Distributed Multirobot Path Planning in Unknown Maps Using Petri Net Models
| Autor: | Marius Kloetzer, Cristian Mahulea, Eduardo Montijano |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Multirobot systems Bayes estimator Optimization problem True quantified Boolean formula Computer science 020208 electrical & electronic engineering 02 engineering and technology Petri net Computer Science::Robotics 020901 industrial engineering & automation Control and Systems Engineering Iterated function 0202 electrical engineering electronic engineering information engineering Robot Motion planning |
| Zdroj: | IFAC-PapersOnLine. 53:2063-2068 |
| ISSN: | 2405-8963 |
| DOI: | 10.1016/j.ifacol.2020.12.2521 |
| Popis: | This paper considers the path planning problem in multirobot systems with an unknown environment. The robots’ mission is given as a Boolean formula on the final states. We assume that the robots have partial knowledge of the environment and they are able to estimate the environment using a recursive Bayes estimator. Furthermore, they communicate between them if they are at a distance smaller than a given threshold in order to improve their own estimation. Each robot will solve an optimization problem based on the Petri net model of the environment and it will move accordingly. We provide an algorithm to be iterated by each robot and we evaluate the results by simulation. |
| Databáze: | OpenAIRE |
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