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Novel Hardware Architecture of EKF-SLAM's Jacobian matrices and its FPGA Implementation

机译:EKF-SLAM的Jacobian矩阵的新硬件架构及其FPGA实现

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Simultaneous Localization and Mapping (SLAM) is a critical technique for autonomous navigation systems to build and update a map of the surrounding environment and estimate their own locations in this map. However, due to the computational complexity of SLAM algorithms, it is very difficult to achieve real time implementation on low resources and low complexity platforms. Field-Programmable Gate Array (FPGA) is an attractive real-time platform for SLAM systems as they are low power and high performance. In this work, we present a novel EKF-SLAM (Extended Kalman Filter SLAM) Jacobian matrices hardware architecture design and implementation on FPGA. We implemented the design using an FPGA Cyclone 2. The design can reach up to 112 MHz and uses 1517 logic elements, and it respect the real time requirements.
机译:同时本地化和映射(SLAM)是自主导航系统构建和更新周围环境的地图并在此地图中估算自己的位置的重要技术。 然而,由于SLAM算法的计算复杂性,很难在低资源和低复杂性平台上实现实时实现。 现场可编程门阵列(FPGA)是SLAM系统的有吸引力的实时平台,因为它们是低功率和高性能。 在这项工作中,我们提出了一部小说EKF-SLAM(扩展卡尔曼滤波器SLAM)雅各比矩阵硬件架构设计和在FPGA上实现。 我们使用FPGA Cyclone 2实施了设计。设计可以达到高达112 MHz并使用1517个逻辑元素,尊重实时要求。

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