Title :
Prediction Servoing to catch escaping fish using neural network
Author :
Minami, Mamoru ; Yoshida, Toshiaki
Author_Institution :
Grad. Sch. of Eng., Univ. of Fukui, Fukui
Abstract :
This paper presents a method to predict a fish motion by neural network (N.N.) with on-line learning when a robot is pursuing fish-catching by a net at hand through hand-eye robot visual servoing. We have learned by previous experiments that fish is much smarter than a robot controlled by visual servoing whose escaping strategy is to make a steady state distance error between the net at robotpsilas hand and the fish. To overcome the fishpsilas escaping strategy we propose prediction servoing utilizing estimated future fish position by on-line adjusting N.N.. The effectiveness have been proven through visual servoing and fish catching experiments.
Keywords :
learning (artificial intelligence); motion estimation; neural nets; position control; predictive control; robot vision; servomechanisms; escaping fish; fish catching experiments; fish motion prediction; fish position estimation; hand-eye robot visual servoing; neural network; online learning; prediction servoing; Brightness; Control systems; Intelligent robots; Marine animals; Neural networks; Robot kinematics; Shape; Steady-state; Trajectory; Visual servoing;
Conference_Titel :
Advanced Intelligent Mechatronics, 2008. AIM 2008. IEEE/ASME International Conference on
Conference_Location :
Xian
Print_ISBN :
978-1-4244-2494-8
Electronic_ISBN :
978-1-4244-2495-5
DOI :
10.1109/AIM.2008.4601837