Practical Implementation of a Trajectory Planning Algorithm for an Autonomous UAV

Jean-Pierre Theron; Laurent Dala; Daniel N. Wilke; Patrick Barrier

Practical Implementation of a Trajectory Planning Algorithm for an Autonomous UAV

Jean-Pierre Theron, Laurent Dala, Daniel N. Wilke, Patrick Barrier

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Abstract

A near real-time optimal trajectory planning framework for UAVs is presented and tested in a series of low altitude obstacle avoidance planning scenarios. The framework uses the Inverse Dynamics Trajectory Optimisation approach with a quaternion point-mass aircraft dynamic model and a hybrid Differential Evolution and Sequential Quadratic Programming based Interior-Point optimisation strategy.

It was found that the new framework was able to successfully find a feasible (if not optimal) trajectory and to do so as efficiently as possible. However, it was also concluded that at this stage the framework is not yet fit to be used on a UAV, as the framework tends to take longer to plan a trajectory than it takes the UAV to fly it.

Ultimately it was concluded that with some further work, the Hybrid framework could be a viable near real-time trajectory planner for UAVs.

Original language	English
Publication status	Published - 9 Sept 2018
Event	31st Congress of the International Council of the Aeronautical Sciences - Centro de Feiras de Minas Gerais George Norman Kutova, Belo Horizonte, Brazil Duration: 9 Sept 2018 → 14 Sept 2018 https://eventos.abcm.org.br/icas2018/

Conference

Conference	31st Congress of the International Council of the Aeronautical Sciences
Abbreviated title	ICAS 2018
Country/Territory	Brazil
City	Belo Horizonte
Period	9/09/18 → 14/09/18
Internet address	https://eventos.abcm.org.br/icas2018/

Keywords

Inverse dynamics based planning
Near real-time planning
Numerical optimisation
Obstacle avoidance
Fixed-wing autonomous unmanned aerial vehicle

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abstract = "A near real-time optimal trajectory planning framework for UAVs is presented and tested in a series of low altitude obstacle avoidance planning scenarios. The framework uses the Inverse Dynamics Trajectory Optimisation approach with a quaternion point-mass aircraft dynamic model and a hybrid Differential Evolution and Sequential Quadratic Programming based Interior-Point optimisation strategy. It was found that the new framework was able to successfully find a feasible (if not optimal) trajectory and to do so as efficiently as possible. However, it was also concluded that at this stage the framework is not yet fit to be used on a UAV, as the framework tends to take longer to plan a trajectory than it takes the UAV to fly it. Ultimately it was concluded that with some further work, the Hybrid framework could be a viable near real-time trajectory planner for UAVs.",

keywords = "Inverse dynamics based planning, Near real-time planning, Numerical optimisation, Obstacle avoidance, Fixed-wing autonomous unmanned aerial vehicle",

author = "Jean-Pierre Theron and Laurent Dala and Wilke, \{Daniel N.\} and Patrick Barrier",

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T1 - Practical Implementation of a Trajectory Planning Algorithm for an Autonomous UAV

AU - Theron, Jean-Pierre

AU - Dala, Laurent

AU - Wilke, Daniel N.

AU - Barrier, Patrick

PY - 2018/9/9

Y1 - 2018/9/9

N2 - A near real-time optimal trajectory planning framework for UAVs is presented and tested in a series of low altitude obstacle avoidance planning scenarios. The framework uses the Inverse Dynamics Trajectory Optimisation approach with a quaternion point-mass aircraft dynamic model and a hybrid Differential Evolution and Sequential Quadratic Programming based Interior-Point optimisation strategy. It was found that the new framework was able to successfully find a feasible (if not optimal) trajectory and to do so as efficiently as possible. However, it was also concluded that at this stage the framework is not yet fit to be used on a UAV, as the framework tends to take longer to plan a trajectory than it takes the UAV to fly it. Ultimately it was concluded that with some further work, the Hybrid framework could be a viable near real-time trajectory planner for UAVs.

AB - A near real-time optimal trajectory planning framework for UAVs is presented and tested in a series of low altitude obstacle avoidance planning scenarios. The framework uses the Inverse Dynamics Trajectory Optimisation approach with a quaternion point-mass aircraft dynamic model and a hybrid Differential Evolution and Sequential Quadratic Programming based Interior-Point optimisation strategy. It was found that the new framework was able to successfully find a feasible (if not optimal) trajectory and to do so as efficiently as possible. However, it was also concluded that at this stage the framework is not yet fit to be used on a UAV, as the framework tends to take longer to plan a trajectory than it takes the UAV to fly it. Ultimately it was concluded that with some further work, the Hybrid framework could be a viable near real-time trajectory planner for UAVs.

KW - Inverse dynamics based planning

KW - Near real-time planning

KW - Numerical optimisation

KW - Obstacle avoidance

KW - Fixed-wing autonomous unmanned aerial vehicle

UR - https://www.scopus.com/pages/publications/85060440143

M3 - Paper

T2 - 31st Congress of the International Council of the Aeronautical Sciences

Y2 - 9 September 2018 through 14 September 2018

ER -

Practical Implementation of a Trajectory Planning Algorithm for an Autonomous UAV

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