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Homography-Based Visual Servo Tracking Control of Wheeled Mobile Robots with Simultaneous Depth Identification

机译:同时基于深度识别的基于单应象的轮式移动机器人视觉伺服跟踪控制

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In this paper, a visual servo tracking control method is developed for the wheeled mobile robot subject to nonholonomic motion constraints, while the unknown feature depth information is simultaneously identified in the visual servoing process. Firstly, a video feature points are prerecorded as the desire trajectory for the mobile robot. Secondly, Euclidean homographies are constructed by utilizing projective geometric relationships of feature points. Subsequently, trajectory tracking errors are obtained after Euclidean homographies decomposition. Then, the kinematic controller is designed for the mobile robot to achieve the visual servo trajectory tracking task. Moreover, by utilizing the concurrent learning framework, the historical and current system data is used to construct an adaptive updating mechanism for recovering the unknown feature depth. Simulation results are collected to prove the efficiency and utility of the proposed strategy.
机译:本文针对非完整运动约束的轮式移动机器人,开发了一种视觉伺服跟踪控制方法,同时在视觉伺服过程中同时识别未知特征深度信息。首先,将视频特征点预先记录为移动机器人的愿望轨迹。其次,利用特征点的投影几何关系构造欧几里得单应式。随后,在欧几里得单应性分解之后获得轨迹跟踪误差。然后,为移动机器人设计了运动学控制器,以实现视觉伺服轨迹跟踪任务。此外,通过利用并发学习框架,历史数据和当前系统数据被用于构建自适应更新机制以恢复未知特征深度。仿真结果被收集以证明所提策略的有效性和实用性。

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