Advancement of a spinal-like reach controller for multi-muscle arm movements without trajectory planning: Implementing muscle activation bias and determining the role of pre-motor gains
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Bibliographic record
Abstract
This thesis seeks to advance a spinal-like reflex controller for a two-link planar arm. This controller relies on a hand-target error signal and reaches to a target using only this error signal and the spinal circuit topology to complete realistic reach movements. The reliance on a single error signal implies a common control strategy across multiple joints, which could later be extended to additional motor platforms or limb coordination. The original spinal-like controller was able to perform robust reaching motions with and without perturbations and was able to replicate experimentally observed trajectories without pre-planning or optimization.Advancements to the original controller include the introduction of a muscle activation bias and a non-linear pre-motor gain field to map the shared reach error onto separate joints. The muscle activation bias increases the symmetric range for agonist-antagonist muscle control. This gives rise to smooth muscle activation (EMG) signals which in turn lead to smooth hand trajectories and speed profiles, especially as the hand approaches the target. The endpoint accuracy of reach movements is significantly improved by calibrating the muscle activation bias with the expected target location. This result implies system planning based on the target location but not for the reach trajectory itself. The non-linear pre-motor gain field also makes a significant contribution to reach stability: stable reaches were made at higher speeds with a non-linear gain field where reaching between the same points at higher speeds with a constant gain would lead to endpoint instability. Finally, the combined modifications to the controller significantly improved the steady state stability of the system. The arm now starts at rest, makes a reach, and the hand stops relatively close to the target at the end of the reach because of the inherent steady state behaviour of the system. These conclusions help to define the role of spinal circuitry in motor control and, by extension, to allocate remaining control functions to the cortex and higher brain centers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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