ORB-SLAM accelerated on heterogeneous parallel architectures

ORB-SLAM accelerated on heterogeneous parallel architectures

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SLAM algorithm permits the robot to cartography the desired environment while positioning it in space.It is a more efficient system and more accredited by autonomous vehicle navigation and robotic application in the ongoing research.Except san antonio spurs robe it did not adopt any complete end-to-end hardware implementation yet.Our work aims to a hardware/software optimization of an expensive computational time functional gumball bere block of monocular ORB-SLAM2.

Through this, we attempt to implement the proposed optimization in FPGA-based heterogeneous embedded architecture that shows attractive results.Toward this, we adopt a comparative study with other heterogeneous architecture including powerful embedded GPGPU (NVIDIA Tegra TX1) and high-end GPU (NVIDIA GeForce 920MX).The implementation is achieved using high-level synthesis-based OpenCL for FPGA and CUDA for NVIDIA targeted boards.