Name
Abstract | ||
|---|---|---|
In this overview paper, we present the work of the Goal-Oriented Long-Lived Systems Lab on multi-robot systems. We address multi-robot systems from a decision-making under uncertainty perspective, proposing approaches that explicitly reason about the inherent uncertainty of action execution, and how such stochasticity affects multi-robot coordination. To develop effective decision-making approaches, we take a special focus on (i) temporal uncertainty, in particular of action execution; (ii) the ability to provide rich guarantees of performance, both at a local (robot) level and at a global (team) level; and (iii) scaling up to systems with real-world impact. We summarise several pieces of work and highlight how they address the challenges above, and also hint at future research directions. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.3233/AIC-220118 | AI COMMUNICATIONS |
Keywords | DocType | Volume |
Multi-robot systems, decision-making under uncertainty, Markov models, formal methods, asynchronous execution | Journal | 35 |
Issue | ISSN | Citations |
4 | 0921-7126 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bruno Lacerda | 1 | 0 | 0.34 |
| Anna Gautier | 2 | 0 | 0.34 |
| Alex Rutherford | 3 | 0 | 0.34 |
| Alex Stephens | 4 | 0 | 0.34 |
| Charlie Street | 5 | 0 | 1.69 |
| Nick Hawes | 6 | 321 | 34.18 |