Evaluation of Visual Inertial Navigation System for Autonomous Robot Tours on Campus

Autonomous mobile robot navigation is a challenging area of research due to various physical, hardware, and software issues. In this research, an autonomous robot system has been developed, which incorporates a visual inertial navigation system (VINS) with the goal that the robot could conduct automated university campus tours. Mapping and state estimation rely on the accuracy acquired from fusing the data from the cameras and inertial measurement units (IMU). The fusion of these two sensors makes VINS systems more accurate and robust. We created a custom stereo inertial system and performed extensive evaluation to mitigate calibration issues such as noise and bias for accurate state estimation. The custom sensor infrastructure can be mounted on any mobile system. Furthermore, we tested our evaluation methodology on two challenging benchmark datasets, namely, EuRoC and TUM to determine the precision of the state estimator. Experiments show that VINS achieved highly accurate results in terms of calibration, reprojection, and trajectory estimation.