Towards Comparison and Real Time Implementation of Path Planning Methods for 2R Planar Manipulator with Obstacles Avoidance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The main requirement of parametric path planning techniques in robot manipulators is to create continuous, smooth, and easy-to-modify path such as to move the end-effector from start point to destination point. To meet these requirements, the rational Bezier and NURBS algorithms have been proposed for path planning of 2R manipulator in environment with known and static obstacles. In this study, a comparison in terms of path length and time consumption of algorithm has been conducted to show the superior of one method to another. Based on numerical simulation, it has been shown that the rational Bezier algorithm generates shorter path and takes less time to complete the path planning task as compared to NURBS method. In addition, this study presented the design of real-time set-up based on Arduino UNO microcontroller and micro-stepping actuators. It has been shown that the experimental results could successfully verify the numerical results for both proposed path planning methods for different configuration of obstacles.
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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 | 0.001 | 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 it