Fuzzy Control of a Log Carrying Robot on Tree-Filled Steep-Sloping Terrains
Bibliographic record
Abstract
Abstract A modular robotic system and its fuzzy logic based controller are proposed for use in logging operations in forest environments with steep slopes. The Log-Carrying Robot (LCR) concept is composed of two modular wheeled robotic agents with individual wheel steering that connect to the ends of a log to a form a centrally controlled robot. A fuzzy controller specifies the desired direction of travel using four factors: the presence of obstacles, boundaries limiting the robot’s travel space, the heading of the goal position relative to the robot, and the slope of the terrain. The capabilities of the proposed controller are demonstrated in simulation using a rectangular robot with four individually actuated and steered wheels. Results indicate that the controller successfully steers the robot towards the goal position while avoiding obstacles using only eleven fuzzy rules. Additionally, the simple rules are shown to be effective at automatically compensating for sloped terrain by avoiding direct travel down hills, as well as adapting for various robot lengths.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".