a practical framework for cooperative localization that addresses the cha

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Paniti, Imre, János Nacsa, Péter Kovács, and Dávid Szur. "Human-robot collision predictor for flexible assembly." ACTA IMEKO 10, no. 3 (2021): 72. http://dx.doi.org/10.21014/acta_imeko.v10i3.1072.

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<p class="Abstract"><span lang="EN-US">The performance of human–robot collaboration can be improved in some assembly tasks when a robot emulates the effective coordination behaviours observed in human teams. However, this close collaboration could cause collisions, resulting in delays in the initial scheduling. Besides the commonly used acoustic or visual signals, vibrations from a mobile device can be used to communicate the intention of a collaborative robot (cobot). In this paper, the communication time of a virtual reality and depth camera-based system is presented in which vib

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Hentout, Abdelfetah, Abderraouf Maoudj, Nesrine Kaid-youcef, Djamila Hebib, and Brahim Bouzouia. "Distributed Multi-agent Bidding-Based Approach for the Collaborative Mapping of Unknown Indoor Environments by a Homogeneous Mobile Robot Team." Journal of Intelligent Systems 29, no. 1 (2017): 84–99. http://dx.doi.org/10.1515/jisys-2017-0255.

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Abstract This paper deals with the problem of the collaborative mapping of unknown indoor environments by a homogeneous mobile robot team. For this aim, a distributed multi-agent coordination approach is proposed for the mapping process to offer a global view of the entire environment. First, the scheme starts by assigning the most suitable robots to the different zones of the environment to be mapped based on a bidding strategy. Then, while a Robot agent of the group explores its local surroundings and collects information about its neighborhood, it sends mapping data to the Human/Machine Int

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Nasr, Mohammad, Nihar Masurkar, Pouria Meshkizadeh, and Ehsan Dehghan-Niri. "Guided by Hearing: Robotic Motion Planning for Precision in Gas Leakage Localization." Materials Evaluation 83, no. 4 (2025): 51–61. https://doi.org/10.32548/2025.me-04491.

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This research proposes a motion planning framework for a robot equipped with a bioinspired hearing system to enhance its sound source localization, specifically for gas leak detection. Similar to how animals use movements, such as changing positions or rotating their ears, to precisely localize a sound source, this framework enables the robot to improve its estimation of both direction and distance through strategic motion. The proposed method uses the time difference of arrival (TDOA) between two wideband optical microphones, obtained through this motion, to accurately estimate the direction

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Liu, Guohua, Juan Guan, Haiying Liu, and Chenlin Wang. "Multirobot Collaborative Navigation Algorithms Based on Odometer/Vision Information Fusion." Mathematical Problems in Engineering 2020 (August 27, 2020): 1–16. http://dx.doi.org/10.1155/2020/5819409.

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Collaborative navigation is the key technology for multimobile robot system. In order to improve the performance of collaborative navigation system, the collaborative navigation algorithms based on odometer/vision multisource information fusion are presented in this paper. Firstly, the multisource information fusion collaborative navigation system model is established, including mobile robot model, odometry measurement model, lidar relative measurement model, UWB relative measurement model, and the SLAM model based on lidar measurement. Secondly, the frameworks of centralized and decentralized

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Dmytro, Gurin, Yevsieiev Vladyslav, Abu-Jassar Amer, and Maksymova Svitlana. "Using the Kalman Filter to Represent Probabilistic Models for Determining the Location of a Person in Collaborative Robot Working Area." Multidisciplinary Journal of Science and Technology 4, no. 8 (2024): 66–75. https://doi.org/10.5281/zenodo.13348731.

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The article is devoted to the study of the use of the Kalman filter for the development of probabilistic models for determining the location of a person in collaborative robot working area. The article discusses in detail the mathematical representation of the Kalman filter, including formulas for estimating and predicting system states based on measurements with noise. A software implementation of the Kalman filter was carried out, including the development of an algorithm for processing data from a video camera, which ensures accurate tracking of a person. As part of the research, a series o

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Zhou, Chengzhi. "Enhancing 2D Path Search and PID Control for Autonomous Mobile Robots: A* Algorithm Optimization and Hardware." Advances in Engineering Technology Research 9, no. 1 (2024): 723. http://dx.doi.org/10.56028/aetr.9.1.723.2024.

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Intelligent autonomous mobile robots find diverse applications across various fields. This article delves into the optimization of path search planning and implementation for these robots in specific scenarios. The study enhances the traditional right-hand principle's search strategy, integrating a forward-looking approach grounded in the goal-oriented law with A* algorithm path planning. Emphasizing the algorithm's lightweight and high efficiency, the study also considers its interaction with hardware systems. The real-world application scenario is abstracted into a two-dimensional planar env

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