Motion Planning for Safe Landing of a Human-Piloted Parafoil

TL;DR

This paper develops a motion planning algorithm for safe parafoil landings, demonstrating that computer-generated trajectories can outperform human pilots in safety and efficiency, with potential to improve pilot training.

Contribution

It adapts the SST motion planner for parafoil landing trajectories, comparing its performance with human pilots and highlighting its advantages for training and safety.

Findings

Algorithm achieves 20-80% better cost efficiency than humans.

Generated trajectories are smoother and more gradual.

Potential for integration into pilot training simulators.

Abstract

Most skydiving accidents occur during the parafoil-piloting and landing stages and result from human lapses in judgment while piloting the parafoil. Training of novice pilots is protracted due to the lack of functional and easily accessible training simulators. Moreover, work on parafoil trajectory planning suitable for aiding human training remains limited. To bridge this gap, we study the problem of computing safe trajectories for human-piloted parafoil flight and examine how such trajectories fare against human-generated solutions. For the algorithmic part, we adapt the sampling-based motion planner Stable Sparse RRT (SST) by Li et al., to cope with the problem constraints while minimizing the bank angle (control effort) as a proxy for safety. We then compare the computer-generated solutions with data from human-generated parafoil flight, where the algorithm offers a relative cost improvement of 20\%-80\% over the performance of the human pilot. We observe that human pilots tend to, first, close the horizontal distance to the landing area, and then address the vertical gap by spiraling down to the suitable altitude for starting a landing maneuver. The algorithm considered here makes smoother and more gradual descents, arriving at the landing area at the precise altitude necessary for the final approach while maintaining safety constraints. Overall, the study demonstrates the potential of computer-generated guidelines, rather than traditional rules of thumb, which can be integrated into future simulators to train pilots for safer and more cost-effective flights.