Toward a dynamic analysis of bipedal robots inspired by human leg muscles
Bibliographic record
Abstract
A walking bipedal robot by adding passive springs like mono and biarticular muscles which correspond to rectus femoris (RF), biceps femoris (BF), gastrocnemius (GAS) and tibialis anterior (TA) in human legs has been modeled in this paper. The stability of human-like leg walking can be achieved by adding these passive springs in the leg mechanism of bipedal robot. On the other hand, using these springs may inflict a fatigue during walking due to the additional work that can provide to the joints. The main objective of this paper is to analyze the total work of the robot during walking by proposing four cases of the preload of the springs at the equilibrium position. It’s found from this study that the case that has the most energy saving and ensure the comfortable walking to the robot is when the two muscles (GAS) and (TA) are not preloaded to support the total weight at the equilibrium position.
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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) | 0.002 | 0.000 |
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.
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".