UCL  IRIS
Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at http://www.ucl.ac.uk/finance/research/post_award/post_award_contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
Path planning in partially known environments
Abstract
Many path planning algorithms assume that the environment is either perfectly known or perfectly unknown (in which case the environment is assumed to be empty). We consider the intermediate case in which partial prior information, in the form of a probabilistic occupancy cell map, is available. Using heuristics for clustering the spatial distribution of paths based on most common routes, we derive an algorithm, called the PD planner, which exploits this probabilistic information. Unlike local entropy-based planners, it can account for global effects such as the need for a robot to "Back Up" if it becomes stuck in a blind alley. The performance of the algorithm is assessed in a simulated highly damaged indoor scenario, where we show that exploiting the global impacts of uncertainty has the potential to significantly reduce both travel time and travel distance.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Author
Dept of Computer Science
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by