Abstract
We propose an efficient scheme based on a swarm robotics approach for exploring unknown environments. The initial goal is to trace a map which is later used to find optimal paths. The algorithm minimizes distance and danger. The proposed scheme consists in three phases: exploration, mapping and path optimization. A cellular automata approach is used for the simulation of the fist two phases. For the exploration phase, a stigmergy approach is applied in order to allow for swarm communication in a implicit way. For the path planning phase a hybrid method is proposed. First an adapted Rapidlyexploring Random Graph algorithm is used and then a scalarized multiobjective technique is applied to find the shortest path.
| Original language | English |
|---|---|
| Pages (from-to) | 692-702 |
| Number of pages | 11 |
| Journal | International Journal of Advanced Computer Science and Applications |
| Volume | 10 |
| Issue number | 5 |
| DOIs | |
| State | Published - 2019 |
Keywords
- Cellular automata
- Path planning
- Rapidly-exploring Random Graph (RRG)
- Scalarized multiobjective optimization
- Swarm robotics
Fingerprint
Dive into the research topics of 'Swarm robotics and rapidly exploring random graph algorithms applied to environment exploration and path planning'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver