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Fuzzy logic based design of classical behaviors for mobile robots in ROS middleware

机译:基于模糊逻辑的ROS中间件移动机器人的古典行为设计

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Autonomous mobile vehicles are used in many applications to realize special tasks. These tasks involve obstacle avoidance, target reaching and/or tracking. Such vehicles include the use of artificial intelligence to assist the vehicle's operator. Fuzzy logic can be used in the design of an autonomous vehicle to improve the classical control mechanisms. Classical robot control/decision mechanisms can give imperfect results due to sensor compensation errors or calculation costs. These drawbacks can be eliminated by using a combined fuzzy inference. In this study, we have modified the mobile robot ATEKS, which is an intelligent wheelchair, by introducing three fuzzy inference systems to realize goal reaching, obstacle avoidance and a controller for combined behavior selection. Designed fuzzy control system has been implemented on Robot Operating System (ROS) under Ubuntu 12.04 operating system and tested under Gazebo simulation platform. Simulation results verified faithful behavior outputs of ATEKS.
机译:自主移动车辆用于许多应用程序来实现特殊任务。这些任务涉及避免障碍物,目标到达和/或跟踪。这种车辆包括使用人工智能来帮助车辆的操作员。模糊逻辑可用于自主车辆的设计,以改善古典控制机制。古典机器人控制/判定机制可以引起的不完美结果,因为传感器补偿误差或计算成本。可以通过使用组合的模糊推理来消除这些缺点。在这项研究中,我们通过引入三种模糊推理系统来实现一个智能轮椅的移动机器人吃掉,这是一种用于实现目标达到的目标,避免障碍物和组合行为选择的控制器。设计的模糊控制系统已经在Ubuntu 12.04操作系统下的机器人操作系统(ROS)上实现,并在凉亭仿真平台下进行了测试。仿真结果已验证吃东西的忠实行为产出。

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