5 accepted papers
Trajectory optimisation methods for robotic motion planning often require the use of first order derivatives of the dynamics of the system with respect to the states and controls of the system. Particularly when multi-contact dynamics are present, these derivatives are often numerically approximated…
Planning for deformable object manipulation has been a challenge for a long time in robotics due to its high computational cost. In this work, we propose to reduce this cost by reducing the number of pick points on a deformable object in the action space. We do this by identifying a small number of…
We present a predictive system for non-prehensile, physics-based motion planning in clutter with a human-in-the-loop. Recent shared-autonomous systems present motion planning performance improvements when high-level reasoning is provided by a human. Humans are usually good at quickly identifying hig…
We propose a human-operator guided planning approach to pushing-based manipulation in clutter. Most recent approaches to manipulation in clutter employs randomized planning. The problem, however, remains a challenging one where the planning times are still in the order of tens of seconds or minutes,…
We are interested in the problem where a number of robots, in parallel, are trying to solve reaching through clutter problems in a simulated warehouse setting. In such a setting, we investigate the performance increase that can be achieved by using a human-in-the-loop providing guidance to robot pla