Monocular pose and shape estimation of moving targets, for autonomous rendezvous and docking

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Abstract/Contents

Abstract
This thesis describes the design and implementation of an algorithm for tracking a moving (e.g., `tumbling') target. No a priori information about the target is assumed, and only a single camera is used. The motivation is to enable autonomous rendezvous, inspection, and docking by robots in remote environments, such as space and underwater. Tracking refers to the simultaneous estimation of both the target's 6DOF pose and 3D shape (in the form of a point cloud of recognizable features), a problem of the SLAM (`Simultaneous Localization and Mapping') and SFM (`Structure from Motion') research fields. This research extends SLAM/SFM to deal with non-communicative moving targets (rigid bodies) with unknown, arbitrary 6DOF motion and no a priori knowledge of mass properties, dynamics, shape, or appearance. Specifically, a hybrid algorithm for real-time frame-to-frame pose estimation and shape reconstruction is presented. The algorithm combines concepts from two existing approaches to pose tracking, Bayesian estimation methods and nonlinear optimization techniques, to achieve a real-time capable, feasible, smooth estimate of the relative pose between a robotic platform and a moving target. The rationale for a hybrid approach is explained, and an algorithm is presented. A specific implementation using a modified Rao-Blackwellized particle filter is described and tested. Field demonstrations were performed in conjunction with the Monterey Bay Aquarium Research Institute, using the camera-equipped Remotely Operated Vehicle (ROV) Ventana to observe, reconstruct, and track the pose of an underwater tethered target in Monterey Bay. Results are included which demonstrate the performance and viability of the hybrid approach.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2011
Issuance monographic
Language English

Creators/Contributors

Associated with Augenstein, Sean
Associated with Stanford University, Department of Aeronautics and Astronautics
Primary advisor Rock, Stephen M
Thesis advisor Rock, Stephen M
Thesis advisor Enge, Per
Thesis advisor Tomlin, Claire J, 1969-
Advisor Enge, Per
Advisor Tomlin, Claire J, 1969-

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Sean Augenstein.
Note Submitted to the Department of Aeronautics and Astronautics.
Thesis Ph.D. Stanford University 2011
Location electronic resource

Access conditions

Copyright
© 2011 by Sean Augenstein
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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