作　　者： ; ;

机构地区： 湖南大学电气与信息工程学院

出　　处： 《仪器仪表学报》 2004年第5期676-680,687,共6页

摘　　要： 估计两参考坐标系之间的相对三维位姿和相对运动 ,对机器人导航、机器人装配、测量、跟踪、目标识别和摄像机定标来说是一个非常重要的问题。用八元数来表示摄像机和运动目标两坐标系之间相对平移和旋转 ,在假设运动目标的三维几何尺寸已知 ,且摄像机和运动目标之间的相对运动为匀速运动的情况下 ,由单个针孔摄像机获取运动目标的图像并测量其图像中的线特征点。由于旋转部分用四元数表示 ,状态转移函数是非线性的 ,测量函数由三维坐标变换和针孔摄像机模型所决定 ,存在严重的非线性 ,常规的卡尔曼滤波方法不适合 ,这里以扩展卡尔曼滤波方法作为数学模型 ,对状态转移函数和测量函数进行线性化后 ,对摄像机和运动目标之间的位姿和相对运动进行了估计 ,仿真结果表明 Determination of relative three-dimensional position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry, tracking, object recognition, and camera calibration. Using dual quaternion represents the relative translation and rotation of two coordinate systems between camera and moving object. Under the assumption that the mobile object's three dimension geometric size is known and the relative motion velocity between camera and moving object is constant. The moving object's image is obtained using monocular pinhole camera and the line feature points in image plaue are measured. Because the rotation is presented by quaternion, the state transferring function is non-linear, what's more, the measured function is decided by the 3D coordinate transformation and the pinhole camera model, it exists non-linear severely. The general Kalman filtering is not suit to pox and motion estimation. Using the extended Kalman filtering as mathematic model, and after the linearization of the measurement function and the state transformation function, the pose and the relative motion of camera and moving object are estimated. And the result of simulation has shown that the algorithm of pose and motion estimation has good convergence.

关 键 词： 位姿 状态转移函数 运动目标 机器人导航 线特征 表示 仿真结果 摄像机 运动估计 扩展卡尔曼滤波

领　　域： [机械工程] [自动化与计算机技术] [自动化与计算机技术]