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 …

In this paper, we address the problem of sampling-based motion planning under motion and
measurement un-certainty with probabilistic guarantees. We generalize traditional sampling …

The Trolley Problem Version of Autonomous Vehicles left right Home Publisher Home About Us
Editorial Board Submit Manuscript Contact Us IMPORTANT INFORMATION ⟱ About the …

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

Autonomous vehicles will be used without a driver. This will make them less inspected
because the driver often listens to the engine and its sounds; however, a passenger in an …

This work is dedicated to the study of how uncertainty estimation of the human motion
prediction can be embedded into constrained optimization techniques, such as Model …

Characterizing the risk of operations is a fundamental requirement in robotics, and a crucial
ingredient of safe planning. The problem is multifaceted, with multiple definitions arising in …

Crane-lift path planning (CLPP) ensures the safe and efficient installation of hefty modules in
high-rise modular integrated construction (MiC). The implementation of CLPP requires …

This paper provides an empirical evaluation, in both simulation and real scenarios, of the
social navigation problem when considering human motion prediction and its stochastic …