Vision-Based Landing of Light Weight Unmanned Helicopters on a Smart Landing Platform

Authors:
Mohammad H. Mahoor;R. Godzdanker;K. Dalamagkidis;K. P. Valavanis
Affiliations:
Unmanned Systems Laboratory Electrical and Computer Engineering, University of Denver, Denver, USA 80208;Unmanned Systems Laboratory Electrical and Computer Engineering, University of Denver, Denver, USA 80208;Unmanned Systems Laboratory Electrical and Computer Engineering, University of Denver, Denver, USA 80208;Unmanned Systems Laboratory Electrical and Computer Engineering, University of Denver, Denver, USA 80208
Venue:
Journal of Intelligent and Robotic Systems
Year:
2011

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Abstract

This paper presents a simple and efficient solution to vision guided autonomous landing of a light-weight (ISLANDS--Intelligent Self-Leveling and Nodal Docking System. The advantage of ISLANDS is that it may allow the helicopter upon docking to recharge its batteries or refuel, thus, indirectly increasing endurance and flight range. In order for the helicopter to dock with ISLANDS, an on-board `vision module' coupled with the helicopter attitude controller is developed. This `vision module' detects the location and orientation of ISLANDS and feeds back information to the helicopter attitude controller, which commands the helicopter to descent onto the landing platform at a desired orientation and speed. The Scale Invariant Feature Transform (SIFT) is used for automatic detection of the landing platform based on images captured by a single camera mounted on the helicopter. The detected SIFT features are used to estimate the 3-D orientation of the platform relative to the helicopter using Homography and RANSAC techniques. The focus of this paper is on the vision-guided landing technique in a predefined orientation and not on controller details, which may be found in Shim et al. (1998).