Decentralised fault tolerance and fault detection of modular and reconfigurable robots with joint torque sensing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A decentralised approach to fault tolerant control and fault detection is proposed for modular and reconfigurable robots with joint torque sensing. The proposed fault tolerant control scheme is independent of fault detection, avoiding the chances of delay being introduced by the detection scheme on the fault tolerant control algorithm. Based on a unique joint by joint control approach, the proposed fault tolerant controller for each module neither requires motion states of any other modules, nor the link dynamics. The addition or removal of modules does not affect the control of other joint modules. Uncalibrated torque sensor signals are utilized and actuator performance degradation is considered. Faults are detected and corrective measures are taken at the module level. An observer-based fault detection algorithm is proposed by using a residual generated from the joint velocity estimation and measured joint velocity. Simulation and experimental results have confirmed the effectiveness of the proposed fault tolerant control and fault detection schemes.
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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