Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots

The path planning and obstacles avoidance in dynamic environments are vitally important problems for auto-navigation of mobile robots. Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows approach is poor, while the generated paths are not smooth. Thus, this paper proposed a fuzzy logic improved dynamic windows approach. Firstly, the energy consumption model of the drive motor is established and used to extend the evaluation function of the dynamic windows approach, which helps to improve the smoothness of generated paths. Secondly, three fuzzy logic controllers are designed based on the directional rules, safety rules and fusion rules respectively to output weight parameters real-time, which improves the robustness. In static and dynamic simulations, maps with sizes of 20 × 20 and 30 × 30 are designed respectively to compare the paths generated by the algorithm proposed in this study with the dynamic windows approach that selects different weight parameters. The results show that although the average calculation time of fuzzy logic improved dynamic windows approach is slightly longer, the robustness is better, the generated path is shorter, and the energy consumption of the drive motors is lower. The LEO ROS mobile robot is selected for the experiments, the results also show that compared with the dynamic windows approach and the time elastic band, the algorithm proposed in this study has better performance in terms of length and smoothness of paths and robustness.