The uncertainty and dynamic of home environment present great challenges to the task
planning of service robots. The nature of the home environment is highly unstructured, with a …

A core capability of robots is to reason about multiple objects under uncertainty. Partially
Observable Markov Decision Processes (POMDPs) provide a means of reasoning under …

In this article, we present a task and motion planning method for retrieving a target object
from clutter using a robotic manipulator. We consider dense and cluttered environments …

This paper presents planning algorithms for a robotic manipulator with a fixed base in order
to grasp a target object in cluttered environments. We consider a configuration of objects in a …

Robots operating in households must find objects on shelves, under tables, and in
cupboards. In such environments, it is crucial to search efficiently at 3D scale while coping …

Decision-making is the key for autonomous systems to achieve real intelligence and
autonomy. This paper presents an integrated probabilistic decision framework for a robot to …

We consider the problem of rearranging objects in a cluttered and confined space using a
robotic manipulator. The goal is to retrieve a target object from the clutter where the target is …

Object manipulation planning in clutter suffers from perception uncertainties due to
occlusion, as well as action constraints required by collision avoidance. Partially observable …

Future collaborative robots must be capable of finding objects. As such a fundamental skill,
we expect object search to eventually become an off-the-shelf capability for any robot …

Service robots performing tasks in human environments constantly face changes due to the
dynamic of the environments. Such robots need to reason about their surrounding for a …