Hierarchical Geometric Path-Following Control for UAV Slung Load Transport
Bibliographic record
Abstract
This paper addresses the motion control problem of a slung load system (SLS), which consists of an unmanned aerial vehicle (UAV) carrying a pendulum. The pendulum is pivoted at the UAV's center of mass through a 2-degree-of-freedom rotational joint. The other end of the pendulum carries a payload to be transported by the SLS. The control design is based on a geometric SLS model, where UAV and pendulum rotations evolve in SO(3) and S2, respectively. Hence, the control design is geometric in nature and does not adhere to the parameterization of SO(3) and S2. The objective is to control payload position and UAV heading without using timed reference trajectories. Instead, the control design stabilizes the so-called path set to control payload motion using a hierarchical control structure. Utilizing the Reduction Theorem, the paper proves that the path set is almost globally asymptotically stable. The Reduction Theorem simplifies the stability proof as no Lyapunov function is needed and allows for modularity in individual control-loop designs. Numerical simulations are presented to validate the result and show its almost global asymptotic nature.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".