Application of triune parallel‐serial robot system for full‐mission tank training
Bibliographic record
Abstract
Purpose The purpose of this paper is to build a seven‐degrees of freedom (DOF) parallel‐serial robot system which has the advantage of mechanical novelty and simplicity compared with the existing platforms, and to share the experience of converting a popular motion base to an industrial robot for use in full‐mission tank training processes of three armored arms. Design/methodology/approach By studying the concept of the robot system, a novel parallel‐serial robot with seven DOF driven by electrical servo motors is built. And the transmission modules and Hooke joints are explored and designed in detail. Then the inverse kinematics based on coupling compensation and time‐jerk synthetic optimization methods for trajectory planning of the simulator are presented and further discussed in order to satisfy the requirements of high stability and perfect performance. In advance, the feasibility and applicability of this triune parallel‐serial robot system are verified. Findings A prototyped test shows that the performance of the system is of a satisfaction with real‐time tracking any trajectories given by the visual system smoothly. Finally, the characteristics of the robot system are realized and verified by experiments and an industrial application. Practical implications The triune full‐mission tank training simulator developed in this paper has been used in the military industry and it has a great potential application. Originality/value This successful usage of the novel and simple parallel robot system in the military industry expands the range of its applications in real‐life task more operators training. And the proposal methods of inverse kinematics based on coupling compensation and trajectory planning enhanced the theoretical research of the parallel robot.
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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 | 0.002 | 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 | 0.001 | 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".