Improving Heuristics of Optimal Perception Planning using Visibility Maps

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Pereira, T (Author) Other; António Paulo Moreira (Author) FEUP; Veloso, M (Author) Other

Conference proceedings International

Title: 2016 International Conference on Autonomous Robot Systems and Competitions, ICARSC 2016, Bragança, Portugal, May 4-6, 2016

Pages: 150-155

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 3 Citations

Other information

Authenticus ID: P-00M-D62

DOI: 10.1109/icarsc.2016.44

Abstract (EN): In this paper we consider the problem of motion planning for perception of a target position. A robot has to move to a position from where it can sense the target, while minimizing both motion and perception costs. The problem of finding paths for robots executing perception tasks can be solved optimally using informed search. In perception path planning, the solution for the perception task considering a straight line without obstacles is used as heuristic. In this work, we propose a heuristic that can improve the search efficiency. In order to improve the node expansion using a more informed search, we use the robot Approximate Visibility Map (A-VM), which is used as a representation of the observability capability of a robot in a given environment. We show how the critical points used in A-VM provide information on the geometry of the environment, which can be used to improve the heuristic, increasing the search efficiency. The critical points allow a better estimation of the minimum motion and perception cost for targets in non-traversable regions that can only be sensed from further away. Finally, we show the contributed heuristic dominates the common heuristic (based on the euclidian distance), and present the results of the performance increase in terms of node expansion.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6