Sensor-based roadmaps for motion planning for articulated robots in unknown environments: some experiments with an eye-in-hand system

Abstract

We present a real implemented "eye-in-hand" test-bed system for sensor-based collision-free motion planning for articulated robot arms. The system consists of a PUMA 560 with a triangulation based area-scan laser range finder (the eye) mounted on its wrist. The framework for our planning approach was presented in Yu and Gupta (1998). It is inspired by motion planning research and incrementally builds a roadmap that represents the connectivity of the free configuration space, as it senses the physical environment. We present some experimental results with our sensor-based planner running on this real test-bed. The robot is started in completely unknown and cluttered environments. Typically, the planner is able to reach (planning as it senses) the goal configuration in about 7-25 scans (depending on the scene complexity), while avoiding collisions with the obstacles throughout.