The problem of planning for a robot that operates in environments containing a large
number of objects, taking actions to move itself through the world as well as to change the …

The objective of this work is to augment the basic abilities of a robot by learning to use
sensorimotor primitives to solve complex long-horizon manipulation problems. This requires …

Effective planning of long-horizon deformable object manipulation requires suitable
abstractions at both the spatial and temporal levels. Previous methods typically either focus …

Deformable object manipulation (DOM) for robots has a wide range of applications in
various fields such as industrial, service and health care sectors. However, compared to …

We present the first platform-independent evaluation method for task and motion planning
(TAMP). Previously point, various problems have been used to test individual planners for …

Objects rarely sit in isolation in human environments. As such, we'd like our robots to reason
about how multiple objects relate to one another and how those relations may change as the …

The objective of this work is to augment the basic abilities of a robot by learning to use new
sensorimotor primitives to enable the solution of complex long-horizon problems. Solving …

We present a framework for solving long-horizon planning problems involving manipulation
of rigid objects that operates directly from a point-cloud observation. Our method plans in the …

Multi-step forceful manipulation tasks, such as opening a push-and-twist childproof bottle,
require a robot to make various planning choices that are substantially impacted by the …

We present a framework for learning to guide geometric task-and-motion planning (g-tamp).
g-tamp is a subclass of task-and-motion planning in which the goal is to move multiple …