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Dynamic path planning of mobile robot based onimproved ant colony algorithm(PDF)


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Dynamic path planning of mobile robot based onimproved ant colony algorithm
Wang LeiShi Xin
College of Mechanical and Automotive Engineering,Anhui Polytechnic University,Wuhu 241000,China
improved ant colony algorithm mobile robots local path planning dynamic environment grid method optimal path concave obstacles
Aiming at the shortest path searching problem of mobile robots in a dynamic environment,a path planning model is established using the grid method,and an improved ant colony algorithm is presented. The volatilization coefficient is changed adaptively by adjusting pheromone heuristic factors and expectation heuristic factors. In the path planning process,a corresponding dynamic path planning collision avoidance strategy is proposed to enable the robot to obtain the optimal or sub-optimal path and avoid obstacle simultaneously. The experimental results show that the improved algorithm needs 25 generations to achieve better convergence and find the shortest path when the robot is trapped in a concave obstacle with low search efficiency in a complex environment; the improved algorithm reduces by nearly 50 generations than the basic ant colony algorithm,and it can effectively avoid the collision between the mobile robot and dynamic obstacles,and obtain a 15.656 collision-free optimal path.


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Last Update: 2019-12-31