In this paper,a visual servoing approach is developed to capture the docking rings of tumbling non-cooperative satellites with a space manipulator.The primary challenge addressed is the potential for the docking ring ...In this paper,a visual servoing approach is developed to capture the docking rings of tumbling non-cooperative satellites with a space manipulator.The primary challenge addressed is the potential for the docking ring to leave the monocular camera’s field-of-view as the manipulator approaches the target,due to the ring’s large size.To solve this issue,a two-phase visual servoing scheme combining a monocular camera and a three-line structured light vision system is proposed.In an effort to augment the success rate and safety of capture operations,several constraints are formulated,encompassing manipulator’s kinematics,monocular camera’s field-of-view,obstacle avoidance,structured light’s breakpoints and smooth capture.Subsequently,a nonlinear model predictive controller is proposed to manage these constraints in real-time and regulate the system.System models are established based on image moments and pose for each phase,selecting these features as visual feedback to simplify the formulation of servo constraints and avoid the complex circle-based pose measurement.Furthermore,to ensure unbiased predictions,the model disturbances arising from the imprecise estimation of target motion parameter are observed using an extended Kalman filter,which are then incorporated into the predictive control framework.The simulation results demonstrate the effectiveness of this scheme.展开更多
针对非合作慢旋卫星的模型重建问题,提出基于飞行时间(time-of-flight,TOF)相机和同时定位与制图(simultaneous localization and mapping,SLAM)的稠密重建方法。基于预先检测与自适应阈值方法提高旋转提取与描述(oriented fast and rot...针对非合作慢旋卫星的模型重建问题,提出基于飞行时间(time-of-flight,TOF)相机和同时定位与制图(simultaneous localization and mapping,SLAM)的稠密重建方法。基于预先检测与自适应阈值方法提高旋转提取与描述(oriented fast and rotated brief,ORB)的特征尺度适应性。利用运动度量方法选取关键帧。利用子模型拼接方法加快重建效率。利用仿真环境制作非合作慢旋卫星的数据集。仿真实验结果表明:该方法能够实现长时间稳定地工作,可在3 min内重建出卫星模型的稠密点云,点云密度大于5000,重建误差小于5 cm。利用机械臂、卫星模型及光学暗室搭建半物理实验系统,表明算法的精度及抗噪声能力基本满足非合作目标感知的任务的需求。展开更多
基金supported by the China Postdoctoral Science Foundation(No.2022M710956).
文摘In this paper,a visual servoing approach is developed to capture the docking rings of tumbling non-cooperative satellites with a space manipulator.The primary challenge addressed is the potential for the docking ring to leave the monocular camera’s field-of-view as the manipulator approaches the target,due to the ring’s large size.To solve this issue,a two-phase visual servoing scheme combining a monocular camera and a three-line structured light vision system is proposed.In an effort to augment the success rate and safety of capture operations,several constraints are formulated,encompassing manipulator’s kinematics,monocular camera’s field-of-view,obstacle avoidance,structured light’s breakpoints and smooth capture.Subsequently,a nonlinear model predictive controller is proposed to manage these constraints in real-time and regulate the system.System models are established based on image moments and pose for each phase,selecting these features as visual feedback to simplify the formulation of servo constraints and avoid the complex circle-based pose measurement.Furthermore,to ensure unbiased predictions,the model disturbances arising from the imprecise estimation of target motion parameter are observed using an extended Kalman filter,which are then incorporated into the predictive control framework.The simulation results demonstrate the effectiveness of this scheme.
文摘针对非合作慢旋卫星的模型重建问题,提出基于飞行时间(time-of-flight,TOF)相机和同时定位与制图(simultaneous localization and mapping,SLAM)的稠密重建方法。基于预先检测与自适应阈值方法提高旋转提取与描述(oriented fast and rotated brief,ORB)的特征尺度适应性。利用运动度量方法选取关键帧。利用子模型拼接方法加快重建效率。利用仿真环境制作非合作慢旋卫星的数据集。仿真实验结果表明:该方法能够实现长时间稳定地工作,可在3 min内重建出卫星模型的稠密点云,点云密度大于5000,重建误差小于5 cm。利用机械臂、卫星模型及光学暗室搭建半物理实验系统,表明算法的精度及抗噪声能力基本满足非合作目标感知的任务的需求。
