A Multi-Agent Local Search Strategy for Robots Navigation
Haiyang Song, Yue Sun, Siyang Chen, Xi Yang, Kunhao Yuan · 2022
This paper proposes a multi-agent local search strategy for mobile robots. In Solving the problem of manual gas inspection in the chemical industry, the last decades have seen increasingly rapid advances in robot navigation and inspection. However, much of the research has been descriptive and limited to a 2D environment, ignoring the factory’s complex environment and needing multi-robot corporation strategies for complex tasks. The paper, therefore, implements a multi-agent framework that offers more flexibility by allowing agents to collaborate while learning and making autonomous decisions. This multi-agent framework uses 3D laser radar to model the surrounding environment and then develops a local searching strategy in cooperation with path planning to achieve autonomous navigation. The simulation results show that the Robot Operating System(ROS) based multi-agent local search strategy can reduce target searching time.