PAPER DOI: Multi-robot systems, Planning under uncertainty, Long-run average optimization

technical paper

AAMAS 2020

May 11, 2020

Live on Underline

Long-Run Multi-Robot Planning Under Uncertain Task Durations

This paper presents part of the work developed so far within the scope of my PhD and suggests possible future research directions. My thesis tackles the problem of multi-robot coordination under uncertainty over the long-term. We present a preliminary approach that tackles multi-robot monitoring problems under uncertain task durations. We propose a methodology that takes advantage of a modeling formalism for robot teams: generalized stochastic Petri nets with rewards (GSPNR). A GSPNR allows for unified modeling of action selection and uncertainty on duration of action execution. At the same time, it allows for goal specification through the use of transition rewards and rewards per time unit. The proposed approach exploits the well-defined semantics provided by Markov reward automata in order to synthesize policies.


SlidesTranscript English (automatic)

Next from AAMAS 2020

technical paper

Desirable Partitions in Coalition Formation Games

AAMAS 2020

Martin Bullinger

11 May 2020

Similar lecture

technical paper

Evolutionary co-optimisation of robot morphology and control: toward a seahorse-tail inspired robotic manipulator

SEB Annual Conference 2022

Dries Marzougui

07 July 2022

Stay up to date with the latest Underline news!


  • All Lectures
  • For Librarians
  • Resource Center
  • Free Trial
Underline Science, Inc.
1216 Broadway, 2nd Floor, New York, NY 10001, USA

© 2023 Underline - All rights reserved