Motion planning for redundant manipulators in uncertain environments based on tactile feedback

Abstract

The exploitation of new fields of application in addition to traditional industrial production for robot manipulators (e.g. agriculture, human areas) requires extensions to the sensor as well as to the planning capabilities. Motion planning solely based on visual information performs poorly in cluttered environments since contacts with obstacles might be inevitable and thus a distinction between hard and soft objects has to be made. In our contribution we present a novel intrinsic tactile sensing module mounted on a multipurpose 9 DOF agricultural manipulator. With its innovative sensor arrangement we consider it to be a low-cost, easily manageable and efficient solution with a reasonable abstraction layer in comparison to complex torque sensing or tactile skins. The sensor provides information about the resulting force and torque. In the second part of our paper, the tactile information is used for minimizing contact forces while pursuing the end-effector tasks as long as reasonable. Hence, we present robust and efficient extensions to Resolved Motion Rate Control for real-time application. We introduce a general formulation providing control inputs in task-space, joint-space and nullspace. Thus, we design a suitable controller by feedback linearization and feed-forward terms. Results from real-world experiments show the potential of our approach. A discussion of the different control schemes completes the paper.