Robot navigation in cluttered 3-D environments using preference-based fuzzy behaviors

Autonomous navigation systems for mobile robots have been successfully deployed for a wide range of planar ground-based tasks. However, very few counterparts of previous planar navigation systems were developed for 3-D motion, which is needed for both unmanned aerial and underwater vehicles. A novel fuzzy behavioral scheme for navigating an unmanned helicopter in cluttered 3-D spaces is developed. The 3-D navigation problem is decomposed into several identical 2-D navigation subproblems, each of which is solved by using preference-based fuzzy behaviors. Due to the shortcomings of vector summation during the fusion of the 2-D subproblems, instead of directly outputting steering subdirections by their own defuzzification processes, the intermediate preferences of the subproblems are fused to create a 3-D solution region, representing degrees of preference for the robot movement. A new defuzzification algorithm that steers the robot by finding the centroid of a 3-D convex region of maximum volume in the 3-D solution region is developed. A fuzzy speed-control system is also developed to ensure efficient and safe navigation. Substantial simulations have been carried out to demonstrate that the proposed algorithm can smoothly and effectively guide an unmanned helicopter through unknown and cluttered urban and forest environments.