A multi-robot cooperation strategy for dexterous task oriented teleoperation

In this paper, we compare the common plume-tracing algorithms: chemotaxis and anemotaxis in obstructed multi-source environment using multi-robot system. A multi-robot cooperation strategy with virtual physics force, which includes structure formation force, goal force, obstacle avoidance force, repulsion force and rotary force, is proposed. First, plume model with two sources in three obstacles environment is constructed by computation fluid dynamics simulations. Second, parallel searches by two groups robots with chemotaxis and anemotaxis are used to locate two sources in obstructed environment. Simulation comparison experiment with two plume-tracing algorithms discussed the influence of the varied wind direction/ speed frequency and methane release frequency and different initial positions of two groups to the search performance. Finally, the comparative result is illustrated.

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Multi-Robot Cooperation Strategy in Game Environment Using Deep Reinforcement Learning

2018 IEEE International Conference on Robotics and Biomimetics (ROBIO) ◽

10.1109/robio.2018.8665165 ◽

2018 ◽

Cited By ~ 1

Author(s):

Hongda Zhang ◽

Decai Li ◽

Yuqing He

Keyword(s):

Reinforcement Learning ◽

Cooperation Strategy ◽

Game Environment ◽

Robot Cooperation ◽

Multi Robot

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A PSO-Based Approach with Fuzzy Obstacle Avoidance for Cooperative Multi-Robots in Unknown Environments

International Journal of Computational Intelligence and Applications ◽

10.1142/s1469026816500012 ◽

2016 ◽

Vol 15 (01) ◽

pp. 1650001 ◽

Cited By ~ 5

Author(s):

Yifan Cai ◽

Simon X. Yang

Keyword(s):

Obstacle Avoidance ◽

Fitness Function ◽

Field Function ◽

Robot Trajectory ◽

Unknown Environments ◽

Cooperation Strategy ◽

Key Issues ◽

Robot Cooperation ◽

Target Searching ◽

Multi Robot

Cooperative exploration in unknown environments is fundamentally important in robotics, where the real-time path planning and proper task allocation strategies are the key issues for multi-robot cooperation. In this paper, a PSO-based approach, combined with a fuzzy obstacle avoidance module, is proposed for cooperative robots to accomplish target searching and foraging tasks in unknown environments. The proposed cooperation strategy for a multi-robot system makes use of the potential field function as the fitness function of PSO, while the proposed fuzzy obstacle-avoidance module improves the smoothness of robot trajectory. In the simulation studies, several scenarios with and without the fuzzy module are investigated. The robot trajectory smoothness improvement is demonstrated through the comparative studies.

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Improvised multi-robot cooperation strategy for hunting a dynamic target

EAI Endorsed Transactions on Internet of Things ◽

10.4108/eai.8-2-2021.168691 ◽

2021 ◽

Vol 6 (24) ◽

pp. 168691

Author(s):

Oussama Hamed ◽

Mohamed Hamlich

Keyword(s):

Cooperation Strategy ◽

Dynamic Target ◽

Robot Cooperation ◽

Multi Robot

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Localizing Multiple Odor Sources Using Virtual Physics Based Robots

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.756-759.223 ◽

2013 ◽

Vol 756-759 ◽

pp. 223-227

Author(s):

Yu Li Zhang ◽

Xiao Ping Ma

Keyword(s):

Search Performance ◽

Simulation Environment ◽

Robot System ◽

Comparative Result ◽

System A ◽

Cooperation Strategy ◽

Robot Cooperation ◽

Dynamics Simulations ◽

Multiple Chemical ◽

Multi Robot

This paper is concerned with the problem of multiple chemical sources localization using multi-robot system. A multi-robot cooperation strategy with virtual physics force, which includes structure formation force, goal force, repulsion force and rotary force, is proposed. First, in order to test the effectiveness of the proposed strategy, two sources plume model are constructed by computation fluid dynamics simulations. Second, parallel search by two groups robots is used to locate two sources in simulation environment. With the purpose of preventing two groups from locating the same source, we proposed a rotary force which made each subgroup can locate different chemical source. Simulation experiment discussed the influence of the varied wind direction/ speed frequency and methane release frequency and different initial positions of two groups to the search performance. Finally, the comparative result about them is illustrated.

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