Computing position and orientation of free-flying polyhedron from 3D data

A robotic vision system for grasping a free-flying polyhedron in space has been developed using stereo vision and laser range finders. Real-time motion estimation and sensor fusion is achieved by using prior knowledge of the object. A maximum likelihood parameter estimation is developed for rotational symmetric polyhedrons, and the 3D transformations for fusing many different sensors into one coordinate frame are given. The minimization is solved using the sequential quadratic programming technique, which has proved to be a robust and efficient method. Included are simulation results performed on the hardware that will be used in the ROTEX space robot technology experiment.<<ETX>>

[1]  Klaus Landzettel,et al.  Predictive and knowledge-based telerobotic control concepts , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[2]  Jens G. Balchen,et al.  Sensor integration using state estimators , 1990 .

[3]  E D Dickmanns,et al.  GUIDING LAND VEHICLES ALONG ROADWAYS BY COMPUTER VISION , 1985 .

[4]  H. F. Durrant-White.  Consistent integration and propagation of disparate sensor observations , 1987 .

[5]  Rama Chellappa,et al.  Estimation of Object Motion Parameters from Noisy Images , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Jake K. Aggarwal,et al.  On the computation of motion from sequences of images-A review , 1988, Proc. IEEE.

[7]  Steven D. Blostein,et al.  ROBUST ALGORITHMS FOR MOTION ESTIMATION BASED ON TWO SEQUENTIAL STEREO IMAGE PAIRS. , 1985 .

[8]  G. Skofteland,et al.  Motion Estimation from Multi-Sensor Data for Tele-Robotics , 1990, Proceedings of the IEEE International Workshop on Intelligent Motion Control.

[9]  J. K. Aggarwal,et al.  Motion from a Sequence of Range Images , 1990, Proceedings of the IEEE International Workshop on Intelligent Motion Control.

[10]  Richard Szeliski.  Estimating Motion From Sparse Range Data Without Correspondence , 1988, [1988 Proceedings] Second International Conference on Computer Vision.