Physically interacting individuals estimate the partner’s goal to enhance their movements

Abstract

From a parent helping to guide their child during their first steps, to a therapist supporting a patient, physical assistance enabled by haptic interaction is a fundamental modus for improving motor abilities. However, what movement information is exchanged between partners during haptic interaction, and how this information is used to coordinate and assist others, remains unclear¹. Here, we propose a model in which haptic information, provided by touch and proprioception², enables interacting individuals to estimate the partner’s movement goal and use it to improve their own motor performance. We use an empirical physical interaction task³ to show that our model can explain human behaviours better than existing models of interaction in literature^4–8. Furthermore, we experimentally verify our model by embodying it in a robot partner and checking that it induces the same improvements in motor performance and learning in a human individual as interacting with a human partner. These results promise collaborative robots that provide human-like assistance, and suggest that movement goal exchange is the key to physical assistance.