Synthesis of a complete sagittal gait cycle for a five-link biped robot
Bibliographic record
Abstract
This paper presents a method for synthesising the joint profiles for a planar five-link biped walking on flat ground. Both single support and double support phases are considered. The joint profiles have been determined based on constraint equations cast in terms of step length, step period, maximum step height and so on. A special constraint equation is developed to eliminate the destabilising effect of the impact (heel strike) occurring in the system. Other advantages of our joint profiles include system stability during the double support phase and repeatability of gait. The method of formulating compatible trajectories of the hip and swing limb is employed. We demonstrate the advantages of this method over the one of direct formulation of the joint profiles in that it not only significantly simplifies the problem by de-coupling the biped into three subsystems (a trunk and two lower limbs), but also allows the incorporation of certain constraints without drastically increasing the complexity of the constraint equations. The effectiveness of the proposed method is demonstrated using computer simulations. We believe that this research can provide a valuable tool for generating motion patterns of bipedal gait.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".