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Coverage of an inaccessible or challenging region with potential health and safety hazards, such as in a volcanic region, is difficult yet crucial from scientific and meteorological perspectives. Areas contained within the region often provide valuable information of varying importance. We present an algorithm to optimally cover a volcanic region in Hawai`i with an unmanned aerial vehicle (UAV). The target region is assigned with a nonuniform coverage importance score distribution. For a specified battery capacity of the UAV, the optimization problem seeks the path that maximizes the total coverage area and the accumulated importance score while penalizing the revisiting of the same area. Trajectories are generated offline for the UAV based on the available power and coverage information map. The optimal trajectory minimizes the unspent battery power while enforcing that the UAV returns to its starting location. This multi-objective optimization problem is solved by using sequential quadratic programming. The details of the competitive optimization problem are discussed along with the analysis and simulation results to demonstrate the applicability of the proposed algorithm.
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Emergency Landing Trajectory Optimization for Fixed-Wing UAV under Engine Failure
With the growing popularity of autonomous unmanned aerial vehicles (UAVs), the improvement of safety for UAV operations has become increasingly important. In this paper, a landing trajectory optimization scheme is proposed to generate reference landing trajectories for a fixed-wing UAV with accidental engine failure. For a specific landing objective, two types of landing trajectory optimization algorithms are investigated: i) trajectory optimization algorithm with nonlinear UAV dynamics, and ii) trajectory optimization algorithm with linearized UAV dynamics. An initialization procedure that generates an initial guess is introduced to accelerate the convergence of the optimization algorithms. The effectiveness of the proposed scheme is verified in a high-fidelity UAV simulation environment, where the optimized landing trajectories are tracked by a UAV equipped with an L1 adaptive altitude controller in both the offline and online modes.
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- Award ID(s):
- 1739732
- PAR ID:
- 10099241
- Date Published:
- Journal Name:
- AIAA SciTech Forum, San Diego, CA
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.2514/6.2019-0959
