Research on Rolling Parallel Robot With Hydraulic Driven Antiparallelogram Chain
Bibliographic record
Abstract
Aiming at acquiring large deformation capability, powerful strength output, rapid response, and flexible locomotion, a novel three degrees-of-freedoms (DOFs) rolling parallel robot is proposed. This robot adopts the parallel mechanism, and its structure can guarantee the stiffness of the robot. The large capability of deformation can be obtained by taking advantage of the antiparallelogram mechanism with an enlarging mechanism of extension ratio. Hydraulic actuation is used for the telescopic input, which can increase the locomotion flexibility and the strength output of the robot. Rolling motion of the robot can be reached through planning and controlling the relations between the center of mass (CM) of the robot and the supporting region. The mechanical construction and configuration of the robot are described, the rolling gaits are planned, and the optimal locomotion law is given. Based on the law, the kinematic model of the robot is created. The kinematic model is validated by the given numerical example. The locomotion feasibility of two locomotion periods is analyzed. A set of experimental tests on the hydraulic system and the robotic system are performed. Results of four rolling experiments verify the reliability of the experimental system and the rapid response capability and also verify the validity and feasibility of the theoretical analysis and the rolling locomotion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".