An FPGA-Based Embedded System for Terrain Recognition Using Inertial Measurement Units

Terrains Recognition (TR) using Inertial Measurement Units has received special attention in recent years due to the widespread availability of wearable devices. In this research, we suggested a hardware implementation of a Terrains Recognition system on a Xilinx FPGA platform. The solution employs a lone IMU sensor positioned on the shank and employs an MLP neural network classifier for the categorization of five terrains (Walking, Stair Descent/Ascent, Ramp Descent/Ascent). The hardware architecture of the suggested system underwent optimization through the utilization of parallelism optimization methods such as Unroll, Pipeline and Memory partition. This approach led to a significant improvement in performance, with faster processing speeds.