MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Reliable and resource-aware collaborative SLAM for multi-robot search and rescue

Author(s)
Tian, Yulun.
Thumbnail
Download1119734214-MIT.pdf (8.042Mb)
Other Contributors
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Advisor
Jonathan P. How.
Terms of use
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
Collaborative simultaneous localization and mapping (CSLAM) is a core capability for many multi-robot systems operating in GPS-denied environments. Motivated by the application of forest search and rescue, this thesis presents two contributions that advance state-of-the-art CSLAM systems. The first part proposes a reliable loop closure procedure for the forest environment. Complex occlusions and strong perceptual aliasing often make it extremely difficult to detect previously visited areas. By leveraging stable tree features extracted from the environment, our approach significantly improves precision and recall during loop closure detection. The proposed technique is fully integrated into a centralized CSLAM system, and is extensively validated during real-world collaborative exploration missions in the forest. The second part of this thesis proposes a resource-aware framework for distributed loop closure detection in CSLAM. Detecting inter-robot loop closures is a resource-demanding process that involves exchanging observations and verifying potential matches. This poses severe challenges for mobile robots as they are frequently limited by available onboard resources. We propose a principled framework for robots to seamlessly adapt to such resource constraints while maximizing performance. Given budgets on computation and communication, our proposed method maximizes a task-oriented performance metric by selecting and verifying a budget-feasible set of potential loop closures. We show that this problem is NP-hard in general. Then, we provide simple approximation algorithms and leverage results on monotone submodular maximization to establish provable performance guarantees. The proposed framework is extensively evaluated on real and synthetic SLAM benchmarks.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2019
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (pages 67-74).
 
Date issued
2019
URI
https://hdl.handle.net/1721.1/122417
Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Publisher
Massachusetts Institute of Technology
Keywords
Aeronautics and Astronautics.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.