Odometria visual por fluxo óptico integrada a um sistema de localização multi-sensor aplicado a veículos de mineração

Abstract

This work presents a method for estimating odometry for vehicles in mining environments, where GNSS-based localization systems may experience failures or signal degradation. To mitigate these faults, the proposed method uses visual odometry from a camera directed towards the ground. Captured images are used to calculate the optical flow, which describes the movement of visual information in a sequence of images. This movement is combined with data from an IMU to determine the camera’s movement (Visual-Inertial Odometry). The optical flow is calculated using Gunnar Farneback’s GPU processing method to compute the camera motion accurately and efficiently. An analysis of four localization implementations is conducted: (1) Wheel Odometry, (2) Visual-Inertial Odometry, (3) fusion of Wheel Odometry and IMU using Extended Kalman Filter (EKF), and (4) fusion using EKF of Visual-Inertial Odometry, Wheel Odometry, and IMU. Results obtained in the simulation illustrate that the proposed multi-sensor localization system can be effectively used to assist in the localization of mining vehicles in field tasks.