Review of visual odometry: types, approaches, challenges, and applications
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 (Fernandez and Price 2004). 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 (Gonzalez et al. 2012) . 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. Abstract Accurate localization of a vehicle is a fundamental challenge and one of the most important tasks of mobile robots. For autonomous navigation, motion tracking, and obstacle detection and avoidance, a robot must maintain knowledge of its position over time. Vision-based odometry is a robust technique utilized for this purpose. It allows a vehicle to localize itself robustly by using only a stream of images captured by a camera attached to the vehicle. This paper presents a review of state-of-the-art visual odometry (VO) and its types, approaches, applications, and challenges. VO is compared with the most common localization sensors and techniques, such as inertial navigation systems, global positioning systems, and laser sensors. Several areas for future research are also highlighted.