![]() ![]() We propose to use a linearly constrained extended Kalman filter for a stereo-based visual odometry or simultaneous localization and mapping approach. Therefore, our solution was able to mitigate the errors with negligible use of additional computing resources. The proposed method was based on a robust linearly constrained state estimation technique able to mitigate the model mismatch without estimating the model parameters. The standard method, which consists of estimating the calibration online, fails in such harsh conditions. Such mechanical stresses change the stereo pair geometry, and as a consequence, the pre-calculated epipolar geometry or any geometric-based approach is no longer valid. In real-world conditions, any optical system is subject to various mechanical stresses, caused by vibration, rough handling, collisions, or even thermal expansion. We especially focused on the context of autonomous vehicles. This work addressed the problem of miscalibration or decalibration of mobile stereo/bi-monocular camera setups. ![]()
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