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We present a system consisting of a miniature unmanned aerial vehicle (UAV) and a small carrier vehicle, in which the UAV is capable of autonomously starting from the moving ground vehicle, tracking it at a constant distance and landing on a platform on the carrier in motion. Our visual tracking approach differs from other methods by using low-cost,(More)
Global Integral Invariant Features have shown to be useful for robot localization in indoor environments. In this paper, we present a method that uses integral invariants for outdoor environments. To make the integral invariant features more distinctive for outdoor images, we split the image into a grid of subimages and calculate integral invariants for(More)
Vision-based robot localization in outdoor environments is difficult because of changing illumination conditions. Another problem is the rough and cluttered environment which makes it hard to use visual features that are not rotation invariant. A popular method that is rotation invariant and relatively robust to changing illumination is the Scale Invariant(More)
— We present the evolution of a highly-efficient system for visually detecting number signs in real-time on a mobile robot with limited computational power. The system was designed for use on a robot participating in the 2010 " SICK robot day " robotics challenge, in which the robot needed to autonomously find 10 number signs and drive to all of them in a(More)
In this paper we investigate the effectiveness of SURF features for visual terrain classification for outdoor flying robots. A quadrocopter fitted with a single camera is flown over different terrains to take images of the ground below. Each image is divided into a grid and SURF features are calculated at grid intersections. A classifier is then used to(More)
We present a follow-the-leader scenario with a system of two small low-cost quadrocopters of different types and configurations. The leader is a Parrot AR.Drone which is controlled by an iPad App utilizing the visual odometry provided by the quadrocopter and pilots it autonomously. The follower is an Asctec Hummingbird which is controlled by an onboard(More)
This paper is an annotated version of [6], explaining the proposed algorithm in more detail. In the paper we present a novel method for pose estimation for micro aerial vehicles (MAVs), which provides all six degrees of freedom (6DOF) and runs completely onboard and in real time at 60 Hz. The approach uses a distinct pattern of orange table tennis balls as(More)
In this paper, we present a geometrical localization method based on a combination of global image features. Our method represents each image by two feature vectors. The first feature vector is a Weighted Gradient Orientation Histogram (WGOH). The second feature vector is a Weighted Grid Integral Invariant (WGII) feature vector based on Integral Invariants.(More)
— In this paper, we compare three different marker based approaches for six degrees of freedom (6DOF) pose estimation, which can be used for position and attitude control of micro aerial vehicles (MAV). All methods are able to achieve real time pose estimation onboard without assistance of any external metric sensor. Since these methods can be used in(More)