We present a motion planning algorithm to compute collision-free and smooth trajectories for
high-degree-of-freedom (high-DOF) robots interacting with humans in a shared workspace …

As drones and autonomous cars become more widespread, it is becoming increasingly
important that robots can operate safely under realistic conditions. The noisy information fed …

We would like robots to be able to safely navigate at high speed, efficiently use local 3D
information, and robustly plan motions that consider pose uncertainty of measurements in a …

This paper presents a tool for addressing a key component in many algorithms for planning
robot trajectories under uncertainty: evaluation of the safety of a robot whose actions are …

We present a novel approach to perform probabilistic collision detection between a high-
DOF robot and imperfect obstacle representations in dynamic and uncertain environments …

We present new algorithms to perform fast probabilistic collision queries between convex as
well as non-convex objects. Our approach is applicable to general shapes, where one or …

Path planning in an uncertain environment is a key enabler of true vehicle autonomy. Over
the past two decades, numerous approaches have been developed to account for errors in …

We present an efficient algorithm to compute tight upper bounds of collision probability
between two objects with positional uncertainties, whose error distributions are represented …

An autonomous mobile robot may encounter adversarial environments in which an attacker
tries to influence its decisions. Through physical or software-level attacks, some of the …

The goal of autonomous driving is to increase safety, benefit and comfort for all road users.
Above all, the area of risk perception is of central importance in preventing critical situations …