9 accepted papers
Policy learning often encounters difficulties in long-horizon tasks. Subgoal-conditioned policies address long-horizon problems by decomposing them into manageable segments, but they usually struggle with identifying informative subgoals. To address this limitation, we propose PDS (planning with dua…
The automation of warehouse operations is crucial for improving productivity and reducing human exposure to hazardous environments. One operation frequently performed in warehouses is bin-packing where items need to be placed into containers, either for delivery to a customer, or for temporary stora…
Robot teleoperation plays a crucial role in collecting data for large-scale imitation learning. Inferring operator's hand pose is crucial for vision-based teleoperation, and current solutions either rely on additional neural network training or hardware to infer the operator's wrist pose. To our kno…
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 address the manipulation task of retrieving a target object from a cluttered shelf. When the target object is hidden, the robot must search through the clutter for retrieving it. Solving this task requires reasoning over the likely locations of the target object. It also requires physics reasonin…
Humans, in comparison to robots, are remarkably adept at reaching for objects in cluttered environments. The best existing robot planners are based on random sampling of configuration space- which becomes excessively high-dimensional with large number of objects. Consequently, most planners often fa…
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,…
Physics-based manipulation in clutter involves complex interaction between multiple objects. In this paper, we consider the problem of learning, from interaction in a physics simulator, manipulation skills to solve this multi-step sequential decision making problem in the real world. Our approach ha…
This work presents a soft hand capable of robustly grasping and identifying objects based on internal state measurements. A highly compliant hand allows for intrinsic robustness to grasping uncertainty, but the specific configuration of the hand and object is not known, leaving undetermined if a gra…