Robust egomotion estimation using ICP in inverse depth coordinates

WLD Lui, TJJ Tang, T Drummond… - 2012 IEEE International …, 2012 - ieeexplore.ieee.org
2012 IEEE International Conference on Robotics and Automation, 2012ieeexplore.ieee.org
This paper presents a 6 degrees of freedom egomotion estimation method using Iterative
Closest Point (ICP) for low cost and low accuracy range cameras such as the Microsoft
Kinect. Instead of Euclidean coordinates, the method uses inverse depth coordinates which
better conforms to the error characteristics of raw sensor data. Novel inverse depth
formulations of point-to-point and point-to-plane error metrics are derived as part of our
implementation. The implemented system runs in real time at an average of 28 frames per …
This paper presents a 6 degrees of freedom egomotion estimation method using Iterative Closest Point (ICP) for low cost and low accuracy range cameras such as the Microsoft Kinect. Instead of Euclidean coordinates, the method uses inverse depth coordinates which better conforms to the error characteristics of raw sensor data. Novel inverse depth formulations of point-to-point and point-to-plane error metrics are derived as part of our implementation. The implemented system runs in real time at an average of 28 frames per second (fps) on a standard computer. Extensive experiments were performed to evaluate different combinations of error metrics and parameters. Results show that our system is accurate and robust across a variety of motion trajectories. The point-to-plane error metric was found to be the best at coping with large inter-frame motion while remaining accurate and maintaining real time performance.
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