Improving the generation of rapidly exploring randomised trees (RRTs) in large scale virtual environments using trails

Katrina Samperi, Nick Hawes

Research output: Chapter in Book/Published conference outputConference publication


Rapidly exploring randomised trees (RRTs) are a useful tool generating maps for use by agents to navigate. A disadvantage to using RRTs is the length of time required to generate the map. In large scale environments, or those with narrow corridors, the time needed to create the map can be prohibitive. This paper explores a new method for improving the generation of RRTs in large scale environments. We look at using trails as a new source of information for the agent's map building process. Trails are a set of observations of how other agents, human or AI, have navigated an environment. We evaluate RRT performance in two types of virtual environment, the first generated to cover a variety of scenarios an agent may face when building maps, the second is a set of 'real' virtual environments based in Second Life. By including trails we can improve the RRT generation step in most environments, allowing the RRT to be used to successfully plan routes using fewer points and reducing the length of the overall route.

Original languageEnglish
Title of host publicationAdvances in autonomous robotics systems
Subtitle of host publication15th Annual Conference, TAROS 2014, Birmingham, UK, September 1-3, 2014. Proceedings
EditorsMichael Mistry, Aleš Leonardis, Mark Witkowski, Chris Melhuish
Place of PublicationChem (CH)
Number of pages12
ISBN (Electronic)978-3-319-10401-0
ISBN (Print)978-3-319-10400-3
Publication statusPublished - 31 Dec 2014
Event15th Towards Autonomous Robotic Systems conference - Birmingham, United Kingdom
Duration: 1 Sept 20143 Sept 2014

Publication series

NameLecture notes in computer science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th Towards Autonomous Robotic Systems conference
Abbreviated titleTAROS 2014
Country/TerritoryUnited Kingdom


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