Title :
Vision assisted robotic tele-training
Author :
Sang, Tao ; Croft, Elizabeth ; Sameti, Mohammad
Author_Institution :
Mech. Eng., British Columbia Univ., Vancouver, BC, Canada
Abstract :
This paper presents a self-calibrated vision system for human-guided robot task-learning. The system assists robot operators in training industrial robots quickly, safely, and accurately. The system can be used in various industrial environments and requires no predetermined model of the working space. The system self-calibrates to compute the initial sensor locations and orientations. Next, the user demonstrates the tool path that is to be followed by the robot arm using a 6 DOF training medium. Finally, the system optimizes the sensor locations so that, at those locations, the sensors can provide to the operator the sufficient images for the operator to observe and perform further remote training of the robot as required.
Keywords :
calibration; image sensors; industrial manipulators; learning (artificial intelligence); robot vision; telerobotics; 6-DOF training medium; human-guided robot task-learning; industrial robot training; initial sensor locations; remote training; robot arm; self-calibrated vision system; tool path; vision assisted robotic teletraining; Cameras; Humans; Image sensors; Industrial training; Machine vision; Orbital robotics; Robot sensing systems; Robot vision systems; Sensor systems; Service robots;
Conference_Titel :
Mechatronics and Automation, 2005 IEEE International Conference
Conference_Location :
Niagara Falls, Ont., Canada
Print_ISBN :
0-7803-9044-X
DOI :
10.1109/ICMA.2005.1626739