COMPLIANCE CONTROL OF A LEGGED ROBOT BASED ON IMPROVED ADAPTIVE CONTROL: METHOD AND EXPERIMENTS
Why this work is in the frame
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Bibliographic record
Abstract
For the purpose of impact reduction and stable walking of a hexapod robot under different environments, a control strategy based on the improved adaptive control algorithm is proposed.According to the model of robot structure and impedance control, a fuzzy control scheme is utilized for parameters adjustment of adaptive control.With a real-time error regulator, a fast response of system can be achieved.Comparative analysis and a series of experiments for improved compliance control method are proposed in different circumstances and presence of disturbs.The results show that expected force can be tracked quickly in complex environments, as well as smaller contact shocking and body height fluctuations are obtained, which makes foot force regulating speed of the legs be more balance and decreases instability risk of the whole system.With this characteristic, foot slipping in soft terrains can be avoided.This means the proposed strategy has great benefit for the adaptability and robustness of the hexapod walking robot in complex environment.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it