With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …

We propose a framework for planning in unknown dynamic environments with probabilistic
safety guarantees using conformal prediction. Particularly, we design a model predictive …

This paper proposes an algorithm for motion planning among dynamic agents using
adaptive conformal prediction. We consider a deterministic control system and use trajectory …

Challenges related to automated driving are no longer focused on just the construction of
such automated vehicles (AVs) but also on assuring the safety of operation. Recent …

Safety is crucial for autonomous drones to operate close to humans. Besides avoiding
unwanted or harmful contact, people should also perceive the drone as safe. Existing safe …

Robots such as autonomous vehicles and assistive manipulators are increasingly operating
in dynamic environ-ments and close physical proximity to people. In such scenarios, the …

Optimal and safety-critical control are fundamental problems for stochastic systems, and are
widely considered in real-world scenarios such as robotic manipulation and autonomous …

For robots navigating in dynamic environments, exploiting and understanding uncertain
human motion prediction is key to generate efficient, safe and legible actions. The robot may …

Designing human motion predictors which preserve safety while maintaining robot efficiency
is an increasingly important challenge for robots operating in close physical proximity to …

There are few technologies that hold as much promise in achieving safe, accessible, and
convenient transportation as autonomous vehicles. However, as recent years have …