Kinodynamic Planning for an Energy-Efficient Autonomous Ornithopter
| Autor: | Ernesto Sanchez-Laulhe, Jesús Capitán, Anibal Ollero, Fabio Rodríguez, José Miguel Díaz-Báñez |
|---|---|
| Přispěvatelé: | Universidad de Sevilla. Departamento de Matemática Aplicada II (ETSI) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology Mathematical optimization General Computer Science Computer science Trayectory optimization ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology nonlinear dynamics Computer Science - Robotics 020901 industrial engineering & automation ornithopter 0202 electrical engineering electronic engineering information engineering Ornithopter General Engineering Probabilistic logic Trajectory optimization Energy consumption motion planning Tree (data structure) Kinodynamic planning Nonlinear dynamics Key (cryptography) Flapping 020201 artificial intelligence & image processing Motion planning Robotics (cs.RO) Efficient energy use |
| Zdroj: | Computers & Industrial Engineering |
| Popis: | Article number 107814 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 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 applica- tions 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 maneu- vers. Our algorithm builds a tree of dynamically feasible trajectories and it applies heuristic search for efficient online planning, using reference curves to guide the search and prune states. We present computational ex- periments to analyze and tune the key parameters, as well as a comparison against a recent alternative proba- bilistic planner, showing best performance. Finally, we demonstrate how our algorithm can be used for planning perching maneuvers online Horizonte 2020 734922 Ministerio de Economía y Competitividad de España MTM2016-76272-R AEI Horizonte 2020 734922 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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