Shi Dongqing, Collins Emmanuel G, Dunlap Damion
Florida A&M University-Florida State University, Tallahassee, FL 32310, USA.
IEEE Trans Syst Man Cybern B Cybern. 2007 Dec;37(6):1486-99. doi: 10.1109/tsmcb.2007.904581.
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.
移动机器人的自主导航系统已成功应用于广泛的平面地面任务。然而，先前的平面导航系统很少有适用于三维运动的对应系统，而无人飞行器和水下航行器都需要三维运动。本文开发了一种新颖的模糊行为方案，用于在杂乱的三维空间中导航无人直升机。三维导航问题被分解为几个相同的二维导航子问题，每个子问题都通过基于偏好的模糊行为来解决。由于在二维子问题融合过程中向量求和存在缺点，子问题的中间偏好不是通过各自的去模糊化过程直接输出转向子方向，而是进行融合以创建一个三维解区域，该区域表示机器人运动的偏好程度。本文开发了一种新的去模糊化算法，通过在三维解区域中找到最大体积的三维凸区域的质心来引导机器人。还开发了一种模糊速度控制系统，以确保高效安全的导航。大量仿真结果表明，该算法能够在未知且杂乱的城市和森林环境中平稳有效地引导无人直升机飞行。
