Planning to Perceive: Exploiting Mobility for Robust Object Detection
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Roy_Planning to perceive.pdf
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3.77 MB
Format
Adobe PDF
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Author(s)
Velez, Javier J.
Hemann, Garrett A.
Huang, Albert S.
Posner, Ingmar
Roy, Nicholas
Date Issued
2011
Journal
Proceedings of the Twenty-First International Conference on Automated Planning and Scheduling
Publisher
AAAI Publications
Citation
Velez, Javier; Hemann, Garrett; Huang, Albert S.; Posner, Ingmar; Roy, Nicholas. ""Twenty-First International Conference on Automated Planning and Scheduling
Version
Author's final manuscript
Abstract
Consider the task of a mobile robot autonomously navigating through an environment while detecting and mapping objects of interest using a noisy object detector. The robot must reach its destination in a timely manner, but is rewarded for correctly detecting recognizable objects to be added to the map, and penalized for false alarms. However, detector performance typically varies with vantage point, so the robot benefits from planning trajectories which maximize the efficacy of the recognition system. This work describes an online, any-time planning framework enabling the active exploration of possible detections provided by an off-the-shelf object detector. We present a probabilistic approach where vantage points are identified which provide a more informative view of a potential object. The agent then weighs the benefit of increasing its confidence against the cost of taking a detour to reach each identified vantage point. The system is demonstrated to significantly improve detection and trajectory length in both simulated and real robot experiments.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
http://aaai.org/ocs/index.php/ICAPS/ICAPS11/paper/view/2707
