World modeling for a sensor-in-hand robot arm

In many robotics applications, e.g. telerobotics under long time delay, building a geometric world model from multisensory data is a crucial requirement. Using a sensor-in-hand configuration to generate a model referenced to the robot base, imposes specific problems. Moving the sensor frame on an arbitrary path over and around an unknown object generates a completely unordered 'data cloud'. A surface reconstruction algorithm, which is based on Kohonen's self-organizing feature maps is used to process this data cloud and to generate a useful surface description. This surface can be used for object recognition and pose estimation using algorithms which were developed in the field of range image understanding.

[1]  Katsushi Ikeuchi Recognition of 3-D Objects Using the Extended Gaussian Image , 1981, IJCAI.

[2]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Demetri Terzopoulos,et al.  Constraints on Deformable Models: Recovering 3D Shape and Nonrigid Motion , 1988, Artif. Intell..

[4]  Takeo Kanade,et al.  Real-time 3-D pose estimation using a high-speed range sensor , 1993, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[5]  Gerd Hirzinger,et al.  ROTEX-the first remotely controlled robot in space , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[6]  Helge Ritter,et al.  Parametrized Self-Organizing Maps , 1993 .

[7]  Gerd Hirzinger,et al.  A self-organizing algorithm for multisensory surface reconstruction , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[8]  David A. Smith Using Enhanced Spherical Images for Object Representation , 1979 .

[9]  Teuvo Kohonen,et al.  Self-organization and associative memory: 3rd edition , 1989 .

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

[11]  Demetri Terzopoulos,et al.  Multilevel computational processes for visual surface reconstruction , 1983, Comput. Vis. Graph. Image Process..