Bimanual Manipulation Workspace Analysis of Humanoid Robots with Object Specific Coupling Constraints
Bibliographic record
Abstract
In this work, a bimanual manipulation workspace analysis for humanoid robots is developed. This analysis con-siders manipulability and whole-body stability for a workspace where constraints exist between the hands of the humanoid for varying hand positions and object grasps. With this goal in mind, a combined manipulability-stability metric based on the volume of the manipulability ellipsoid and the distance of the capture point from the edge of the support polygon is proposed. This metric is visualized in a variety of workspace scenarios including those where the humanoid's center of mass is moving at a certain velocity and where it is grasping and carrying objects of different masses and shapes. With a focus on tightly coupled bimanual manipulation of varying symmetry, objects studied include boxes, a broom and a rolling pin. A general workspace and a box manipulation workspace are visualized for both the REEM-C and TALOS humanoids showing differences in the generated workspace volumes due to the varying topologies of the humanoids. These visualizations aim to provide insights into how manipulability and whole-body stability are affected by bimanual manipulation scenarios and to inform complex manipulation applications in areas such as control and cost-based planning.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".