Trajectory planning for surface following with a manipulator under RGB-D visual guidance

Abstract

This paper introduces a manipulator robot surface following algorithm using a 3D model of vehicle body panels acquired by a network of rapid but low resolution RGB-D sensors. The main objective of this work is to scan and dynamically explore regions of interest over an automotive vehicle body under visual guidance by closely following the surface curves and maintaining close proximity to the object. The work is motivated by applications in automated vehicles inspection and screening in security applications. The proposed path planning strategy is developed based on a perception-modeling-planning-action approach. Raw data rapidly captured by a calibrated network of Kinect sensors are processed to provide the required 3D surface shape of objects, normal measurements, orientation estimation, and obstacle detection. A robust motion planning method is designed that relies on this information, resulting in a safe trajectory that is planned to follow and explore the curved surfaces while avoiding collision with protruding components of the vehicle. The feasibility and effectiveness of the proposed method is validated through experimental results with a 7-DOF manipulator navigating over automotive body panels.