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

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.

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.

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.

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.

This suggests that the training of motor skills with a proficient partner may be enhanced through the use of robot-mediated asymmetric haptic connections.

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.