Formation Control Study Based on Improved Dynamic Window Approach and Artificial Potential Field Method
To address the lack of individual collision avoidance strategies in dynamic window approach(DWA)for multi-robot formation control,as well as the issue of ineffective target point reaching due to interactions among formation members,a formation control algo-rithm is proposed,which integrates DWA with the artificial potential field method.The efficiency of formation control and the ability of individual collision avoidance are enhanced through three key improvements.Firstly,the artificial potential field method is incorporated to effectively achieve collision avoidance among individuals.Secondly,the sliding window design is optimized by introducing steering constraints,enhancing the robots'ability to navigate towards the goal and global search capability in unknown environments.Thirdly,the evaluation function is reconstructed to prioritize goal navigation at long distances and enhance exploration capabilities at closer ranges.Finally,the results of a series of experiments demonstrate the significant advantages of the improved DWA in enhancing multi-robot for-mation control effectiveness and collision avoidance performance,thereby improving the navigation efficiency of robots and their obstacle and collision avoidance capabilities in complex environments.
formation controldynamic window methodartificial potential field methodunknown environment
万方数据
维普
