Abstract
This paper proposes a method for pose estimation of unknown motion target by integrating the improved iterative closest point (ICP) algorithm and the adaptive extended Kalman filter (AEKF). First, the point cloud of scene is obtained by stereo vision. Then, the target is extracted based on color and depth information. Last, the point clouds of adjacent frames are registered by the improved ICP-AEKF in closed loop configuration in order to obtain relative pose parameters between the target and stereo camera. The physical experiment is also conducted under the ZED binocular camera, which shows that the performance of the improved ICP-AEKF is much better than the traditional ICP in accuracy, convergence speed and robustness.
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