The Robotics Institute

Carnegie Mellon Robotics Institute

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

The high cost of damaging an expensive robot or injuring people or equipment in its environment make even rare failures unacceptable in many mobile robot applications. Often the objects that pose the highest risk for a mobile robot are those that were not present throughout previous successful traversals of an environment. Change detection, a closely related problem to novelty detection, is therefore of high importance to many mobile robotic applications that require a robot to operate repeatedly in the same environment. We present a novel algorithm for performing online change detection based on a previously developed robust online novelty detection system that uses a learned lower-dimensional representation of the feature space to perform measures of similarity. We then further improve this change detection system by incorporating online scene segmentation to better utilize contextual information in the environment. We validate these approaches through extensive experiments onboard a large outdoor mobile robot. Our results show that our approaches are robust to noisy sensor data and moderate registration errors and maintain their performance across diverse natural environments and conditions.

Keywords

Change Detection, Novelty Detection, Perception, Field Robotics, Segmentation, MDA

Notes

Associated Center(s) / Consortia: National Robotics Engineering Center and Field Robotics Center

Associated Lab(s) / Group(s): rCommerce

Text Reference

Bradford Neuman, Boris Sofman, Anthony (Tony) Stentz, and J. Andrew (Drew) Bagnell, "Segmentation-Based Online Change Detection for Mobile Robots," International Conference on Robotics and Automation, May, 2011.

BibTeX Reference

@inproceedings{Neuman_2011_6805,
   author = "Bradford Neuman and Boris Sofman and Anthony (Tony) Stentz and J. Andrew (Drew) Bagnell",
   title = "Segmentation-Based Online Change Detection for Mobile Robots",
   booktitle = "International Conference on Robotics and Automation",
   month = "May",
   year = "2011",
}

The Robotics Institute

Menu