Uncalibrated image-based position-force adaptive visual servoing for constrained robots under dynamic friction uncertainties
Uncalibrated image-based position-force adaptive visual servoing for constrained robots under dynamic friction uncertainties
复制标题
动摩擦不确定性下约束机器人的未校准图像位置力自适应视觉伺服
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
A. Espinosa
中科院分区：
文献类型：
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作者：
E. Dean;L. García;Vicente Parra‐Vega;A. Espinosa
约束动力机器人的视觉伺服问题目前还没有得到正式的研究。同时，注意到由于技术限制，这项任务是在速度反转的情况下缓慢完成的，因此会产生动态摩擦，这使问题更加复杂。提出了一种新的动态摩擦约束机器人视觉伺服自适应方案。提出了一种基于图像的控制方法，使约束视觉位置和末端执行器与约束曲面之间的接触力同时收敛。摄像机和机器人参数被认为是不确定的。这种新方法是基于力控制中使用的正交化原理的新公式，即视觉正交化原理。这允许，在被动的框架下，产生融合摄像头，编码器和力传感器信号的协同方案。仿真结果表明，尽管存在摩擦模型的不确定性，但图像误差和力误差是收敛的。
Visual servoing of constrained dynamical robots has not yet met a formal treatment. Also, notices that due technological constraints, this task is done slowly at velocity reversals, thus dynamic friction arises, which complicates even more the problem. In this paper, a new adaptive scheme for visual servoing of constrained robots subject to dynamic friction is proposed. An image-based control is introduced to produce simultaneous convergence of the constrained visual position and the contact force between the end-effector and the constraint surface. Camera and robot parameters are considered uncertain. This new approach is based on a new formulation of the orthogonalization principle used in force control, coined here visual orthogonalization principle. This allows, under the framework of passivity, to yield a synergetic scheme that fuses camera, encoder and force sensor signals. Simulation results are presented and show that image errors and force errors converge despite uncertainties of friction model.