A novel approach to embodiment design of a robotic system for maximum workspace
Bibliographic record
Abstract
Relevant works on the design of spherical parallel robots (SPRs) are mostly for conceptual design. The conceptual design of a SPR considers kinematic parameters and variables to describe the motion transformation between joints and the end-effector. For example, the Denavit-Hartenberg (D-H) notation with four kinematic parameters is used to represent the spatial relations of two motion axes with no consideration of the physical embodiment between the two axes. We call the design parameters involved in the conceptual design phase as conceptual design parameters (CDPs). In contrast, embodiment design concerns the specifications of links and kinematic pairs in terms of their geometrics, volumes, spatial arrangements and dynamic behaviors. Accordingly, we call the design parameters in the embodiment design phase as embodiment design parameters (EDPs). As far as a robotic design is concerned, a critical challenge of embodiment design is to sustain the workspace obtained in conceptual design based on CDPs. Actual geometries of objects might cause the interferences among physical objects in an embodied robot. In this paper, the conceptual design of a SPR is assumed to be known, the embodiment design of a SPR is focused to minimize the workspace loss caused by EDPs. We propose three principles to guide the embodiment design of the SPR, and we apply the general algorithm (GA) for interference check based on the proposed principles. A case study of the embodiment design of a SPR is provide to illustrate how the principles are used to maximize the robot workspace at the stage of embodiment design.
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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".