Motion planning is a fundamental research area in robotics. Sampling-based methods offer
an efficient solution for what is otherwise a rather challenging dilemma of path planning …

Integrating task and motion planning is becoming increasingly important due to the
recognition that a growing number of robotics applications in navigation, search-and-rescue …

This article deals with path planning of a mobile robot based on a grid map. Essential
assumption for path planning is a mobile robot with functional and reliable reactive …

The open motion planning library (OMPL) is a new library for sampling-based motion
planning, which contains implementations of many state-of-the-art planning algorithms. The …

Sampling-based algorithms are viewed as practical solutions for high-dimensional motion
planning. Recent progress has taken advantage of random geometric graph theory to show …

Dynamic environments have obstacles that unpredictably appear, disappear, or move. We
present the first sampling-based replanning algorithm that is asymptotically optimal and …

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 …

This paper addresses the driver-automation shared driving control for lane keeping and
obstacle avoidance of automated vehicles in highway traffic. The proposed shared control …

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

RRT and RRT* have become popular planning techniques, in particular for high-
dimensional systems such as wheeled robots with complex nonholonomic constraints. Their …