A Reconfigurable Visual–Inertial Odometry Accelerated Core with High Area and Energy Efficiency for Autonomous Mobile Robots

Abstract

With the wide application of autonomous mobile robots (AMRs), the visual inertial odometer (VIO) system that realizes the positioning function through the integration of a camera and inertial measurement unit (IMU) has developed rapidly, but it is still limited by the high complexity of the algorithm, the long development cycle of the dedicated accelerator, and the low power supply capacity of AMRs. This work designs a reconfigurable accelerated core that supports different VIO algorithms and has high area and energy efficiency, precision, and speed processing characteristics. Experimental results show that the loss of accuracy of the proposed accelerator is negligible on the most authoritative dataset. The on-chip memory usage of 70 KB is at least 10× smaller than the state-of-the-art works. Thus, the FPGA implementation’s hardware-resource consumption, power dissipation, and synthesis in the 28 nm CMOS outperform the previous works with the same platform.