Mobile manipulation using tracks of a tracked mobile robot
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents the investigation on mobile manipulation of a self-reconfigurable tracked mobile robot, using its tracks for both manipulation and locomotion. It is desirable for a mobile robot to possess manipulation capability in unstructured environments, especially in the scenario which is unsuitable for human beings. However, it is not convenient for such a mobile robot to carry an onboard manipulator and perform grasping and placing operations. An alternative is to realize the manipulation potential of the existing parts and perform manipulation without attaching additional hardware. Besides the enhanced locomotion ability, a self-reconfigurable tracked mobile robot has great potential in manipulation, which may take the forms of box-pushing, cylinder-moving or lateral hitting. However, the manipulation with tracks has to be controlled properly. One challenge is to optimize the tracks' configuration so as to get the optimal contact point. Furthermore, the speed and acceleration of the mobile robot have dramatic influence on mobile manipulation with tracks. To verify the effectiveness of the proposed algorithms, experiments are conducted using a tracked mobile robot in our laboratory.
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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