In this paper,we present a robot vision based system for coordinate measurement of feature points on large scale automobile parts.Our system consists of an industrial 6-DOF robot mounted with a CCD camera and a PC.The...In this paper,we present a robot vision based system for coordinate measurement of feature points on large scale automobile parts.Our system consists of an industrial 6-DOF robot mounted with a CCD camera and a PC.The system controls the robot into the area of feature points.The images of measuring feature points are acquired by the camera mounted on the robot.3D positions of the feature points are obtained from a model based pose estimation that applies to the images.The measured positions of all feature points are then transformed to the reference coordinate of feature points whose positions are obtained from the coordinate measuring machine(CMM).Finally,the point-to-point distances between the measured feature points and the reference feature points are calculated and reported.The results show that the root mean square error(RMSE) of measure values obtained by our system is less than 0.5 mm.Our system is adequate for automobile assembly and can perform faster than conventional methods.展开更多
This paper presents a coordinated target localization method for clustered space robot.According to the different measuring capabilities of cluster members,the master-slave coordinated relative navigation strategy for...This paper presents a coordinated target localization method for clustered space robot.According to the different measuring capabilities of cluster members,the master-slave coordinated relative navigation strategy for target localization with respect to slavery space robots is proposed;then the basic mathematical models,including coordinated relative measurement model and cluster centralized dynamics,are established respectively.By employing the linear Kalman flter theorem,the centralized estimator based on truth measurements is developed and analyzed frstly,and with an intention to inhabit the initial uncertainties related to target localization,the globally stabilized estimator is designed through introduction of pseudo measurements.Furthermore,the observability and controllability of stochastic system are also analyzed to qualitatively evaluate the convergence performance of pseudo measurement estimator.Finally,on-orbit target approaching scenario is simulated by using semi-physical simulation system,which is used to verify the convergence performance of proposed estimator.During the simulation,both the known and unknown maneuvering acceleration cases are considered to demonstrate the robustness of coordinated localization strategy.展开更多
The skill of robotic hand-eye coordination not only helps robots to deal with real time environment,but also afects the fundamental framework of robotic cognition.A number of approaches have been developed in the lite...The skill of robotic hand-eye coordination not only helps robots to deal with real time environment,but also afects the fundamental framework of robotic cognition.A number of approaches have been developed in the literature for construction of the robotic hand-eye coordination.However,several important features within infant developmental procedure have not been introduced into such approaches.This paper proposes a new method for robotic hand-eye coordination by imitating the developmental progress of human infants.The work employs a brain-like neural network system inspired by infant brain structure to learn hand-eye coordination,and adopts a developmental mechanism from psychology to drive the robot.The entire learning procedure is driven by developmental constraint: The robot starts to act under fully constrained conditions,when the robot learning system becomes stable,a new constraint is assigned to the robot.After that,the robot needs to act with this new condition again.When all the contained conditions have been overcome,the robot is able to obtain hand-eye coordination ability.The work is supported by experimental evaluation,which shows that the new approach is able to drive the robot to learn autonomously,and make the robot also exhibit developmental progress similar to human infants.展开更多
This paper presents control strategies for finite-time stabilization of a class of nonholonomic dynamic systems with unknown virtual control coefficients and system parameters. The minimal dilation degree technique an...This paper presents control strategies for finite-time stabilization of a class of nonholonomic dynamic systems with unknown virtual control coefficients and system parameters. The minimal dilation degree technique and the terminal sliding mode control scheme with finite-time convergence are used to design the controllers. The systematic control strategy development involves the introduction of state transformations and the application of recursive terminal sliding mode structure. Depending on whether the system in question can be converted into a time-invariant linear system or not, two control schemes are proposed respectively guaranteeing that system states converge to zero in finite time. The effectiveness and the robust feature of the developed control approaches are testified by two practical examples: the simplified underactuated hovercraft system and the parking problem for a mobile robot of the unicycle type.展开更多
基金wsupported by the Thailand Research Fund and Solimac Automation Co.,Ltd.under the Research and Researchers for Industry Program(RRI)under Grant No.MSD56I0098Office of the Higher Education Commission under the National Research University Project of Thailand
文摘In this paper,we present a robot vision based system for coordinate measurement of feature points on large scale automobile parts.Our system consists of an industrial 6-DOF robot mounted with a CCD camera and a PC.The system controls the robot into the area of feature points.The images of measuring feature points are acquired by the camera mounted on the robot.3D positions of the feature points are obtained from a model based pose estimation that applies to the images.The measured positions of all feature points are then transformed to the reference coordinate of feature points whose positions are obtained from the coordinate measuring machine(CMM).Finally,the point-to-point distances between the measured feature points and the reference feature points are calculated and reported.The results show that the root mean square error(RMSE) of measure values obtained by our system is less than 0.5 mm.Our system is adequate for automobile assembly and can perform faster than conventional methods.
