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In this paper, we present a novel approach in combining visual and inertial measurements in non-static environments for first order characterization of the metric motion of non-static objects in the scene. Our approach leverages online estimated ego motion states and uses a novel inertial-optical flow (IOF) measurement analysis to identify moving objects and to characterize them in their angular and...
In this paper, we describe a novel method using only optical flow from a single camera and inertial information to quickly initialize, deploy, and autonomously stabilize an inherently unstable aerial vehicle. Our approach requires a minimal number of tracked features in only two consecutive frames and inertial readings eliminating the need of long feature tracks or local maps and rendering it inherently...
We address obstacle avoidance for outdoor flight of micro air vehicles. The highly textured nature of outdoor scenes enables camera-based perception, which will scale to very small size, weight, and power with very wide, two-axis field of regard. In this paper, we use forward-looking stereo cameras for obstacle detection and a downward-looking camera as an input to state estimation. For obstacle representation,...
Safe navigation through corridors plays a major role in the autonomous use of Micro Aerial Vehicles (MAVs) in indoor environments. In this paper, we present an approach for wall collision avoidance using a depth map based on optical flow from on board camera images. An omnidirectional fisheye camera is used as a primary sensor, while IMU data is needed for compensating rotational effects of the optical...
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