Force-based Haptic Input Device and Online Motion Generator: Investigating Learning Curves in Robotic Telemanipulation

Both robot-assisted surgery (RAS) and future manufacturing systems use telemanipulation setups to enable remote control by surgeons in the operating room and assembly technicians. Precision, intuitive handling, as well as short task execution times have the highest priority. In this paper, we present a novel force-sensing stick and velocity-based online motion generator for a robotic telemanipulator. This custom rigid stick with 6 degrees of freedom (DoF) force/torque (F/T) sensing capabilities is considered for telemanipulation. In a first study, 24 subjects perform three tasks which mimic relevant manipulation maneuvers for industrial assembly and RAS: (1) picking and placing objects, (2) inserting a peg into a hole, and (3) moving the end-effector precisely along a specific pathway. In a second study, three subjects repeat the tasks over a longer period of time in order to assess the learning characteristics and long-term effects on task performance and execution times. For comparison, the same tests are carried out using an off-the-shelf 3 DoF motion-based device. Our results show, that both devices lead to similar performance rates and task execution times over all trials. For the force-sensing stick, subjects report an intuitive and natural response to their force input with no perceptible latency. Conclusions of the long-term study are particularly interesting: within only a few days, task execution times for both input devices can be significantly reduced by 53-69%. The present study builds on previous works of the authors presented at the World Haptics Conference 2023 in Delft [1].