Robot path planning algorithms can plan a safe path from one point to another, and Dynamic Window Approach (DWA) is a commonly used planning algorithm. However, such method usually does not consider the direction of the robot, so that the robot at the planning end point has a large deviation from the desired direction. At the same time, the robot is not sensitive enough to dynamic obstacles during planning. In this paper, a fuzzy-based improved DWA is proposed for path planning of mobile robot. In the local path planning, the cost functions of the traditional DWA are optimized to regulate the robot direction. The fuzzy controller is introduced to dynamically tune the planning tendency of the robot in each stage. Compared with the traditional DWA algorithm, the improved DWA algorithm can enable the robot to complete the planning with end-direction constraints in unknown environments. Simulations of two static scenes and two dynamic scenes show that robot can move to the destination in high direction accuracy and effectively avoid obstacle with fuzzy-based DWA.
A Fuzzy-Based Improved Dynamic Window Approach for Path Planning of Mobile Robot
Lect.Notes Computer
International Conference on Intelligent Robotics and Applications ; 2023 ; Hangzhou, China July 05, 2023 - July 07, 2023
16.10.2023
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Path planning , improved DWA algorithm , fuzzy logic Computer Science , Artificial Intelligence , Software Engineering/Programming and Operating Systems , Computer Applications , User Interfaces and Human Computer Interaction , Computer Communication Networks , Special Purpose and Application-Based Systems
Mobile Robot Path Planning Based on Improved Ant Colony Fusion Dynamic Window Approach
British Library Conference Proceedings | 2021
|Q-Learning Based Robot Path Planning with Improved Dynamic Window Approach
Springer Verlag | 2022
|Global Dynamic Path Planning Based on Fusion of Improved A^* Algorithm and Dynamic Window Approach
British Library Online Contents | 2017
|