ROOct 23, 2020

Kinodynamic Planning for an Energy-Efficient Autonomous Ornithopter

arXiv:2010.12273v1
Originality Incremental advance
AI Analysis

This addresses the need for long flight endurance and hovering capabilities in ornithopters for practical UAV applications, representing an incremental advance as it adapts existing planning methods to a less-explored vehicle type.

The paper tackles the problem of planning energy-efficient trajectories for autonomous ornithopters, a type of flapping-wing UAV, by proposing an algorithm that combines gliding and flapping maneuvers to minimize energy consumption, showing best performance in computational experiments compared to a recent alternative.

This paper presents a novel algorithm to plan energy-efficient trajectories for autonomous ornithopters. In general, trajectory optimization is quite a relevant problem for practical applications with \emph{Unmanned Aerial Vehicles} (UAVs). Even though the problem has been well studied for fixed and rotatory-wing vehicles, there are far fewer works exploring it for flapping-wing UAVs like ornithopters. These are of interest for many applications where long flight endurance, but also hovering capabilities are required. We propose an efficient approach to plan ornithopter trajectories that minimize energy consumption by combining gliding and flapping maneuvers. Our algorithm builds a tree of dynamically feasible trajectories and applies heuristic search for efficient online planning, using reference curves to guide the search and prune states. We present computational experiments to analyze and tune key parameters, as well as a comparison against a recent alternative probabilistic planning, showing best performance. Finally, we demonstrate how our algorithm can be used for planning perching maneuvers online.

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