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Sensor-based control versus neural network technology for the control of fast mobile robots behaviors in unstructured environments

机译:基于传感器的控制与神经网络技术在非结构化环境中控制快速移动机器人行为

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摘要

The authors address the problem of reactive behaviors for collision avoidance of fast mobile robots moving in unstructured and dynamic environments. Two approaches have been developed, simulated and implemented on fast indoor and outdoor vehicles. The first approach is based on the original description of a virtual deformable zone surrounding the robot. The deformations of this risk zone, due to the intrusion of proximity information, control the robot reactions. The second approach is based on neural network technology. The network inputs are the measured distances of obstacles in the path of the robot and its velocity. Its outputs are the controls of the robot acceleration, direction, and braking actuators.
机译:作者解决了避免在非结构化和动态环境中移动的快速移动机器人冲突的反应行为问题。在快速室内和室外车辆上开发了两种方法,模拟和实施。第一方法基于机器人周围的虚拟可变形区域的原始描述。由于近距离信息的侵入,这种风险区的变形,控制机器人反应。第二种方法是基于神经网络技术。网络输入是机器人路径中的障碍物的测量距离及其速度。其输出是机器人加速度,方向和制动件的控制。

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