We present Interactive Gibson Benchmark, the first comprehensive benchmark for training
and evaluating Interactive Navigation solutions. Interactive Navigation tasks are robot …

The need for combined task and motion planning in robotics is well understood. Solutions to
this problem have typically relied on special purpose, integrated implementations of task …

We describe an integrated strategy for planning, perception, state estimation and action in
complex mobile manipulation domains based on planning in the belief space of probability …

We present a new algorithm for task and motion planning (TMP) and discuss the
requirements and abstractions necessary to obtain robust solutions for TMP in general. Our …

We present a new constraint-based framework for task and motion planning (TMP). Our
approach is extensible, probabilistically complete, and offers improved performance and …

Most common navigation tasks in human environments require auxiliary arm interactions, eg
opening doors, pressing buttons and pushing obstacles away. This type of navigation tasks …

Rearranging multiple objects is a critical skill for robots so that they can effectively deal with
clutter in human spaces. This is a challenging problem as it involves combinatorially large …

Typical end-to-end formulations for learning robotic navigation involve predicting a small set
of steering command actions (eg, step forward, turn left, turn right, etc.) from images of the …

In this paper, we examine the problem of rearranging many objects on a tabletop in a
cluttered setting using overhand grasps. Efficient solutions for the problem, which capture a …

Manipulating multiple movable obstacles is a hard problem that involves searching high-
dimensional C-spaces. A milestone method for this problem was able to compute solutions …