Experimental Test of Unmanned Ground Vehicle Delivering Goods Using RRT Path Planning Algorithm
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
This paper presents the experimental test of an unmanned ground vehicle delivering goods. Configuration and motion equations of the vehicle are illustrated, drivers for the vehicle motion control are introduced. In the presence of obstacles, the collision-free path connecting the vehicle from the start to the goal position is planned using Rapidly-exploring Random Tree (RRT) algorithm; collision detection, nodes selection, tree expansion, and path generation of the RRT are presented, the path optimization approach is discussed. To grip the goods, vehicle mechanical arms are manipulated based on the inversed kinematics, some control flow of the arms deployment for interacting with the vehicle motion control is applied. Experimental test of the vehicle delivering goods in face of static obstacles is presented; test result validates the applicability of the proposed framework.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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