Improved Dynamic Window Approach using the jerk model

Abstract

The Dynamic Window Approach (DWA) method is a collision avoidance strategy for mobile robots that is optimized to take a robot to its goal while maintaining a minimum distance from any obstacle. However, owing to its velocity invariance assumption, it generates narrow paths that may not enable it to avoid obstacles. In addition, it is impossible to control thejerk. To address these issues, we propose a method for generating speed change paths based on jerk models. First, we limited the maximum jerk in the model. Second, we used the model to generate variable speed sequences to obtain a wider range of paths. We added jerk as a term in the evaluation function to prevent consistently large jerks. We verified the effectiveness of the proposed method by comparing the results with the conventional method through simulation experiments.