4-DOF Robotic Arm Simulator for Machine Operator Training and Performance Evaluation: Engineering Design and Experimental Validation

Abstract

Robotic crane operators are essential in construction or forestry (e.g. excavator or forest harvester cranes), where their performance significantly impacts efficiency and safety. Training for crane operators relies on high-fidelity simulations to develop high skill levels. However, productivity analyses revealed large variances among machine operators, with disparities by up to 40%. Therefore, skill acquisition must be advanced through improved training methods, which are based on a deeper understanding of sensory-motor control of the crane. Typically, used training simulators provided by the original equipment manufacturers (OEMs) lack access to e.g. detailed joystick data as well as lack the possibility to modify the simulations to include real-time performance feedback. To address this limitation, a robotic crane simulator was collaboratively designed by the Leibniz Research Centre for Working Environment and Human Factors and the Chair of Computer Graphics from TU Dortmund. The simulator was evaluated within a pilot study with 36 participants who conducted 32 aiming movements with the simulated robotic crane. The results show skill improvements over time and the suitability of the simulator to analyse skill acquisition in robotic crane operations.

Keywords: Simulator Design, Robotic Crane Control, Machine Operator, Skill Acquisition

DOI: 10.54941/ahfe1005006