Power Efficient Design a Compliant Robotic Leg Based on Klann's Linkage
Bibliographic record
Abstract
This article presents the analysis and optimization of a compliant robotic leg based on Klann's linkage. This leg is specifically designed to efficiently distribute its power requirement over its complete motion cycle, avoiding large peaks in the energy drawn from the battery. The structural compliance of the leg will be shown to be able to both provide a satisfactory walking motion and a timely energy boost to help with the gait. Klann's linkage is selected here as the basic kinematic structure of the leg to demonstrate the proposed methodology, namely to combine in a single structure both a complex trajectory generation and energy storage/release. This work is first aiming at proposing a thorough kinematic analysis of that mechanism using planar screw theory. The latter will be shown to be able to efficiently provide the velocity equations of the linkage as well as its force input–output relationship and singularity conditions. In a second part of this article, the previous kinetostatic model will be used to design and optimize a compliant version of the leg optimizing the power required for the robot to move. Finally, experiments will be shown to support the proposed approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".