Nonlinear visual mapping model for 3-D visual tracking with uncalibrated eye-in-hand robotic system.
A new control scheme for uncalibrated robotic visual tracking problem is proposed that compromises the computational expenses of overall system with offline modeling and online control. A nonlinear visual mapping model for the uncalibrated hand-eye coordination is first proposed with an artificial neural network implementation. An online visual tracking controller is then developed together with a real-time motion planner. To improve the system performance, the control scheme is also integrated with a feedforward controller to compensate unknown object motions. Extensive simulations and experiments demonstrate the effectiveness of the proposed control scheme.
Su
Jianbo
J
Department of Automation, Shanghai Jiaotong University, Shanghai, China. jbsu@sjtu.edu.cn
Xi
Yugeng
Y
Hanebeck
Uwe D
UD
Schmidt
G
G
D000465:Algorithms; D001185:Artificial Intelligence; D002138:Calibration; D003198:Computer Simulation; D006225:Hand; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008962:Models, Theoretical; D009068:Movement; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated; D012371:Robotics / Q000379:methods*