Implementation of Multi-valued Fuzzy Behavior Control for Robot Navigation in Cluttered Environments

M. Selekwa, D. Dunlap, E. Collins
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引用次数: 25

Abstract

Navigation in environments that are densely cluttered with obstacles is still a challenge for Autonomous Ground Vehicles (AGVs), especially when the configuration of obstacles is not known a priori. Reactive local navigation schemes that tightly couple the robot actions to the sensor information have proved to be effective in these environments, and because of the environmental uncertainties, fuzzy behavior systems have been proposed. The most difficult problem in applying these systems is that of arbitrating or fusing the reactions of the individual behaviors. This paper presents an architectural design of a fuzzy behavior based system for navigation control of robotic vehicles using multivalued reactive fuzzy behaviors. This design allows the robot to thoroughly use the available sensor information when choosing the control action to be taken. Experimental results show that the proposed method can smoothly and effectively guide a robot through cluttered environments such as dense forests.
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混沌环境下机器人导航的多值模糊行为控制
对于自动地面车辆(agv)来说,在障碍物密集的环境中导航仍然是一个挑战,尤其是在障碍物的配置未知的情况下。在这些环境中,将机器人动作与传感器信息紧密耦合的响应式局部导航方案被证明是有效的,由于环境的不确定性,模糊行为系统被提出。应用这些系统最困难的问题是如何仲裁或融合个体行为的反应。提出了一种基于模糊行为的机器人导航控制系统的体系结构设计,该系统采用多值反应模糊行为。这种设计允许机器人在选择要采取的控制动作时充分利用可用的传感器信息。实验结果表明,该方法能够平稳有效地引导机器人通过茂密森林等杂乱环境。
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