The ground surveillance robot (GSR): An autonomous vehicle designed to transit unknown terrain

S. Harmon
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引用次数: 79

Abstract

The Ground Surveillance Robot (GSR) project has proceeded continuously since the Fall of 1980, and in that time an autonomous vehicle design and some degree of implementation has been achieved. The vehicle design has been partitioned into sensor, control, and planning subsystems. A distributed blackboard scheme has been developed which provides the mechanism by which these subsystems are coordinated. Vehicle position and orientation are supplied by vehicle attitude and navigation sensor subsystems. Obstacle avoidance capability has been implemented by fusing information from vision and acoustic ranging sensors into local goals and avoidance points. The influence of these points is combined through potential field techniques to accomplish obstacle avoidance control. Distant terrain characteristics are identified using information from a gray-level vision system, a color vision system, and a computer-controlled laser ranging sensor. These characteristics are used by a general planning engine to develop the desired path to a visible goal in the direction of the final goal. Progress to the final goal consists of a succession of movements from one distant but visible intermediate goal to another. The experience from implementing this autonomous vehicle has indicated the need for an integrated set of debugging tools which make the faults in subsystem hardware and software more distinguishable.
地面监视机器人(GSR):一种设计用于穿越未知地形的自动车辆
自1980年秋季以来,地面监视机器人(GSR)项目一直在持续进行,当时已经实现了自动驾驶车辆的设计和一定程度的实施。整车设计分为传感器、控制和规划子系统。开发了一个分布式黑板方案,该方案提供了这些子系统协调的机制。车辆位置和方向由车辆姿态和导航传感器子系统提供。通过将视觉和声测距传感器的信息融合到局部目标和避障点,实现了避障能力。通过势场技术将这些点的影响结合起来实现避障控制。使用来自灰度视觉系统、彩色视觉系统和计算机控制的激光测距传感器的信息来识别远处的地形特征。一般规划引擎使用这些特征,在最终目标的方向上开发到可见目标的期望路径。实现最终目标的过程包括从一个遥远但可见的中间目标到另一个中间目标的一系列动作。实现这种自动驾驶汽车的经验表明,需要一套集成的调试工具,使子系统硬件和软件中的故障更容易区分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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