VIBI: Assistive vision-based interface for robot manipulation
Why this work is in the frame
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Bibliographic record
Abstract
Upper-body disabled people can benefit from the use of robot-arms to perform every day tasks. However, the adoption of this kind of technology has been limited by the complexity of robot manipulation tasks and the difficulty in controlling a multiple-DOF arm using a joystick or a similar device. Motivated by this need, we present an assistive vision-based interface for robot manipulation. Our proposal is to replace the direct joystick motor control interface present in a commercial wheelchair mounted assistive robotic manipulator with a human-robot interface based on visual selection. The scene in front of the robot is shown on a screen, and the user can then select an object with our novel grasping interface. We develop computer vision and motion control methods that drive the robot to that object. Our aim is not to replace user control, but instead augment user capabilities through our system with different levels of semi-autonomy, while leaving the user with a sense that he/she is in control of the task. Two disabled pilot users, were involved at different stages of our research. The first pilot user during the interface design along with rehab experts. The second performed user studies along with an 8 subject control group to evaluate our interface. Our system reduces robot instruction from a 6-DOF task in continuous space to either a 2-DOF pointing task or a discrete selection task among objects detected by computer vision.
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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