Safe robot operation alongside humans using spring-assisted modular and reconfigurable robot
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
Recently a novel spring-assisted modular and reconfigurable robot (SA-MRR) has been developed at our laboratory to reinforce its performance and to enable safe and dexterous operation in shared human-robot environments. Upon spring engagement at any joint position, the joint output torque becomes the sum of the actuator torque and spring torque, and the joint displacement range is mechanically limited. Restricting the manipulator's joint displacement limits individually allows the workspace to be confined selectively to a subspace of its entire or natural workspace, and creates an opportunity for a human to enter safely into the robot's natural workspace even while the robot continues to operate. Furthermore, the SA-MRR operating under spring-assistance offers functional benefits; the spring torque may counterbalance the manipulator and payload weight to avail the actuator torque fully for manipulation-an act which may simultaneously increase dexterity and decrease power consumption. The shared human-robot workspace notion as enabled by the SA-MRR is explored first in this work. Then, capabilities of a 3-DOF SA-MRR are investigated through simulations for dexterous operations and for payload handling within limited workspaces.
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