Affiliation:
1. School of Electrical Engineering, Shenyang University of Technology, Shenyang 110020, China
2. Intelligent Robot Laboratory, Shenyang Open University, Shenyang 110020, China
3. Department of Intelligent Mechanical Systems Engineering, Kochi University of Technology, Kochi 782-8502, Japan
Abstract
At present, autonomous mobile robots are widely used in industrial and commercial fields. However, although the global path searched by existing mobile robot path planning methods has no collision with obstacles, there is a problem in that the path is close to obstacles and is not smooth, and there is a collision safety risk when the robot is actually moving. To solve the above problems, this paper proposes a global path planning method based on minimizing the risk index. Firstly, the distance calculation method of the heuristic function of the traditional graph search algorithm is improved to reduce the number of nodes in the search space. Additionally, by selecting the appropriate search neighborhood, the search efficiency and path smoothness of the algorithm are improved. Thirdly, to increase the distance between the original search path and obstacles, the risk index path search strategy is proposed. Finally, the minimized snap trajectory smoothing method with a safe corridor is used to smooth the original waypoint. Both simulation and real robot experimental results show that the minimum distance between waypoints and obstacles is increased by 43.72% on average, and the number of trajectory inflection points are reduced by 75.12% on average after optimization. As such, the proposed method can fully guarantee safety and generate smooth mobile robot paths in global trajectory planning tasks.
Funder
111Project
Science and Technology Department of Liaoning Province, Natural Science Foundation of Liaoning Province
General Program of Liaoning Provincial Department of Education
Subject
Control and Optimization,Control and Systems Engineering
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