| Presentation | 2021-01-22 Deep Learning based Link Quality Prediction for Autonomous Mobility Robots Riichi Kudo, Kahoko Takahashi, Tomoki Murakami, Tomoaki Ogawa, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Highly advanced mobility robots are expected to be managed, monitored, or efficiently controlled by using wireless communication links. The wireless links will need to satisfy higher level requirements if they are to realize more advanced applications in future robot systems. In the mobity robot systems, the devices accurately understands self-status such as position, direction, and velocity so as to safely operate without colliding with other objects. Accurate self-status is useful not only for robot operations but also enhancing wireless link performance. This paper proposes deep-learning-based wireless link quality prediction that uses robot status and evaluates the prediction performance of the future link quality by using an implemented autonomous mobility robot in an indoor environment. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Deep learning / Link quality prediction / Autonomous mobility robot / wireless LAN |
| Paper # | IT2020-102,SIP2020-80,RCS2020-193 |
| Date of Issue | 2021-01-14 (IT, SIP, RCS) |
| Conference Information | |
| Committee | SIP / IT / RCS |
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| Conference Date | 2021/1/21(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Kazunori Hayashi(Kyoto Univ.) / Tadashi Wadayama(Nagoya Inst. of Tech.) / Eiji Okamoto(Nagoya Inst. of Tech.) |
| Vice Chair | Yukihiro Bandou(NTT) / Toshihisa Tanaka(Tokyo Univ. Agri.&Tech.) / Tetsuya Kojima(Tokyo Kosen) / Fumiaki Maehara(Waseda Univ.) / Toshihiko Nishimura(Hokkaido Univ.) / Tomoya Tandai(Toshiba) |
| Secretary | Yukihiro Bandou(Hosei Univ.) / Toshihisa Tanaka(Waseda Univ.) / Tetsuya Kojima(Yamaguchi Univ.) / Fumiaki Maehara(Saga Univ.) / Toshihiko Nishimura(Kyushu Univ.) / Tomoya Tandai(NEC) |
| Assistant | Yuichi Tanaka(Tokyo Univ. Agri.&Tech.) / Takahiro Ohta(Senshu Univ.) / Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Manabu Sakai(Mitsubishi Electric) / Masashi Iwabuchi(NTT) / Tatsuki Okuyama(NTT DOCOMO) |
| Paper Information | |
| Registration To | Technical Committee on Signal Processing / Technical Committee on Information Theory / Technical Committee on Radio Communication Systems |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Deep Learning based Link Quality Prediction for Autonomous Mobility Robots |
| Sub Title (in English) | |
| Keyword(1) | Deep learning |
| Keyword(2) | Link quality prediction |
| Keyword(3) | Autonomous mobility robot |
| Keyword(4) | wireless LAN |
| 1st Author's Name | Riichi Kudo |
| 1st Author's Affiliation | NTT(NTT) |
| 2nd Author's Name | Kahoko Takahashi |
| 2nd Author's Affiliation | NTT(NTT) |
| 3rd Author's Name | Tomoki Murakami |
| 3rd Author's Affiliation | NTT(NTT) |
| 4th Author's Name | Tomoaki Ogawa |
| 4th Author's Affiliation | NTT(NTT) |
| Date | 2021-01-22 |
| Paper # | IT2020-102,SIP2020-80,RCS2020-193 |
| Volume (vol) | vol.120 |
| Number (no) | IT-320,SIP-321,RCS-322 |
| Page | pp.pp.218-223(IT), pp.218-223(SIP), pp.218-223(RCS), |
| #Pages | 6 |
| Date of Issue | 2021-01-14 (IT, SIP, RCS) |