Loading...
Please wait, while we are loading the content...
Similar Documents
Discrete Analysis of Obstacle Clustering by Distributed Autonomous Robots
| Content Provider | Semantic Scholar |
|---|---|
| Author | Sueoka, Yuichiro Ishikawa, Masato Kita, Takuto Sugimoto, Yasuhiro Osuka, Koichi |
| Copyright Year | 2013 |
| Abstract | In this paper, we discuss some phenomena of obstacle clustering by distributed autonomous robots, in the light of space-discretization (or cellular automata) approach. This work was motivated by Swiss Robots which collect scattered obstacles into some clusters without any global information nor intelligent concentrated controller. In order to evaluate these phenomena from quantitative and statistical points of view, we propose an analysis platform using discretized state space, i.e., a hexagonal cellular space where the robots’ direction and velocity are discretized as well. We then introduce two types of local rule, Sense & Avoid rule (which resembles the Swiss Robot’s action) and Push & Turn rule and compare the results focusing on size of resulting clusters, transient/steadystate behaviors and density of obstacles and robots. |
| Starting Page | 193 |
| Ending Page | 201 |
| Page Count | 9 |
| File Format | PDF HTM / HTML |
| DOI | 10.5687/iscie.26.193 |
| Volume Number | 26 |
| Alternate Webpage(s) | https://www.jstage.jst.go.jp/article/iscie/26/6/26_193/_pdf |
| Alternate Webpage(s) | https://doi.org/10.5687/iscie.26.193 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
