Search:
Computing and Library Services - delivering an inspiring information environment

Abstract Augmented Lazy Theta*: Applying Graph Abstractions to Trajectory Planning with Speed-Limit Constraints

Gregory, Peter and Chrpa, Lukáš (2014) Abstract Augmented Lazy Theta*: Applying Graph Abstractions to Trajectory Planning with Speed-Limit Constraints. In: 31st Workshop of the UK Planning & Scheduling Special Interest Group (PlanSIG 2013), 29-30 January 2014, Edinburgh, UK.

[img] PDF - Accepted Version
Download (406kB)

Abstract

Trajectory planning is a generalisation of path planning in
which velocity is also taken into consideration. Considering
velocity, in the context of a real-world system such as a
robotic vehicle, means considering physical constraints such
as the speed limit constraints when steering the vehicle. One
of the recent algorithms for solving this type of planning
problem is Augmented Lazy Theta*.
In this work we introduce the trajectory planner Abstract
Augmented Lazy Theta*. This planner uses a combination
of abstraction and relaxation to reduce the search space of
Augmented Lazy Theta*. We demonstrate that Abstract Augmented
Lazy Theta* significantly improves the time performance
of Augmented Lazy Theta* whilst retaining the same
overall solution quality. Additionally, we show that Abstract
Augmented Lazy Theta* performs competitively with another
state-of-the-art trajectory planning algorithm, the RRT*
algorithm, by demonstrating significantly better

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Schools: School of Computing and Engineering
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
Related URLs:
Depositing User: Lukas Chrpa
Date Deposited: 25 Jun 2014 15:28
Last Modified: 03 Dec 2016 06:14
URI: http://eprints.hud.ac.uk/id/eprint/20863

Downloads

Downloads per month over past year

Repository Staff Only: item control page

View Item View Item

University of Huddersfield, Queensgate, Huddersfield, HD1 3DH Copyright and Disclaimer All rights reserved ©