Adaptive control of manipulators using uncalibrated joint-torque sensing
Why this work is in the frame
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Bibliographic record
Abstract
The application of joint-torque sensory feedback (JTF) in robot control has been proposed in the past that, unlike the model-based controllers, does not require the dynamic model of the robot links. JTF, however, assumes precise measurement of joint torque and accurate friction model of the joints. This paper presents an adaptive JTF control algorithm that does not rely on these assumptions. First, the robot dynamics with JTF is presented in a standard form with a minimum number of parameters, where the inertia matrix appears symmetric and positive definite. Second, an adaptive JTF control law is developed that requires only incorporation of uncalibrated joint-torque signals, i.e., the gains and offsets of multiple sensors are unknown. Also, all physical parameters of the joints including inertia of the rotors, link twist angles, and friction parameters are assumed to be unknown to the controller. The stability analysis of the control system is presented. Experimental results demonstrating the tracking performance of the proposed adaptive JTF controller are presented.
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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