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 …

Space exploration and exploitation depend on the development of on-orbit robotic
capabilities for tasks such as servicing of satellites, removing of orbital debris, or …

Abstract We introduce Habitat 2.0 (H2. 0), a simulation platform for training virtual robots in
interactive 3D environments and complex physics-enabled scenarios. We make …

Reinforcement learning (RL) techniques optimize the accumulated long-term reward of a
suitably chosen reward function. However, designing such a reward function often requires …

In this paper we present the Yale-CMU-Berkeley (YCB) Object and Model set, intended to be
used for benchmarking in robotic grasping and manipulation research. The objects in the set …

In this article, we present the Yale-Carnegie Mellon University (CMU)-Berkeley (YCB) object
and model set, intended to be used to facilitate benchmarking in robotic manipulation …

We present a new approach to motion planning using a stochastic trajectory optimization
framework. The approach relies on generating noisy trajectories to explore the space …

In this paper we present the Yale-CMU-Berkeley (YCB) Object and Model set, intended to be
used to facilitate benchmarking in robotic manipulation, prosthetic design and rehabilitation …

We present a manipulation planning framework that allows robots to plan in the presence of
constraints on end-effector pose, as well as other common constraints. The framework has …

Robotic construction assembly planning aims to find feasible assembly sequences as well
as the corresponding robot-paths and can be seen as a special case of task and motion …