Multi-Agent Decision Fusion and Its Application in Adversarial Multi-robot System

This paper puts forward a multi-Agent alliance control model that is made up of the series robot Agent, the parallel moving platform Agent and the polishing tool system Agent and so on by the MAS theory. Based on the multi-robot system which is made up of the MOTOMAN - HP3 serial robot and NPT800 parallel robot, the MOTOMAN-HP3 serial robot communication, the NPT800 parallel robot of motion control and communication between two robots are introduced respectively. In the end, the mutual communication can be accomplished by two robots and the robot position and status information can be transported with programming of the win socket. The satisfied polishing effect on the curved surfaces can be obtained and the demand of the polishing can be achieved by the MAS.

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Multi-Agent Robot System and Events Executing Using GPS Cloud

Journal of Informatics and Data Mining ◽

10.21767/2472-1956.100010 ◽

2016 ◽

Vol 1 (2) ◽

Author(s):

Abdellah Redjaimia

Keyword(s):

Robot System ◽

Multi Agent

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Reinforcement-Learning-Based Asynchronous Formation Control Scheme for Multiple Unmanned Surface Vehicles

Applied Sciences ◽

10.3390/app11020546 ◽

2021 ◽

Vol 11 (2) ◽

pp. 546

Author(s):

Jiajia Xie ◽

Rui Zhou ◽

Yuan Liu ◽

Jun Luo ◽

Shaorong Xie ◽

...

Keyword(s):

Reinforcement Learning ◽

Formation Control ◽

Rapid Development ◽

Gradient Algorithm ◽

Robot System ◽

Physical Relationship ◽

Unmanned Surface Vehicles ◽

Main Challenge ◽

Control Scheme ◽

Multi Robot

The high performance and efficiency of multiple unmanned surface vehicles (multi-USV) promote the further civilian and military applications of coordinated USV. As the basis of multiple USVs’ cooperative work, considerable attention has been spent on developing the decentralized formation control of the USV swarm. Formation control of multiple USV belongs to the geometric problems of a multi-robot system. The main challenge is the way to generate and maintain the formation of a multi-robot system. The rapid development of reinforcement learning provides us with a new solution to deal with these problems. In this paper, we introduce a decentralized structure of the multi-USV system and employ reinforcement learning to deal with the formation control of a multi-USV system in a leader–follower topology. Therefore, we propose an asynchronous decentralized formation control scheme based on reinforcement learning for multiple USVs. First, a simplified USV model is established. Simultaneously, the formation shape model is built to provide formation parameters and to describe the physical relationship between USVs. Second, the advantage deep deterministic policy gradient algorithm (ADDPG) is proposed. Third, formation generation policies and formation maintenance policies based on the ADDPG are proposed to form and maintain the given geometry structure of the team of USVs during movement. Moreover, three new reward functions are designed and utilized to promote policy learning. Finally, various experiments are conducted to validate the performance of the proposed formation control scheme. Simulation results and contrast experiments demonstrate the efficiency and stability of the formation control scheme.

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Voronoi-based Geometric Distributed Fleet Control of a Multi-Robot System

2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV) ◽

10.1109/icarcv50220.2020.9305373 ◽

2020 ◽

Author(s):

Sylvain Bertrand ◽

Ioannis Sarras ◽

Alexandre Eudes ◽

Julien Marzat

Keyword(s):

Robot System ◽

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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Modelling and verification of reconfigurable multi-agent systems

Autonomous Agents and Multi-Agent Systems ◽

10.1007/s10458-021-09521-x ◽

2021 ◽

Vol 35 (2) ◽

Author(s):

Yehia Abd Alrahman ◽

Nir Piterman

Keyword(s):

Model Checking ◽

Communication Protocols ◽

Local State ◽

Multi Agent Systems ◽

Agent Systems ◽

Robot Systems ◽

Message Exchange ◽

Multi Agent ◽

Exchange Data ◽

Multi Robot

AbstractWe propose a formalism to model and reason about reconfigurable multi-agent systems. In our formalism, agents interact and communicate in different modes so that they can pursue joint tasks; agents may dynamically synchronize, exchange data, adapt their behaviour, and reconfigure their communication interfaces. Inspired by existing multi-robot systems, we represent a system as a set of agents (each with local state), executing independently and only influence each other by means of message exchange. Agents are able to sense their local states and partially their surroundings. We extend ltl to be able to reason explicitly about the intentions of agents in the interaction and their communication protocols. We also study the complexity of satisfiability and model-checking of this extension.

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