In constrained motion control of a robot,the interaction force is an important variable,which directly describes the state of interaction.It is required in a number of algorithms for interaction control.Desirably,the ...In constrained motion control of a robot,the interaction force is an important variable,which directly describes the state of interaction.It is required in a number of algorithms for interaction control.Desirably,the interaction force has to be measured by force sensors.However,there are inherent limitations with force sensors,such as the cost,sensing noise,limited bandwidth,and the difficulty of physical location at the required place,which is dynamic.In the present paper,the interaction force is estimated by using high order sliding mode observers.An adaptive version of a high order sliding mode observer is developed to robustly reconstruct the interaction force.Experimental results are given to show the effectiveness of the developed algorithms.展开更多
In this research work,a hierarchical controller has been designed for an autonomous navigation robot to avoid unexpected moving obstacles where the state and action spaces are continuous.The proposed scheme consists o...In this research work,a hierarchical controller has been designed for an autonomous navigation robot to avoid unexpected moving obstacles where the state and action spaces are continuous.The proposed scheme consists of two parts:1)a controller with a high-level approximate reinforcement learning(ARL)technique for choosing an optimal trajectory in autonomous navigation;and 2)a low-level,appearance-based visual servoing(ABVS)controller which controls and execute the motion of the robot.A novel approach for path planning and visual servoing has been proposed by the combined system framework.The characteristics of the on-board camera which is equipped on the robot is naturally suitable for conducting the reinforcement learning algorithm.Regarding the ARL controller,the computational overhead is quite low thanks to the fact that a knowledge of obstacle motion is not necessary.The developed scheme has been implemented and validated in a simulation system of obstacle avoidance.It is noted that findings of the proposed method are successfully verified by obtaining an optimal robotic plan motion strategy.展开更多
For robot interaction control,the interaction force between the robot and the manipulated object or environment should be monitored.Impedance control is a type of interaction control.Specifically,in impedance control,...For robot interaction control,the interaction force between the robot and the manipulated object or environment should be monitored.Impedance control is a type of interaction control.Specifically,in impedance control,the dynamic relationship between the interaction force and the resulting motion is controlled.In order to control the impedance of a mechanical system,typically,the interaction force has to be sensed.Due to the inherent limitations of direct force sensing at the interaction site,in the present work,the interaction force is observed using robust observers.In particular,to enhance the accuracy of impedance control,a first order sliding mode impedance controller is designed and incorporated in the present paper.Its advantage over positionbased interaction control algorithms is demonstrated through experimentation.Experimental results are given to show the effectiveness of the proposed algorithms.展开更多
文摘In constrained motion control of a robot,the interaction force is an important variable,which directly describes the state of interaction.It is required in a number of algorithms for interaction control.Desirably,the interaction force has to be measured by force sensors.However,there are inherent limitations with force sensors,such as the cost,sensing noise,limited bandwidth,and the difficulty of physical location at the required place,which is dynamic.In the present paper,the interaction force is estimated by using high order sliding mode observers.An adaptive version of a high order sliding mode observer is developed to robustly reconstruct the interaction force.Experimental results are given to show the effectiveness of the developed algorithms.
基金supported by research grants from the Natural Sciences and Engineering Research Council(NSERC)of Canadathe British Columbia Knowledge Development Fund(BCKDF)+1 种基金the Canada Foundation for Innovation(CFI)the Canada Research Chair in Mechatronics and Industrial Automation held by C.W.de Silva
文摘In this research work,a hierarchical controller has been designed for an autonomous navigation robot to avoid unexpected moving obstacles where the state and action spaces are continuous.The proposed scheme consists of two parts:1)a controller with a high-level approximate reinforcement learning(ARL)technique for choosing an optimal trajectory in autonomous navigation;and 2)a low-level,appearance-based visual servoing(ABVS)controller which controls and execute the motion of the robot.A novel approach for path planning and visual servoing has been proposed by the combined system framework.The characteristics of the on-board camera which is equipped on the robot is naturally suitable for conducting the reinforcement learning algorithm.Regarding the ARL controller,the computational overhead is quite low thanks to the fact that a knowledge of obstacle motion is not necessary.The developed scheme has been implemented and validated in a simulation system of obstacle avoidance.It is noted that findings of the proposed method are successfully verified by obtaining an optimal robotic plan motion strategy.
文摘For robot interaction control,the interaction force between the robot and the manipulated object or environment should be monitored.Impedance control is a type of interaction control.Specifically,in impedance control,the dynamic relationship between the interaction force and the resulting motion is controlled.In order to control the impedance of a mechanical system,typically,the interaction force has to be sensed.Due to the inherent limitations of direct force sensing at the interaction site,in the present work,the interaction force is observed using robust observers.In particular,to enhance the accuracy of impedance control,a first order sliding mode impedance controller is designed and incorporated in the present paper.Its advantage over positionbased interaction control algorithms is demonstrated through experimentation.Experimental results are given to show the effectiveness of the proposed algorithms.
