A Continuous Local Motion Planning Framework for Unmanned Vehicles in Complex Environments |
| |
Authors: | Andrew J Berry Jeremy Howitt Da-Wei Gu Ian Postlethwaite |
| |
Affiliation: | (1) QinetiQ, Cody Technology Park, Ively Rd, Farnborough, Hampshire, GU14 0LX, UK;(2) Department of Engineering, University of Leicester, Leicester, LE1 7RH, UK;(3) Northumbria University, Newcastle upon Tyne, NE1 8ST, UK |
| |
Abstract: | As the complexity of an unmanned vehicle’s operational environment increases so does the need to consider the obstacle space
continually, and this is aided by splitting the motion planning functionality into distinct global and local layers. This
paper presents a new continuous local motion planning framework, where the output and control space elements of the traditional
receding horizon control problem are separated into distinct layers. This separation reduces the complexity of the local motion
trajectory optimisation, enabling faster design and increased horizon length. The focus of this paper is on the output space
component of this framework. Bezier polynomial functions are used to describe local motion trajectories which are constrained
to vehicle performance limits and optimised to track a global trajectory. Development and testing is in simulation, targeted
at a nonlinear model of a quadrotor unmanned air vehicle. The defined framework is used to provide situation-aware tracking of a global trajectory in the presence of static and dynamic obstacles, as well as realistic turbulence and gusts.
Also demonstrated is the immediate-term decentralised deconfliction of multiple unmanned vehicles, and multiple formations of unmanned vehicles. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|