Spring assisted modular and reconfigurable robot: Design, analysis and control
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
This paper presents an innovative spring assisted modular and reconfigurable robot (MRR) design and control framework, which is developed based on a synergetic integration of robot control with a brake and an embedded spring at each modular joint. By activating the brake, static balancing can be established, allowing reinforced delicate operation in the neighborhood of a balanced configuration such as door opening, as well as spring assisted lift of heavy payload. The developed spring assisted MRR can improve the payload to weight ratio of the conventional robot manipulators without introducing sophisticated mechanisms. A distributed control method has been proposed to facilitate control of the spring assisted MRR. The developed control algorithm does not rely on a prior dynamic models and can suppress uncertainties introduced by module reconfigurations as well as uncertainties due to sensor inaccuracies and noises. With the developed controller, control parameters need not to be adjusted when adding modules to or removing modules from an MRR, or changing its configurations. Prototype modules have been developed, and the experimental results have confirmed the effectiveness of the proposed design and control.
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