This thesis considers the problem of sensor-based motion planning for a three-dimensional robot arm manipulator operating among unknown obstacles. The attractiveness of such systems lies in their ability to operate in a complex, perhaps even time-varying, unstructured environment. When every point of the robot body is subject to potential collision, the corresponding planning system must include these four basic components: sensor hardware; real-time signal/sensory data processing hardware/software; a component for local step planning; and finally, a subsystem for global planning. The developed methodology and experimental prototype represents, to our knowledge, the first attempt of a system that guarantees collision-free motion for the whole body of a complex piece of machinery. The necessary on-line input information is generated in the system by a proximity sensitive skin that covers the whole body of the arm and consists of an array of discrete active infrared sensors that detect obstacles by processing reflected light. The sensor data then undergoes low level processing via a step planning procedure, which converts sensor information into local normals at the contact points in the configuration space of the robot. Based on the current collection of local normals, the real-time global motion planning algorithm generates preferable directions of motion around obstacles, so as to guarantee reaching the target position if it is reachable. Experimental results from testing the developed system are also presented.
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