基金supported by the National Natural Science Foundation of China (No.11102018)
文摘This paper presents a coordinated target localization method for clustered space robot.According to the different measuring capabilities of cluster members,the master-slave coordinated relative navigation strategy for target localization with respect to slavery space robots is proposed;then the basic mathematical models,including coordinated relative measurement model and cluster centralized dynamics,are established respectively.By employing the linear Kalman flter theorem,the centralized estimator based on truth measurements is developed and analyzed frstly,and with an intention to inhabit the initial uncertainties related to target localization,the globally stabilized estimator is designed through introduction of pseudo measurements.Furthermore,the observability and controllability of stochastic system are also analyzed to qualitatively evaluate the convergence performance of pseudo measurement estimator.Finally,on-orbit target approaching scenario is simulated by using semi-physical simulation system,which is used to verify the convergence performance of proposed estimator.During the simulation,both the known and unknown maneuvering acceleration cases are considered to demonstrate the robustness of coordinated localization strategy.
基金supported by National Natural Science Foundation of China (No.6120333661273338 and 61003014)Major State Basic Research Development Program of China (973 Program)(No.2013CB329502)
文摘The skill of robotic hand-eye coordination not only helps robots to deal with real time environment,but also afects the fundamental framework of robotic cognition.A number of approaches have been developed in the literature for construction of the robotic hand-eye coordination.However,several important features within infant developmental procedure have not been introduced into such approaches.This paper proposes a new method for robotic hand-eye coordination by imitating the developmental progress of human infants.The work employs a brain-like neural network system inspired by infant brain structure to learn hand-eye coordination,and adopts a developmental mechanism from psychology to drive the robot.The entire learning procedure is driven by developmental constraint: The robot starts to act under fully constrained conditions,when the robot learning system becomes stable,a new constraint is assigned to the robot.After that,the robot needs to act with this new condition again.When all the contained conditions have been overcome,the robot is able to obtain hand-eye coordination ability.The work is supported by experimental evaluation,which shows that the new approach is able to drive the robot to learn autonomously,and make the robot also exhibit developmental progress similar to human infants.
基金supported by National Natural Science Foundation of China(No.61273091)Project of Taishan Scholar of Shandong Province of China,and the Ph.D.Programs Foundation of Ministry of Education of China
文摘This paper presents control strategies for finite-time stabilization of a class of nonholonomic dynamic systems with unknown virtual control coefficients and system parameters. The minimal dilation degree technique and the terminal sliding mode control scheme with finite-time convergence are used to design the controllers. The systematic control strategy development involves the introduction of state transformations and the application of recursive terminal sliding mode structure. Depending on whether the system in question can be converted into a time-invariant linear system or not, two control schemes are proposed respectively guaranteeing that system states converge to zero in finite time. The effectiveness and the robust feature of the developed control approaches are testified by two practical examples: the simplified underactuated hovercraft system and the parking problem for a mobile robot of the unicycle type.