On Task-Specific Redundant Actuation of Spring-Assisted Modular and Reconfigurable Robot
Bibliographic record
Abstract
Modular and reconfigurable robots (MRRs) are unique and highly versatile for their self-innovation potential. Multiple working mode (MWM) on-line control adds potential by enabling each spring-assisted MRR (SA-MRR) joint module to switch independently between primary (motor-only) mode, and secondary, redundant actuation (spring-assisted) mode. In this work we proposed the spring-assisted mode as an on-board, physical innovation aid for uncertain, task-critical manipulation acts in uncontrolled environments. The spring-assisted mode is characterized by synergy of the spring and motor energy, and strengthens the SA-MRR by complementing the net actuation effort to help overcome task failure, to improve competency at ordinary tasks, and to enhance SA-MRR suitability as a tool for new tasks. Spring modules are fully reconfigurable offline through component swapping, and human-robot collaboration safety is considered. Task-specific, physical innovation with the SA-MRR was investigated by applying the spring-assisted mode directly to strenuous task segments in simulation case studies, demonstrating effectiveness of the proposed MWM approach.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".