Novel Design of a Precision Planter for a Robotic Assistant Farmer
Bibliographic record
Abstract
Farming consumes considerable energy, natural resources and intensive human labor. Robotic assisted farmer can make farming activities more precise and more efficient; particularly it may remedy shortage of farmers in the future. A planter is a mechanism which performs precision seeding. Design of a planter in the optimum manner that needs minimum draft force when attached to a mobile robot, was the main objective of this work. A planter was developed, fabricated and tested in the course of a research project. The main motivation for this research is the fact that a mobile robot, is an electric powered vehicle with limited power and pulling force. Thus, a customized planter with a customized connection mechanism should be designed that can be pulled by mobile robot. The developed planter should have the same efficiency as the existing planters in seeding. To study the interaction between soil engagement tool (disc coulter) and soil, experiments were performed in the Linear Soil Bin. Different parameters of the disc coulter were changed and the draft force, vertical force and side force were measured. The results of the experiments were used to find the optimum parameters of the disc that caused minimum draft force. A novel planter was designed and fabricated; it was attached to a mobile robot, and field tested. Tests performed in outdoor and indoor settings showed satisfactory results. Draft force developed on the planter was close to analytical value and performance of the planter in other aspects was as expected.
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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 | 0.000 | 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) | 0.000 | 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".