VISUAL ODOMETRY FOR AUTONOMOUS VEHICLES.

With rapid advancements in the area of mobile robotics and industrial automation, a growing need has arisen towards accurate navigation and localization of moving objects. Camera based motion estimation is one such technique which is gaining huge popularity owing to its simplicity and use of limited resources in generating motion path. In this paper, an attempt is made to introduce this topic for covering different aspects of vision based motion estimation task.Visual odometry (VO) is the process of estimating the egomotion of an agent (e.g., vehicle, human, and robot) using only the input of a single or multiple camera attached to it. Application domains include robotics, wearable computing, augmented reality, and automotive. The advantage of VO with respect to wheel odometry is that VO is not affected by wheel slip in uneven terrain or other adverse conditions. It has been demonstrated that compared to wheel odometry, VO provides more accurate trajectory estimates, with relative position error ranging from 0.1 to 2%. This capability makes VO an interesting supplement to wheel odometry and, additionally, to other navigation systems such as global positioning system (GPS), inertial measurement units (IMUs), and laser odometry (similar to VO, laser odometry estimates the egomotion of a vehicle by scan-matching of consecutive laser scans). In GPS-denied environments, such as underwater and aerial, VO has the utmost importance.