Robot-Mediated Asymmetric Connection Between Humans Can Improve Performance Without Increasing Effort

Abstract

Whether working together to move a table or supporting a child learning to ride a bike, physically connected individuals exchange haptic information to improve motor performance. However, this improvement occurs at the cost of additional effort for the more skilled partner. OBJECTIVE: Here, we hypothesize that an asymmetric connection, consisting of a stiffer link to the less skilled partner and a more compliant link to the more skilled partner, could improve task performance without additional effort in collaborative tasks. METHODS: Through computational modelling, we first tested this hypothesis on simulated human dyads tracking a common target. Then we experimentally validated the approach on a three degree-of-freedom tracking task using two commercial robots as individual interfaces. RESULTS: The simulation and experimental results confirm that using an asymmetric connection stiffness can improve joint performance without requiring additional effort from either partner compared to their solo effort. CONCLUSION: This suggests that the training of motor skills with a proficient partner may be enhanced through the use of robot-mediated asymmetric haptic connections. SIGNIFICANCE: This approach may benefit joint tasks between individuals with clearly different motor abilities, such as a violin teacher demonstrating bowing techniques or a physical therapist assisting a patient during rehabilitation.