Safe motion planning for robotic systems in dynamic environments is nontrivial in the
presence of uncertain obstacles, where estimation of obstacle uncertainties is crucial in …

Safety is a core challenge of autonomous robot motion planning, especially in the presence
of dynamic and uncertain obstacles. Many recent results use learning and deep learning …

Safe navigation around obstacles is a fundamental challenge for highly dynamic robots. The
state-of-the-art approach for adapting simple reference path planners to complex robot …

Motion planning plays a significant role in enabling advances of autonomous vehicles in
saving lives and improving traffic efficiency. In a predictive motionplanning strategy, the ego …

Uncertain dynamic obstacles, such as pedestrians or vehicles, pose a major challenge for
optimal robot navigation with safety guarantees. Previous work on optimal motion planning …

This paper considers the problem of autonomous robot navigation in unknown environments
with moving obstacles. We propose a new method that systematically puts planning, motion …

Mobile robots increasingly interact with unstructured, uncertain environments while
performing useful tasks. To navigate their surroundings these robots rely on models of their …

A robot autonomy stack usually consists of several modules that enable it to perceive the
environment and decide how to interact with it to achieve a desired task. At the heart of this …

This paper presents a real-time path planning algorithm that guarantees probabilistic
feasibility for autonomous robots with uncertain dynamics operating amidst one or more …

This thesis is concerned with trajectory generation for robots in dynamic environments with
relatively narrow passages. In particular, this thesis aims at developing motion planning …