Bibliographic record
Abstract
ABB’s YuMi is a unique, innovative cobot but it is also one of the most challenging 7-degree-of-freedom (DOF) robot arms on the market, in terms of kinematics. Indeed, unlike some other 7-DOF robot arms with revolute joints, in YuMi, consecutive joint axes are normal to each other, but not intersecting. And despite being invented over a decade ago, there is surprisingly little information available about its kinematics. To effectively incorporate this manipulator into motion planning tasks, it is essential to have a comprehensive grasp of its arm angle and singularities. In this paper, we use the screw dependency approach with a novel combinatorial technique and Grassmann geometry of lines to identify and categorize, for the first time, the kinematic singularities of YuMi based on simple geometrical conditions. This methodology allows for a systematic and clear understanding of the robot’s singular configurations. In addition, we provide the definition of the arm angle used by ABB and a formula for the angle calculation. Then, we describe the representation singularity, and explain the algorithmic singularities that are related to the arm angle. • A new approach for analyzing the kinematic singularities of 7-DOF robot arms was proposed. • The singularities of ABB’s 7-axis YuMi were thoroughly analyzed for the first time. • The geometric conditions for each kinematic singularity were described. • A formula for the arm angle of YuMi was provided for the first time. • A comparison with the singularities of KUKA’s iiwa was presented.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".