Optimization of fuzzy behavior-based robots navigation in partially known industrial environments

Deals with the optimization of the reactive navigation performed with fuzzy behaviors in partially known environments. It offers the integration of the fuzzy behaviors with global path-planning techniques in a nested hierarchical architecture for autonomous vehicle navigation. A three level architecture is proposed based on a global path-planner level, a fuzzy behaviors level and an execution level. While the global path-planning level offers optimization in the solution, the fuzzy behaviors level gives the flexibility and robustness required for navigation in uncertain and unpredictable environments. The integrated system allows a mobile robot to plan a path from an initial to a final position, select the fuzzy behaviors to accomplish the navigation based on the sensors readings and control its execution in real time. Some simulation and experimental results are presented to show the navigation of a mobile robot in partially known industrial environments.<>