3 accepted papers
In near future, robots are envisioned to work alongside humans in unstructured professional and domestic environments. In such setups, collaborative manipulation is a fundamental skill that allows manipulation of heavy loads by load sharing between agents. Grasp planning plays a pivotal role for loa…
Grasping systems that build upon meticulously planned hand postures rely on precise knowledge of object geometry, mass and frictional properties — assumptions which are often violated in practice. In this work, we propose an alternative solution to the problem of grasp acquisition in simple autonomo…
Grasp planning in multi-robot systems is usually studied in a centralized setting with all robots sharing common knowledge about the overall system. Relaxing this assumption would allow multiple mobile manipulators to cooperate even without strict and precise coordination. Moreover, most typical tas…