基于图象的视觉 servoing 能被用来高效地控制机器人操纵者的运动。什么时候起始并且然而,需要的配置是远的是由许多研究人员,指出了如此的一条控制途径能由于它的本地性质受不了集中和稳定性问题。由指定足够的图象特征轨道在图象被列在后面,我们能利用基于图象的视觉 servoing 的本地集中和稳定性避免这些问题。因此,路径在图象空间计划是在最近的年里的机器人学的一个活跃研究话题。然而,几乎所有为 camera-in-hand 配置的盒子相关结果被建立。在这篇论文,我们建议 uncalibrated 为改正照相机配置的盒子的视觉路径计划算法。这个算法在射影的空格直接计算图象特征的轨道以便他们与僵硬天体运动兼容。由把旋转和翻译的射影的代表分解成他们的各自的正规形式,我们能容易插入内推他们在射影的空间的路径。然后,在图象飞机的图象特征的轨道能经由射影的路径被产生。这样,特征点的知识组织并且照相机内在的参数没被要求。验证建议算法的可行性和表演,基于 puma560 机器人,操纵者在这被给的模拟结果糊。
Image-based visual servoing can be used to efficiently control the motion of robot manipulators. When the initial and the desired configurations are distant, however, as pointed out by many researchers, such a control approach can suffer from the convergence and stability problems due to its local properties. By specifying adequate image feature trajectories to be followed in the image, we can take advantage of the local convergence and stability of image-based visual servoing to avoid these problems. Hence, path planning in the image space has been an active research topic in robotics in recent years. However, almost all of the related results are established for the case of camera-in-hand configuration. In this paper, we propose an uncalibrated visual path planning algorithm for the case of fixed-camera configuration. This algorithm computes the trajectories of image features directly in the projective space such that they are compatible with rigid body motion. By decomposing the projective representations of the rotation and the translation into their respective canonical forms, we can easily interpolate their paths in the projective space. Then, the trajectories of image features in the image plane can be generated via projective paths. In this way, the knowledge of feature point structures and camera intrinsic parameters are not required. To validate the feasibility and performance of the proposed algorithm, simulation results based on the puma560 robot manipulator are given in this paper.