25 May 2016 Stereo vision-based obstacle avoidance for micro air vehicles using an egocylindrical image space representation
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Abstract
Micro air vehicles which operate autonomously at low altitude in cluttered environments require a method for onboard obstacle avoidance for safe operation. Previous methods deploy either purely reactive approaches, mapping low-level visual features directly to actuator inputs to maneuver the vehicle around the obstacle, or deliberative methods that use on-board 3-D sensors to create a 3-D, voxel-based world model, which is then used to generate collision free 3-D trajectories. In this paper, we use forward-looking stereo vision with a large horizontal and vertical field of view and project range from stereo into a novel robot-centered, cylindrical, inverse range map we call an egocylinder. With this implementation we reduce the complexity of our world representation from a 3D map to a 2.5D image-space representation, which supports very efficient motion planning and collision checking, and allows to implement configuration space expansion as an image processing function directly on the egocylinder. Deploying a fast reactive motion planner directly on the configuration space expanded egocylinder image, we demonstrate the effectiveness of this new approach experimentally in an indoor environment.
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R. Brockers, R. Brockers, A. Fragoso, A. Fragoso, L. Matthies, L. Matthies, } "Stereo vision-based obstacle avoidance for micro air vehicles using an egocylindrical image space representation", Proc. SPIE 9836, Micro- and Nanotechnology Sensors, Systems, and Applications VIII, 98361R (25 May 2016); doi: 10.1117/12.2224695; https://doi.org/10.1117/12.2224695
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