Material recognition CNNs and hierarchical planning for biped robot locomotion on slippery terrain

Martim Brandão, Yukitoshi Minami Shiguematsu, Kenji Hashimoto, Atsuo Takanishi

研究成果: Conference contribution

28 被引用数 (Scopus)

抄録

In this paper we tackle the problem of visually predicting surface friction for environments with diverse surfaces, and integrating this knowledge into biped robot locomotion planning. The problem is essential for autonomous robot locomotion since diverse surfaces with varying friction abound in the real world, from wood to ceramic tiles, grass or ice, which may cause difficulties or huge energy costs for robot locomotion if not considered. We propose to estimate friction and its uncertainty from visual estimation of material classes using convolutional neural networks, together with probability distribution functions of friction associated with each material. We then robustly integrate the friction predictions into a hierarchical (footstep and full-body) planning method using chance constraints, and optimize the same trajectory costs at both levels of the planning method for consistency. Our solution achieves fully autonomous perception and locomotion on slippery terrain, which considers not only friction and its uncertainty, but also collision, stability and trajectory cost. We show promising friction prediction results in real pictures of outdoor scenarios, and planning experiments on a real robot facing surfaces with different friction.

本文言語English
ホスト出版物のタイトルHumanoids 2016 - IEEE-RAS International Conference on Humanoid Robots
出版社IEEE Computer Society
ページ81-88
ページ数8
ISBN(電子版)9781509047185
DOI
出版ステータスPublished - 2016 12 30
イベント16th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2016 - Cancun, Mexico
継続期間: 2016 11 152016 11 17

出版物シリーズ

名前IEEE-RAS International Conference on Humanoid Robots
ISSN(印刷版)2164-0572
ISSN(電子版)2164-0580

Other

Other16th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2016
国/地域Mexico
CityCancun
Period16/11/1516/11/17

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ビジョンおよびパターン認識
  • ハードウェアとアーキテクチャ
  • 人間とコンピュータの相互作用
  • 電子工学および電気工学

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