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Massachusetts Institute of Technology

Simultaneous Tracking, Object Registration, and Mapping (STORM)

Abstract

dc:description.abstract

An autonomous system needs to be aware of its surroundings and know where it is in its environment in order to operate robustly in unknown environments. This problem is known as Simultaneous Localization and Mapping (SLAM). SLAM techniques have been successfully implemented on systems operating in the real world. However, most SLAM approaches assume that the environment does not change during operation -- the static world assumption. When this assumption is violated (e.g. an object moves), the SLAM estimate degrades. Consequently, the static world assumption prevents robots from interacting with their environments (e.g. manipulating objects) and restricts them to navigating in static environments. Additionally, most SLAM systems generate maps composed of low-level features that lack information about objects and their locations in the scene. This representation limits the map's utility, preventing it from being used for tasks beyond navigation such as object manipulation and task planning. We present Simultaneous Tracking, Object Registration, and Mapping (STORM), a SLAM system that represents an environment as a collection of dynamic objects. STORM enables a robot to build and maintain maps of dynamic environments, use the map estimates to manipulate objects, and localize itself in the map when revisiting the environment. We demonstrate STORM's capabilities with simulation and real-world experiments and compare its performance against that of a typical SLAM approach.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kee, Vincent P
Advisor dc:contributor.advisor
  • Gian Luca Mariottini and Sertac Karaman.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • 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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/119560
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/119560

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Kee, Vincent P. Simultaneous Tracking, Object Registration, and Mapping (STORM). Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119560