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Record W3019591491 · doi:10.1109/tmech.2020.2990406

Biologically Inspired Deadbeat Control of Robotic Leg Prostheses

2020· article· en· W3019591491 on OpenAlexaff
Ming Pi, Zhijun Li, Qinjian Li, Zhen Kan, Cuichao Xu, Yu Kang, Chun‐Yi Su, Chenguang Yang

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2020
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsConcordia University
FundersAnhui Provincial Department of Science and TechnologyNational Natural Science Foundation of China
KeywordsRoboticsComputer scienceProsthesisRobotTerrainArtificial intelligenceSimulation

Abstract

fetched live from OpenAlex

Recent advances in robotics technology provide great support for robotic leg prostheses to realize full biomechanical functionalities of the contralateral leg. In order to reproduce the biomechanical behaviors of the contralateral leg, this article addresses biologically inspired deadbeat control of robotic leg prostheses under different terrain conditions including level ground, stairs ascent, and descent. The proposed control method is based on the ground reactive force of the contralateral leg during walking. The trajectories of center-of-mass are encoded by the corresponding polynomial splines. Then, the control of the robotic leg prosthesis is designed by replicating the motion of the user's contralateral leg. Compared to most existing results, our approach does not require any preknowledge of the exact physical parameters. Finally, experiments are conducted to show that the prosthesis can help the user walk smoothly under various terrain conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.206
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2020
Admission routes1
Has abstractyes

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