Review of visual odometry: types, approaches, challenges, and applications 论文

摘要

Accurate localization of a vehicle is a fundamental challenge in mobile robot applications. A robot must maintain knowledge of its position over time to achieve autonomous navigation. Therefore, various sensors, techniques, and systems for mobile robot positioning, such as wheel odometry, laser/ultrasonic odometry, global position system (GPS), global navigation satellite system (GNSS), inertial navigation system (INS), and visual odometry (VO), have been developed by researchers and engineers. However, each technique has its own weaknesses. Although wheel odometry is the simplest technique available for position estimation, it suffers from position drift due to wheel slippage INS is highly prone to accumulating drift, and a highly precise INS is expensive and an unviable solution for commercial purposes. Although GPS is the most common solution to localization as it can provide absolute position without error accumulation, it is only effective in places with a clear view of the sky. Moreover, it cannot be used indoors and in confined spaces The commercial GPS estimates position with errors in the order of meters. This error is considered too large for precise applications that require accuracy in centimeters, such as autonomous parking. Differential GPS and real time kinematic GPS can provide position with centimeter accuracy, but these techniques are expensive.