Workspace Modeling: Visualization and Pose Estimation of Teleoperated Construction Equipment from Point Clouds

Abstract

In order to teleoperate excavators remotely, human operators need accurate information of the robot workspace to carry out manipulation tasks accurately and efficiently. Current visualization methods only allow for limited depth perception and situational awareness for the human operator, leading to high cognitive load when operating the robot in confined spaces or cluttered environments. This research proposes an advanced 3D workspace modeling method for remotely operated construction equipment where the environment is captured in realtime by laser scanning. A real-time 3D workspace state, which contains information such as the pose of end effectors, pose of salient objects, and distances between them, is used to provide feedback to the remote operator concerning the progress of manipulation tasks. The proposed method was validated at a mock urban disaster site where two excavators were teleoperated to pick up and move various debris. A 3D workspace model was constructed by laser scanning which was able to estimate the positions of the excavator and target assets within 0.1 - 0.2m accuracy.