Precision Control of Robots with Harmonic Drives
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
Aimed at achieving ultra-high precision control performance for high-end applications of robots equipped with harmonic drives, an adaptive joint torque controller developed previously is extended to all the joints of seven degrees of freedom (DOF) robot manipulator using four different types of harmonic drives. The developed adaptive joint torque controller uses additional sensing including the joint and motor positions and the joint torque, and adaptively compensates the large friction associated with harmonic drives, while incorporating the dynamics of flexspline. With guaranteed L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> /L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">infin</sub> stability and asymptotic stability, the adaptive joint torque controller allows any motion controller to be employed. Experimental results using the developed adaptive joint torque controller incorporating a motion controller based on the virtual decomposition control demonstrate precision trajectory tracking control of a 7-DOF robot at both moderate and ultra-low speeds. The precision control with encoder-resolution accuracy at an ultra-low joint speed of 0.001 (rad/s) characterizes the effectiveness of the friction compensation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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