Tegotae-Based Control Produces Adaptive Inter- and Intra-limb Coordination in Bipedal Walking

Dai Owaki, Shun Ya Horikiri, Jun Nishii, Akio Ishiguro

Research output: Contribution to journalArticlepeer-review

Abstract

Despite the appealing concept of central pattern generator (CPG)-based control for bipedal walking robots, there is currently no systematic methodology for designing a CPG-based controller. To remedy this oversight, we attempted to apply the Tegotae approach, a Japanese concept describing how well a perceived reaction, i.e., sensory information, matches an expectation, i.e., an intended motor command, in designing localised controllers in the CPG-based bipedal walking model. To this end, we developed a Tegotae function that quantifies the Tegotae concept. This function allowed incorporating decentralised controllers into the proposed bipedal walking model systematically. We designed a two-dimensional bipedal walking model using Tegotae functions and subsequently implemented it in simulations to validate the proposed design scheme. We found that our model can walk on both flat and uneven terrains and confirmed that the application of the Tegotae functions in all joint controllers results in excellent adaptability to environmental changes.

Original languageEnglish
Article number629595
JournalFrontiers in Neurorobotics
Volume15
DOIs
Publication statusPublished - 2021 May 12

Keywords

  • Tegotae
  • adaptability
  • bipedal walking
  • central pattern generator
  • inter- and intra-limb coordination

ASJC Scopus subject areas

  • Biomedical Engineering
  • Artificial Intelligence

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