TY - GEN
T1 - Visual servoing considering sensing dynamics and robot dynamics
AU - Wang, Cong
AU - Lin, Chung Y.
AU - Tomizuka, Masayoshi
N1 - Funding Information:
This work was supported by FANUC Ltd.
PY - 2013
Y1 - 2013
N2 - For many desirable applications of vision guided industrial robots, real-time visual servoing is necessary but also challenging. Difficulty comes from the limited sampling rate and response time of typical machine vision systems equipped on industrial robots. These factors are addressed as the dynamics of visual sensing. In addition, robot dynamics should also be fully considered when designing the control law. Considering these aspects, this paper presents a control scheme of visual servoing. A dual-rate adaptive tracking filter is presented to compensate the visual sensing dynamics. Based on the compensated vision feedback, the techniques of multi-surface sliding control and dynamic surface control are used to formulate a two-layer control law for target tracking. System kinematics and dynamics are decoupled and dealt with by the two layers of the control law respectively. The proposed method is validated through experiments on a SCARA robot.
AB - For many desirable applications of vision guided industrial robots, real-time visual servoing is necessary but also challenging. Difficulty comes from the limited sampling rate and response time of typical machine vision systems equipped on industrial robots. These factors are addressed as the dynamics of visual sensing. In addition, robot dynamics should also be fully considered when designing the control law. Considering these aspects, this paper presents a control scheme of visual servoing. A dual-rate adaptive tracking filter is presented to compensate the visual sensing dynamics. Based on the compensated vision feedback, the techniques of multi-surface sliding control and dynamic surface control are used to formulate a two-layer control law for target tracking. System kinematics and dynamics are decoupled and dealt with by the two layers of the control law respectively. The proposed method is validated through experiments on a SCARA robot.
KW - Adaptive Kalman filter
KW - Dynamic surface control
KW - Multi-surface sliding control
KW - Tracking filter
KW - Visual sensing dynamics
KW - Visual servoing
UR - http://www.scopus.com/inward/record.url?scp=84881083116&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84881083116&partnerID=8YFLogxK
U2 - 10.3182/20130410-3-CN-2034.00027
DO - 10.3182/20130410-3-CN-2034.00027
M3 - Conference contribution
AN - SCOPUS:84881083116
SN - 9783902823311
T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)
SP - 45
EP - 52
BT - 6th IFAC Symposium on Mechatronic Systems, MECH 2013
PB - IFAC Secretariat
T2 - 6th IFAC Symposium on Mechatronic Systems, MECH 2013
Y2 - 10 April 2013 through 12 April 2013
ER -