Visual servoing for autonomous landing of a multi-rotor UAS on a moving platform
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
In this paper, a method to control a small multi-rotor unmanned aerial system (UAS) while landing on a moving platform using image-based visual servoing is described. The landing scheme is based on positioning visual markers on a landing platform in the form of a detectable pattern. When the onboard camera detects the object pattern, the flight control algorithm will send visual-based servo-commands to align the multi-rotor with the targets. The main contribution is that the proposed method is less computationally expensive as it uses color-based object detection applied to a geometric pattern instead of feature tracking algorithms. This method has the advantage that it does not demand calculating the distance to the objects (depth). The proposed method was tested in simulation using a quadcopter model in V-REP (virtual robotics experimental platform) working in parallel with robot operating system (ROS). Finally, this method was validated in a series of real-time experiments with a quadcopter.
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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 | 0.000 | 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 it