Accurate stereo vision calibration is a preliminary step towards high-precision visual posi- tioning of robot. Combining with the characteristics of genetic algorithm （GA） and particle swarm optimization （PSO）, a ...Accurate stereo vision calibration is a preliminary step towards high-precision visual posi- tioning of robot. Combining with the characteristics of genetic algorithm （GA） and particle swarm optimization （PSO）, a three-stage calibration method based on hybrid intelligent optimization is pro- posed for nonlinear camera models in this paper. The motivation is to improve the accuracy of the calibration process. In this approach, the stereo vision calibration is considered as an optimization problem that can be solved by the GA and PSO. The initial linear values can be obtained in the frost stage. Then in the second stage, two cameras＇ parameters are optimized separately. Finally, the in- tegrated optimized calibration of two models is obtained in the third stage. Direct linear transforma- tion （DLT）, GA and PSO are individually used in three stages. It is shown that the results of every stage can correctly find near-optimal solution and it can be used to initialize the next stage. Simula- tion analysis and actual experimental results indicate that this calibration method works more accu- rate and robust in noisy environment compared with traditional calibration methods. The proposed method can fulfill the requirements of robot sophisticated visual operation.展开更多
A real-time arc welding robot visual control system based on a local network with a multi-level hierarchy is developed in this paper. It consists of an intelligence and human-machine interface level, a motion planning...A real-time arc welding robot visual control system based on a local network with a multi-level hierarchy is developed in this paper. It consists of an intelligence and human-machine interface level, a motion planning level, a motion control level and a servo control level. The last three levels form a local real-time open robot controller, which realizes motion planning and motion control of a robot. A camera calibration method based on the relative movement of the end-effector connected to a robot is proposed and a method for tracking weld seam based on the structured light stereovision is provided. Combining the parameters of the cameras and laser plane, three groups of position values in Cartesian space are obtained for each feature point in a stripe projected on the weld seam. The accurate three-dimensional position of the edge points in the weld seam can be calculated from the obtained parameters with an information fusion algorithm. By calculating the weld seam parameter from position and image data, the movement parameters of the robot used for tracking can be determined. A swing welding experiment of type V groove weld is successfully conducted, the results of which show that the system has high resolution seam tracking in real-time, and works stably and efficiently.展开更多
经颅磁刺激(transcranial magnetic stimulation, TMS)是一种神经调制方法,临床中凭借医生经验手动确定TMS线圈摆放位姿,导致线圈摆放位置和姿态不准确且重复定位精度差。针对上述问题,提出一种TMS线圈机器人辅助定位系统,使用RGB相机...经颅磁刺激(transcranial magnetic stimulation, TMS)是一种神经调制方法,临床中凭借医生经验手动确定TMS线圈摆放位姿,导致线圈摆放位置和姿态不准确且重复定位精度差。针对上述问题,提出一种TMS线圈机器人辅助定位系统,使用RGB相机替代导航系统中双目红外相机,采用一种基于神经网络的无标志物TMS线圈机器人辅助定位方法。搭建神经网络实现相机空间线圈姿态到操作臂空间关节角度的映射,并通过仿真数据训练验证了该神经网络架构适用于TMS线圈位姿摆放问题。随后,通过实验验证了该方法的可行性,同时表明训练的神经网络针对TMS线圈定位任务具有良好的泛化能力。最后,在笛卡儿空间的位姿验证结果显示TMS线圈三维位置平均误差为2.16 mm,总体姿态误差为0.055 rad,使用RGB相机的TMS线圈机器人辅助定位系统在精度上达到了与其他使用双目红外相机的科研或商用系统相同的水平,满足TMS临床治疗要求,具备临床应用的可行性。展开更多
同步定位与建图(simultaneous localization and mapping,SLAM)技术能够帮助移动机器人在没有先验信息的条件下,为其提供地图和自身位置信息,已成为移动机器人自主导航的主流解决方案,其中以相机为传感器的视觉SLAM,有着体积小巧、成本...同步定位与建图(simultaneous localization and mapping,SLAM)技术能够帮助移动机器人在没有先验信息的条件下,为其提供地图和自身位置信息,已成为移动机器人自主导航的主流解决方案,其中以相机为传感器的视觉SLAM,有着体积小巧、成本低、高分辨率等优势。随着研究者们对SLAM问题的深入研究,SLAM领域相关成果已非常丰富,但是有关视觉场景下的SLAM论述还不够系统。文中首先介绍了视觉SLAM的基本原理,之后对于传统视觉SLAM与基于深度学习的视觉SLAM两个方面阐述了视觉SLAM的研究方法,从地图类型以及特点等方面进行对比分析,为移动机器人的视觉SLAM技术研究提供了参考。展开更多
文摘Accurate stereo vision calibration is a preliminary step towards high-precision visual posi- tioning of robot. Combining with the characteristics of genetic algorithm （GA） and particle swarm optimization （PSO）, a three-stage calibration method based on hybrid intelligent optimization is pro- posed for nonlinear camera models in this paper. The motivation is to improve the accuracy of the calibration process. In this approach, the stereo vision calibration is considered as an optimization problem that can be solved by the GA and PSO. The initial linear values can be obtained in the frost stage. Then in the second stage, two cameras＇ parameters are optimized separately. Finally, the in- tegrated optimized calibration of two models is obtained in the third stage. Direct linear transforma- tion （DLT）, GA and PSO are individually used in three stages. It is shown that the results of every stage can correctly find near-optimal solution and it can be used to initialize the next stage. Simula- tion analysis and actual experimental results indicate that this calibration method works more accu- rate and robust in noisy environment compared with traditional calibration methods. The proposed method can fulfill the requirements of robot sophisticated visual operation.
基金This work was supported by the National High Technology Research and Development Program of China under Grant 2002AA422160 by the National Key Fundamental Research and the Devel-opment Project of China (973) under Grant 2002CB312200.
文摘A real-time arc welding robot visual control system based on a local network with a multi-level hierarchy is developed in this paper. It consists of an intelligence and human-machine interface level, a motion planning level, a motion control level and a servo control level. The last three levels form a local real-time open robot controller, which realizes motion planning and motion control of a robot. A camera calibration method based on the relative movement of the end-effector connected to a robot is proposed and a method for tracking weld seam based on the structured light stereovision is provided. Combining the parameters of the cameras and laser plane, three groups of position values in Cartesian space are obtained for each feature point in a stripe projected on the weld seam. The accurate three-dimensional position of the edge points in the weld seam can be calculated from the obtained parameters with an information fusion algorithm. By calculating the weld seam parameter from position and image data, the movement parameters of the robot used for tracking can be determined. A swing welding experiment of type V groove weld is successfully conducted, the results of which show that the system has high resolution seam tracking in real-time, and works stably and efficiently.
文摘同步定位与建图(simultaneous localization and mapping,SLAM)技术能够帮助移动机器人在没有先验信息的条件下,为其提供地图和自身位置信息,已成为移动机器人自主导航的主流解决方案,其中以相机为传感器的视觉SLAM,有着体积小巧、成本低、高分辨率等优势。随着研究者们对SLAM问题的深入研究,SLAM领域相关成果已非常丰富,但是有关视觉场景下的SLAM论述还不够系统。文中首先介绍了视觉SLAM的基本原理,之后对于传统视觉SLAM与基于深度学习的视觉SLAM两个方面阐述了视觉SLAM的研究方法,从地图类型以及特点等方面进行对比分析,为移动机器人的视觉SLAM技术研究提供了参考。
