Suo Tan, Simon X. Yang, and Anmin Zhu
Mobile robots, A/B module, fuzzy logic control, genetic algorithm, moving obstacles
A novel genetic algorithm (GA)-based fuzzy-inference control system with an accelerate/brake (A/B) module is proposed in this paper for mobile robots navigating in dynamic environments. The adaptive A/B module is to infuse human-like decision-making strategy into the mobile robot for smooth collision-free navigation toward the target. The proposed fuzzy-inference model is capable of controlling the robot avoiding both static and moving obstacles with human- like intelligence, along a reasonable short path. In addition, a GA module is designed to tune the membership functions, which optimizes the performance of the fuzzy-inference system for a short and smooth robot path to reach the target. Simulation and experimental results demonstrate the feasibility and effectiveness of the proposed approach to autonomous navigation of mobile robots in dynamic environments.
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