Object motion and structure recovery for robotic vision using scanning laser range sensors

Abstract

Although many algorithms have been developed for motion estimation from range images, none are suited for use with scanning laser sensors. In this paper, the feature-based motion transformation model is restated to incorporate the nonzero pixel sampling rate of laser range cameras and a novel iterative, linear, feature-based technique for determining the 3D motion transformation of moving objects is developed using this new model. A technique is then presented which employs the motion recovered using the iterative algorithm to remove the structural distortion of the object in the range map. The performance of the motion recovery method is verified using simulated and experimental data.