Name
Abstract | ||
|---|---|---|
We consider a multi-robot variant of the mission monitoring problem. This problem arises in tasks where a robot observes the progress of another robot that is stochastically following a known trajectory, among other applications. We formulate and solve a variant where multiple tracker robots must monitor a single target robot, which is important because it enables the use of multi-robot systems to improve task performance in practice, such as in marine robotics missions. Our algorithm coordinates the behaviour of the trackers by computing optimal single-robot paths given a probabilistic representation of the other robots' paths. We employ a decentralised scheme that optimises over probability distributions of plans and has useful analytical properties. The planned trajectories collectively maximise the probability of observing the target throughout the mission with respect to probabilistic motion and observation models. We report simulation results for up to 8 robots that support our analysis and indicate that our algorithm is a feasible solution for improving the performance of mission monitoring systems. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/IROS.2018.8593663 | 2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) |
Field | DocType | ISSN |
BitTorrent tracker,Optimal stopping,Computer science,Robot kinematics,Control engineering,Probability distribution,Artificial intelligence,Probabilistic logic,Robot,Robotics,Trajectory | Conference | 2153-0858 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Graeme Best | 1 | 39 | 6.02 |
| Shoudong Huang | 2 | 755 | 62.77 |
| Robert Fitch | 3 | 323 | 38.97 |