Constrained manipulator visual servoing (CMVS): Rapid robot programming in cluttered workspaces
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 a model-free optimization framework for the visual servoing of eye-in-hand manipulators in cluttered environments. Visual feedback is used to solve for a set of feasible trajectories that bring the robot end-effector to a target object at a previously untaught location under a number of challenging constraints (i.e., whole-arm collisions, object occlusions, robot's joint limits, camera's sensing limits). A novel controller is proposed, which exploits the natural by-products of the teach-by-showing process, to help the robot navigate this non-convex space. Examining the user-demonstrated trajectories that lead up to the reference image, we use a combination of stochastic optimization techniques and classical optimization techniques to extract the relevant cost functions and constraints for servoing. We hypothesize that we can leverage the user's sensory capabilities and knowledge of the workspace to alleviate the burden of modeling system constraints explicitly. We verify this hypothesis via realistic experiments on a Barrett WAM 7-DOF manipulator equipped with a Sony XC-HR70 camera to show the comparative efficacy of this approach.
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 | 0.001 |
| Open science | 0.001 | 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