Visual predictive control of spiral motion

Mcfadyen, Aaron, Corke, Peter, & Mejias, Luis (2014) Visual predictive control of spiral motion. IEEE Transactions on Robotics, 30(6), pp. 1441-1454.

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This paper deals with constrained image-based visual servoing of circular and conical spiral motion about an unknown object approximating a single image point feature. Effective visual control of such trajectories has many applications for small unmanned aerial vehicles, including surveillance and inspection, forced landing (homing), and collision avoidance. A spherical camera model is used to derive a novel visual-predictive controller (VPC) using stability-based design methods for general nonlinear model-predictive control. In particular, a quasi-infinite horizon visual-predictive control scheme is derived. A terminal region, which is used as a constraint in the controller structure, can be used to guide appropriate reference image features for spiral tracking with respect to nominal stability and feasibility. Robustness properties are also discussed with respect to parameter uncertainty and additive noise. A comparison with competing visual-predictive control schemes is made, and some experimental results using a small quad rotor platform are given.

Impact and interest:

6 citations in Scopus
6 citations in Web of Science®
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78 since deposited on 19 Nov 2014
6 in the past twelve months

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ID Code: 78794
Item Type: Journal Article
Refereed: Yes
Additional Information: Published online: 06 November 2014
Keywords: Nonlinear model-predictive control (NMPC) spirals, Stability, Visual servoing
DOI: 10.1109/TRO.2014.2361425
ISSN: 1552-3098
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600)
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Current > Research Centres > ARC Centre of Excellence for Robotic Vision
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 IEEE
Copyright Statement: Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Deposited On: 19 Nov 2014 02:13
Last Modified: 23 Jun 2017 08:01

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