Weight-aware robot motion planning for lift-to-pass action
Oskar Palinko, Alessandra Sciutti, Francesco Rea, Giulio Sandini · 2014
Passing an object between two humans is a very natural and seamless operation, mainly thanks to non-verbal cues which facilitate the process. Just from action observation, humans can easily anticipate where and when a passing movement will end and how heavy the transported object is. But how could this natural understanding be ported to non-human agents? We introduce a simple robotic architecture to enable the iCub humanoid robot to visually recognize the weight of an object and select a lift-to-pass motion which implicitly communicates such information to the action partner. In this work we mainly focus on the building and training of the procedural memory module needed to store the association between the mass of an object and its visual appearance, and we propose how such a model can be used to successively select communicative lifting motions.