Robot navigation in crowded public spaces is a complex task that requires addressing a
variety of engineering and human factors challenges. These challenges have motivated a …

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 …

We present a new large dataset of indoor human and robot navigation and interaction,
called THÖR-MAGNI, that is designed to facilitate research on social human navigation: for …

We focus on robot navigation in crowded environments. To navigate safely and efficiently
within crowds, robots need models for crowd motion prediction. Building such models is …

To comprehensively cover the uncertainty of the future, the common practice of multi-modal
human trajectory prediction is to first generate a set/distribution of candidate future …

Robots navigating in crowded areas should negotiate free space with humans rather than
fully controlling collision avoidance, as this can lead to freezing behavior. Game theory …

We focus on robot navigation in crowded environments. The challenge of predicting the
motion of a crowd around a robot makes it hard to ensure human safety and comfort. Recent …

In this paper, we focus on the problem of shrinking-horizon Model Predictive Control (MPC)
in uncertain dynamic environments. We consider controlling a deterministic autonomous …

Over the years, the separate fields of motion planning, mapping, and human trajectory
prediction have advanced considerably. However, the literature is still sparse in providing …