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ON TEMPORAL AND SPATIAL CALIBRATION FOR
HIGH ACCURACY VISUAL-INERTIAL MOTION ESTIMATION
by
Jonathan Scott Kelly
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(COMPUTER SCIENCE)
December 2011
Copyright 2011 Jonathan Scott Kelly
Object Description
| Title | On temporal and spatial calibration for high accuracy visual-inertial motion estimation |
| Author | Kelly, Jonathan Scott |
| Author email | jonathan.kelly@gmail.com;jonathan.kelly@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Computer Science |
| School | Viterbi School of Engineering |
| Date defended/completed | 2010-08-25 |
| Date submitted | 2011-12-12 |
| Date approved | 2011-12-12 |
| Restricted until | 2011-12-12 |
| Date published | 2011-12-12 |
| Advisor (committee chair) | Sukhatme, Gaurav S. |
| Advisor (committee member) |
Schaal, Stefan Matthies, Larry H. Newton, Paul |
| Abstract | The majority of future autonomous robots will be mobile, and will need to navigate reliably in unknown and dynamic environments. Visual and inertial sensors, together, are able to supply accurate motion estimates and are well-suited for use in many robot navigation tasks. Beyond egomotion estimation, fusing high-rate inertial sensing with monocular vision enables other capabilities, such as independent motion segmentation and tracking, moving obstacle detection and ranging, and dense metric 3D mapping, all from a mobile platform. ❧ A fundamental requirement in any multisensor system is precision calibration. To ensure optimal performance, the sensors must be properly calibrated, both intrinsically and relative to one another. In a visual-inertial system, the camera and the inertial measurement unit (IMU) require both temporal and spatial calibration --- estimates of the relative timing of measurements from each sensor and of the six degrees-of-freedom transform between the sensors are needed. Obtaining this calibration information is typically difficult and time-consuming, however. Ideally, we would like to build power-on-and-go robots that are able to operate for long periods without the usual requisite manual sensor (re-) calibration. ❧ This dissertation describes work on combining visual and inertial sensing for navigation applications, with an emphasis on the ability to temporally and spatially (self-) calibrate a camera and an IMU. Self-calibration refers to the use of data exclusively from the sensors themselves to improve estimates of related system parameters. ❧ The primary difficultly in temporal calibration is that the correspondences between measurements from the different sensors are initially unknown, and hence the relative time delay between the data streams cannot be computed directly. We instead formulate temporal calibration as a registration problem, and introduce an algorithm called Time Delay Iterative Closest Point (TD-ICP) as a novel solution. The algorithm operates by aligning curves in a three-dimensional orientation space, and incorporates in a principled way the uncertainty in the camera and IMU measurements. ❧ We then develop a sequential filtering approach for calibration of the spatial transform between the sensors. We estimate the transform parameters using a sigma point Kalman filter (SPKF). Our formulation rests on a differential geometric analysis of the observability of the camera-IMU system; this analysis shows for the first time that the IMU pose and velocity, the gyroscope and accelerometer biases, the gravity vector, the metric scene structure, and the sensor-to-sensor transform, can be recovered from camera and IMU measurements alone. While calibrating the transform we simultaneously localize the IMU and build a map of the surroundings. No additional hardware or prior knowledge about the environment in which a robot is operating is necessary. ❧ Results from extensive simulation studies and from laboratory experiments are presented, which demonstrate accurate camera-IMU temporal and spatial calibration. Further, our results indicate that calibration substantially improves motion estimates, and that the local scene structure can be recovered with high fidelity. ❧ Together, these contributions represent a step towards developing fully autonomous robotic systems that are capable of long-term operation without the need for manual calibration. |
| Keyword | calibration; inertial navigation; simultaneous localization and mapping; SLAM; sensor fusion; monocular vision; observability |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | Kelly, Jonathan Scott |
| Access conditions | The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@usc.edu |
| Archival file | uscthesesreloadpub_Volume6/etd-KellyJonat-454.pdf |
Description
| Title | Page 1 |
| Contributing entity | University of Southern California |
| Full text | ON TEMPORAL AND SPATIAL CALIBRATION FOR HIGH ACCURACY VISUAL-INERTIAL MOTION ESTIMATION by Jonathan Scott Kelly A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (COMPUTER SCIENCE) December 2011 Copyright 2011 Jonathan Scott Kelly |
