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Building Maps of Workspace for Autonomous Mobile Robots Using Self-Organizing Neural Networks
| Content Provider | Semantic Scholar |
|---|---|
| Author | Hori, Katsuhiro Hashimoto, Yukio Wang, Shouyu Tsuchiya, Takeshi |
| Copyright Year | 2000 |
| Abstract | This paper presents a new method of building maps of workspace for autonomous mobile robots using self-organizing neural networks. By this method, the topological maps of the workspace can be self-organized from the relative distance data between a robot and walls on the workspace only using ultrasonic distance sensors. However, when the shape of the workspace is complicated, an unsuitable map with dead nodes or dead links may be generated. In this paper, we consider the cause of the problem, and we propose a new building maps algorithm which consists of two learning stages. |
| Starting Page | 181 |
| Ending Page | 190 |
| Page Count | 10 |
| File Format | PDF HTM / HTML |
| DOI | 10.1007/978-1-4471-0509-1_16 |
| Alternate Webpage(s) | https://page-one.springer.com/pdf/preview/10.1007/978-1-4471-0509-1_16 |
| Alternate Webpage(s) | https://doi.org/10.1007/978-1-4471-0509-1_16 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
