Shape and Nonrigid Motion Estimation Through Physics-Based Synthesis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape, motion, and inertial parameter estimation of space objects using teams of cooperative vision sensors
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Future space applications will require robotic systems to assemble, inspect, and maintain large space structures in orbit. For effective planning and control, robots will need to know the deformation and vibration of the structures with which they interact. This paper presents a method for estimating the shape, motion, and dynamic model parameters of a vibrating space structure using range imaging sensors. The method assumes that the mode shapes are approximately known a priori. An unscented Kalman filter exploits a mechanics-based dynamic model to extract the modal frequencies and damping as well as the modal coefficients and their time rate of change. Both asynchronous-capture (raster-scanning) and synchronous-capture sensors are treated. Theoretical development and experimental results using emulated space hardware are presented.