Title :
The application of a dynamic error framework to robotic assembly
Author :
Taylor, P.M. ; Halleron, I. ; Song, X.K.
Author_Institution :
Dept. of Electron. Eng., Hull Univ., UK
Abstract :
The dynamic error recovery vector framework developed by P.M. Taylor and G.E. Taylor (IEEE Proc. Int. Conf. Robotics and Automation, p.1096-100, 1985) is summarized and extended. Various operators are defined for upper-bound, lower-bound, and best-guess estimates for sensor signals given a priori estimates of error causes or effects. The Bayes theorem is then used for the backwards calculation to estimate the causes of error in a robotic workcell from the sensory information. A practical illustrative example is given to demonstrate the use of the operators
Keywords :
Bayes methods; assembling; error handling; robots; Bayes theorem; a priori estimates; best-guess estimates; dynamic error framework; error causes; lower-bound; robotic assembly; robotic workcell; sensor signals; sensory information; upper-bound; Actuators; Costs; Decision making; Error correction; Error probability; Grippers; Production; Robot sensing systems; Robotic assembly; Upper bound;
Conference_Titel :
Robotics and Automation, 1990. Proceedings., 1990 IEEE International Conference on
Conference_Location :
Cincinnati, OH
Print_ISBN :
0-8186-9061-5
DOI :
10.1109/ROBOT.1990.125967
