C.C. Ho and N.H. McClamrock. Autonomous spacecraft docking using a computer vision syste!m. Proc. of the 31st CDC -- Tucson, AZ, 1992.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... estimation theory have been applied [3, 8, 9, 28, 29, 35, 52, 56, 60, 66] with rather encouraging results in traditionally difficult applications, such as autonomous vehicle navigation [18, 19, 20] visionbased tracking and servo [12, 21, 42, 44] vision based manipulation [5, 21, 42] docking [19, 37], vision based planning [14] active sensing [69] As the reliability and the performance of the algorithms improves, vision starts being acknowledged in the automatic control community as a powerful and versatile sensor to measure motion, position and structure of the environment, and the ....

C.C. Ho and N.H. McClamrock. Autonomous spacecraft docking using a computer vision syste!m. Proc. of the 31st CDC -- Tucson, AZ, 1992.

....appeared in the Proc. of the 33rd IEEE Conference on Decision and Control. Submitted to Automatica in April 1994. Updated in January 1995. 1 Only recently, however, have dynamic estimation and control techniques given encouraging results for designing automatic systems which mimic such abilities [3, 12, 13, 20, 21, 26]. If we restrict our attention to motions inside a static scene , the rigid motion constraint and the perspective projection map define a nonlinear dynamical model. Motion estimation may be formalized in terms of parameter identification and or state estimation of such a model. Traditionally, the ....

C.C. Ho and N.H. McClamrock. Autonomous spacecraft docking using a computer vision system. Proc. of the 31st CDC -- Tucson, AZ, 1992.

....the relative motion between themselves and the environment when facing everyday tasks such as walking, avoiding obstacles, grasping objects. Only recently, however, have dynamic estimation and control techniques given encouraging results for designing automatic systems which mimic such abilities [8, 19, 15]. If we restrict our attention to motions inside a static scene , the rigid motion constraint and the perspective projection map define a nonlinear dynamical model. Motion estimation may be formalized in terms of parameter identification and or state estimation of such a model. Traditionally, the ....

C.C. Ho and N.H. McClamrock. Autonomous spacecraft docking using a computer vision systm. Proc. of the 31st CDC -- Tucson, AZ, 1992.

....Vision: System Theoretic Methods and Control Applications at the 33rd IEEE Conference on Decision and Control. Submitted to Automatica. Only recently, however, have dynamic estimation and control techniques given encouraging results for designing automatic systems which mimic such abilities [3, 12, 13, 20, 21, 26]. If we restrict our attention to motions inside a static scene , the rigid motion constraint and the perspective projection map define a nonlinear dynamical model. Motion estimation may be formalized in terms of parameter identification and or state estimation of such a model. Traditionally, the ....

C.C. Ho and N.H. McClamrock. Autonomous spacecraft docking using a computer vision system. Proc. of the 31st CDC -- Tucson, AZ, 1992.

.... in the case of Gennery, partially structured environment in the case of Dickmanns) Recently, quite a few schemes that use local observers for estimating 3 D shape and or motion have appeared in the literature (see for instance Broida and Chellappa (1986, 1991) Heel (1989) Oliensis and Inigo Thomas (1992), Azarbayejani and Pentland (1995) However, none of these works addresses the issue of the observability of the models proposed. Dayawansa et al. 1994) and Ghosh et al. 1994) first addressed the problem and derived an observability test for perspective systems (linear systems with ....

....of such a model. As the hardware improves, vision begins to be acknowledged as a sensor for control systems involved, for instance, in autonomous vehicle navigation, robotic manipulation, tracking, docking, surveillance (Dickmanns and Graefe (1988a, 1988b) Hashimoto et al. 1991a, 1991b) Ho and McClamrock (1992), Blake et al. 1993) While the early involvements of vision were mostly as a low level sensor for restricted environments, more complex applications require multi level control structures that exploit visual information in a hierarchical way in order to perform low level control task (such as ....

Ho, C. and McClamrock, H. (1992). Autonomous spacecraft docking using a computer vision system. Proc.

.... estimation theory have been applied [3, 8, 9, 28, 29, 35, 52, 56, 60, 66] with rather encouraging results in traditionally difficult applications, such as autonomous vehicle navigation [18, 19, 20] vision based tracking and servo [12, 21, 42, 44] vision based manipulation [5, 21, 42] docking [19, 37], vision based planning [14] active sensing [69] As the reliability and the performance of the algorithms improves, vision starts being acknowledged in the automatic control community as a powerful and versatile sensor to measure motion, position and structure of the environment, and the ....

C.C. Ho and N.H. McClamrock. Autonomous spacecraft docking using a computer vision syste!m. Proc. of the 31st CDC -- Tucson, AZ, 1992.

.... estimation theory have been applied [1, 3, 7, 13, 15, 17, 23, 26, 29, 31] with rather encouraging results in traditionally difficult applications, such as autonomous vehicle navigation [8, 9, 10, 11] visual based tracking and servo [5, 12, 19, 20] visual based manipulation [2, 12, 19] docking [10, 18], visual based planning [6] active sensing [32] Vision in the loop raises new and interesting problems of system theoretic flavor, ranging from distributed filtering and processing of large amounts of sensory data to the analysis and control of new classes of dynamical systems. Crucial issues ....

C.C. Ho and N.H. McClamrock. Autonomous spacecraft docking using a computer vision systm. Proc. of the 31st CDC -- Tucson, AZ, 1992.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC