Intelligent Optimization of Adaptive Dynamic Window Approach for Mobile Robot Motion Control Using Fuzzy Logic

The paper presents an adaptive dynamic window approach (DWA) for mobile robot dynamic obstacles avoidance optimized utilizing a fuzzy logic controller. Most of the present work on autonomous navigation in dynamic environments does not take into account the dynamics of the obstacles. One of the methods used in research today for dynamic obstacles avoidance is the dynamic window approach. The (DWA) is a well-known navigation scheme. One problem facing the DWA is how to optimize the weights of its objective function to allow the robot to move towards the goal while avoiding collisions in all environments. The main contribution of this paper is to build an intelligent system that will be able to optimize the objective function weights of the dynamic window to make it more resilient to changes and moves as fast as possible towards the goal using fuzzy logic system. The proposed new adaptive controller was able to reduce the failure rate of the DWA from 20% to only five per cent in static environments, and maintain more than 60% success rate in dynamic environments with up to 25 obstacles/100 m2, on the other hand the basic algorithm was failing to less than 50% with 15 obstacles/100 m2.

Automated summary

The paper presents an adaptive dynamic window approach with a fuzzy logic controller for mobile robot dynamic obstacles avoidance. The proposed method optimizes the objective function weights to make the robot more resilient to changes and move towards the goal as fast as possible. Experimental results show that the proposed method significantly improves the success rate in both static and dynamic environments.