A learning-based control approach is presented for force servoing of a robot with vision in an unknown environment. Firstly, mapping relationships between image features of the servoing object and the joint angles of ...A learning-based control approach is presented for force servoing of a robot with vision in an unknown environment. Firstly, mapping relationships between image features of the servoing object and the joint angles of the robot are derived and learned by a neural network. Secondly, a learning controller based on the neural network is designed for the robot to trace the object. Thirdly, a discrete time impedance control law is obtained for the force servoing of the robot, the on-line learning algorithms for three neural networks are developed to adjust the impedance parameters of the robot in the unknown environment. Lastly, wiping experiments are carried out by using a 6 DOF industrial robot with a CCD camera and a force/torque sensor in its end effector, and the experimental results confirm the effecti veness of the approach.展开更多
General,high-precision theoretical modeling method is not well developed in the field of soft robotics,which holds back motion control and practical application of soft robots.The concept of modularization brings nove...General,high-precision theoretical modeling method is not well developed in the field of soft robotics,which holds back motion control and practical application of soft robots.The concept of modularization brings novel structure,novel locomotion patterns as well as novel control method for soft robots.This paper presents the concept of hierarchical control method for modular soft robot system and a H-configuration pneumatic modular soft robot is designed as the control object.The H-configuration modular soft robot is composed of two basic motion units that take worm-like locomotion principle.The locomotion principle of the basic motion unit is analyzed and the actuation sequence is optimized by evolution strategy in VOXCAD simulation software.The differential drive method is applied to the H-configuration modular soft robot with multi motion modes and vision sensor is used to control the motion mode of the robot.The H-configuration modular soft robot and the basic motion unit are assembled by a cubic soft module made of silicone rubber.Also,connection mechanism is designed to ensure that the soft modules can be assembled in any direction and posture.Experiments are conducted to verify the effect of the hierarchical control method of the modular soft robots.展开更多
基金This project was supported by the research foundation of China Education Ministry for the scholars from abroad (2002247).
文摘A learning-based control approach is presented for force servoing of a robot with vision in an unknown environment. Firstly, mapping relationships between image features of the servoing object and the joint angles of the robot are derived and learned by a neural network. Secondly, a learning controller based on the neural network is designed for the robot to trace the object. Thirdly, a discrete time impedance control law is obtained for the force servoing of the robot, the on-line learning algorithms for three neural networks are developed to adjust the impedance parameters of the robot in the unknown environment. Lastly, wiping experiments are carried out by using a 6 DOF industrial robot with a CCD camera and a force/torque sensor in its end effector, and the experimental results confirm the effecti veness of the approach.
基金This work is supported by National Outstanding Youth Science Fund Project of National Natural Science Foundation of China(Grant no.52025054)National Natural Science Foundation of China(Grant no.U1713201).
文摘General,high-precision theoretical modeling method is not well developed in the field of soft robotics,which holds back motion control and practical application of soft robots.The concept of modularization brings novel structure,novel locomotion patterns as well as novel control method for soft robots.This paper presents the concept of hierarchical control method for modular soft robot system and a H-configuration pneumatic modular soft robot is designed as the control object.The H-configuration modular soft robot is composed of two basic motion units that take worm-like locomotion principle.The locomotion principle of the basic motion unit is analyzed and the actuation sequence is optimized by evolution strategy in VOXCAD simulation software.The differential drive method is applied to the H-configuration modular soft robot with multi motion modes and vision sensor is used to control the motion mode of the robot.The H-configuration modular soft robot and the basic motion unit are assembled by a cubic soft module made of silicone rubber.Also,connection mechanism is designed to ensure that the soft modules can be assembled in any direction and posture.Experiments are conducted to verify the effect of the hierarchical control method of the modular soft robots.
