Adaptive Robotic Contour Following from Low Accuracy RGB-D Surface Profiling and Visual Servoing

Abstract

This paper introduces an adaptive contour following method for robot manipulators that originally combines low accuracy RGB-D sensing with eye-in-hand visual servoing. The main objective is to allow for the detection and following of freely shaped 3D object contours under visual guidance that is initially provided by a fixed Kinect sensor and refined by a single eye-in-hand camera. A path planning algorithm is developed that constrains the end effector to maintain close proximity to the surface of the object while following its contour. To achieve this goal, a RGB-D sensing is used to rapidly acquire information about the 3D location and profile of an object. However, because of the low resolution and noisy information provided by such sensors, accurate contour following is achieved with an extra eye-in-hand camera that is mounted on the robot's end-effector to locally refine the contour definition and to plan an accurate trajectory for the robot., Experiments carried out with a 7-DOF manipulator and the dual sensory stage are reported to validate the reliability of the proposed contour following method.