Title :
INS-based identification of quay-crane spreader yaw
Author :
Louda, M.A. ; Rye, D.C. ; Dissanayake, M.W.M.G. ; Durrant-Whyte, H.F.
Author_Institution :
Australian Centre for Field Robotics, Sydney Univ., NSW, Australia
Abstract :
A crucial problem in crane control is to identify exactly the position and orientation of the load in space. This paper describes a new non-contact method for determining the crane load location by means of an inertial navigation system (INS) and a Kalman filter. The Kalman filter estimates the spreader position, which is not observed by the INS. Experiments were conducted on a 1/15th geometric scale model of a quay-crane. The work has potential application in the development of integrated estimation and control systems for full-scale quay-cranes
Keywords :
Kalman filters; cranes; dynamics; inertial navigation; parameter estimation; Kalman filter; Stewart platform; dynamics; identification; inertial navigation system; load location; quay-crane; spreader yaw; Containers; Cranes; Geometry; Motion control; NIST; Orbital robotics; Robotics and automation; Solid modeling; Winches; Wire;
Conference_Titel :
Robotics and Automation, 1998. Proceedings. 1998 IEEE International Conference on
Conference_Location :
Leuven
Print_ISBN :
0-7803-4300-X
DOI :
10.1109/ROBOT.1998.680949
