TY - GEN
T1 - A Model Predictive Control Approach for Vision-Based Object Grasping via Mobile Manipulator
AU - Logothetis, Michalis
AU - Karras, George C.
AU - Heshmati-Alamdari, Shahab
AU - Vlantis, Panagiotis
AU - Kyriakopoulos, Kostas J.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/27
Y1 - 2018/12/27
N2 - This paper presents the design of a vision-based object grasping and motion control architecture for a mobile manipulator system. The optimal grasping areas of the object are estimated using the partial point cloud acquired from an onboard RGB-D sensor system. The reach-to-grasp motion of the mobile manipulator is handled via a Nonlinear Model Predictive Control scheme. The controller is formulated accordingly in order to allow the system to operate in a constrained workspace with static obstacles. The goal of the proposed scheme is to guide the robot's end-effector towards the optimal grasping regions with guaranteed input and state constraints such as occlusion and obstacle avoidance, workspace boundaries and field of view constraints. The performance of the proposed strategy is experimentally verified using an 8 Degrees of Freedom KUKA Youbot in different reach-to-grasp scenarios.
AB - This paper presents the design of a vision-based object grasping and motion control architecture for a mobile manipulator system. The optimal grasping areas of the object are estimated using the partial point cloud acquired from an onboard RGB-D sensor system. The reach-to-grasp motion of the mobile manipulator is handled via a Nonlinear Model Predictive Control scheme. The controller is formulated accordingly in order to allow the system to operate in a constrained workspace with static obstacles. The goal of the proposed scheme is to guide the robot's end-effector towards the optimal grasping regions with guaranteed input and state constraints such as occlusion and obstacle avoidance, workspace boundaries and field of view constraints. The performance of the proposed strategy is experimentally verified using an 8 Degrees of Freedom KUKA Youbot in different reach-to-grasp scenarios.
UR - http://www.scopus.com/inward/record.url?scp=85062970514&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062970514&partnerID=8YFLogxK
U2 - 10.1109/IROS.2018.8593759
DO - 10.1109/IROS.2018.8593759
M3 - Conference contribution
AN - SCOPUS:85062970514
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 7145
EP - 7150
BT - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
Y2 - 1 October 2018 through 5 October 2018
ER -