Distributed sensor fusion for object position estimation by multi-robot systems

Education is facing challenges to keep pace with the widespread introduction of robots and digital technologies in industry and everyday life. These challenges necessitate new approaches to impart students at all levels of education with the knowledge of smart connected robot systems. This paper presents the high-school enrichment program Intelligent Robotics and Smart Transportation, which implements an approach to teaching the concepts and skills of robot connectivity, collaborative sensing, and artificial intelligence, through practice with multi-robot systems. The students used a simple control language to program Bioloid wheeled robots and utilized Phyton and Robot Operating System (ROS) to program Tello drones and TurtleBots in a Linux environment. In their projects, the students implemented multi-robot tasks in which the robots exchanged sensory data via the internet. Our educational study evaluated the contribution of the program to students’ learning of connectivity and collaborative sensing of robot systems and their interest in modern robotics. The students’ responses indicated that the program had a high positive contribution to their knowledge and skills and fostered their interest in the learned subjects. The study revealed the value of learning of internet of things and collaborative sensing for enhancing this contribution.

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Decentralized Task and Path Planning for Multi-Robot Systems

IEEE Robotics and Automation Letters ◽

10.1109/lra.2021.3068103 ◽

2021 ◽

Vol 6 (3) ◽

pp. 4337-4344

Author(s):

Yuxiao Chen ◽

Ugo Rosolia ◽

Aaron D. Ames

Keyword(s):

Path Planning ◽

Robot Systems ◽

Multi Robot

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Robustness of Multi-Robot Systems Controlling the Size of the Connected Component After Robot Failure

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2020.12.1052 ◽

2020 ◽

Vol 53 (2) ◽

pp. 3137-3143

Author(s):

Toru Murayama ◽

Lorenzo Sabattini

Keyword(s):

Connected Component ◽

Robot Systems ◽

Multi Robot

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Research Progress on Synergistic Technologies of Agricultural Multi-Robots

Applied Sciences ◽

10.3390/app11041448 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1448

Author(s):

Wenju Mao ◽

Zhijie Liu ◽

Heng Liu ◽

Fuzeng Yang ◽

Meirong Wang

Keyword(s):

Path Planning ◽

Formation Control ◽

Research Progress ◽

Hybrid Architecture ◽

Labor Costs ◽

Robot System ◽

System Architectures ◽

Research Results ◽

Robot Systems ◽

Multi Robot

Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.

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