Equilibrium Point Control of a 2-DOF Manipulator
Bibliographic record
Abstract
Programmable mechanical compliance in actuation is desirable for human interaction tasks and important for producing biomimetic motion, particularly for robots designed for use in domestic settings. In this paper, the equilibrium point (EP) hypothesis is proposed and implemented as a new strategy for controlling programmable compliance. The primary objective of this work is to design and demonstrate a simple robot control strategy that can potentially be used by assistive robots to learn and execute compliant interaction tasks from human demonstrations. A 2-DOF planar manipulator activated by McKibben actuators was constructed for the purpose of demonstrating the application of the EP hypothesis on an inexpensive robotic platform, such as might be used in domestic applications. The equilibrium angle and stiffness of each of the joints on the manipulator can be independently programmed. The results presented herein show stable and satisfactory tracking behavior during free motion, interaction, and transition tasks for a robot control system inspired by the EP hypothesis and implemented with a linear proportional-integral (PI) control strategy.
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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".