We consider the problem of planning optimally in potentially concurrent probabilistic domains: actions have probabilistic effects and may execute in parallel under certain conditi...
Abstract— This paper presents a geometry-based, multilayered synergistic approach to solve motion planning problems for mobile robots involving temporal goals. The temporal goals...
Consider the task of a mobile robot autonomously navigating through an environment while detecting and mapping objects of interest using a noisy object detector. The robot must re...
Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...
Hanna Kurniawati, Yanzhu Du, David Hsu, Wee Sun Le...
This paper presents a navigation framework which enables multiple mobile robots to attain individual goals, coordinate their actions and work safely and reliably in a highly dynam...
Kai Oliver Arras, Roland Philippsen, Nicola Tomati...