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Co-design hardware/software of real time vision system on FPGA for obstacle detection

Ali Alhamwi 1
1 LAAS-RAP - Équipe Robotique, Action et Perception
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : Obstacle detection, localization and occupancy map reconstruction are essential abilities for a mobile robot to navigate in an environment. Solutions based on passive monocular vision such as simultaneous localization and mapping (SLAM) or optical flow (OF) require intensive computation. Systems based on these methods often rely on over-sized computation resources to meet real-time constraints. Inverse perspective mapping allows for obstacles detection at a low computational cost under the hypothesis of a flat ground observed during motion. It is thus possible to build an occupancy grid map by integrating obstacle detection over the course of the sensor. In this work we propose hardware/software system for obstacle detection, localization and 2D occupancy map reconstruction in real-time. The proposed system uses a FPGA-based design for vision and proprioceptive sensors for localization. Fusing this information allows for the construction of a simple environment model of the sensor surrounding. The resulting architecture is a low-cost, low-latency, high-throughput and low-power system.
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Ali Alhamwi. Co-design hardware/software of real time vision system on FPGA for obstacle detection. Embedded Systems. Université Paul Sabatier - Toulouse III, 2016. English. ⟨NNT : 2016TOU30342⟩. ⟨tel-01483746v2⟩

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