Rigid body motion from range image sequences

Abstract

An algorithm is described for recovering the six degrees of freedom of motion of a vehicle from a sequence of range images of a static environment taken by a range camera rigidly attached to the vehicle. The technique utilizes a least-squares minimization of the difference between the measured rate of change of elevation at a point and the rate predicted by the so-called elevation rate constraint equation. It is assumed that most of the surface is smooth enough so that local tangent planes can be constructed, and that the motion between frames is smaller than the size of most features in the range image. This method does not depend on the determination of correspondences between isolated high-level features in the range images. The algorithm has been successfully applied to data obtained from the range imager on the Autonomous Land Vehicle (ALV). Other sensors on the ALV provide an initial approximation to the motion between frames. It was found that the outputs of the vehicle sensors themselves are not suitable for accurate motion recovery because of errors in dead reckoning resulting from such problems as wheel slippage. The sensor measurements are used only to approximately register range data. The algorithm described here then recovers the difference between the true motion and that estimated from the sensor outputs.