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An experimental study of teleoperation system for walking robots using high-speed image stabilization system

机译:使用高速图像稳定系统步行机器人漫通式系统的实验研究

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摘要

Walking robots have high adaptability for terrain variation, and thus, have been expected as effective moving platform on uneven terrain, stairs, forest, marshy surface, and on ice. On the other hand, mobile robots that perform several hazardous tasks such as mine detection or the inspection of an atomic power plant are typically controlled by operators from distant places. For a teleoperation system, use of visual information from a camera mounted on a robot body is very useful. However, unlike wheeled vehicles, the camera mounted on the walking robot oscillates because of the impact of walking, and the obtained unstable images cause inferior operation performance. In this paper, we introduce an image stabilization system for teleoperation of walking robots using a high speed CCD camera and gyrosensors. The image stabilization is executed in two phases, that is, the estimation of the amount of oscillation by the combination of the template matching method and gyrosensors, and change of the display region. Pentium MMX instruction is used for template matching calculation, and the estimated amount of oscillation is given in every 12 [msec]. Furthermore. developed image stabilization mechanism can he used an external attitude sensor from the visual information, and the damping control of the robot body while walking is also possible. Experimental results showed stabilized images that eliminates the oscillation component are taken even when the robot moves dynamically or iii long distance, and verified that the performance of attitude control using the developed image stabilization system is almost same as the case using an attitude sensor.
机译:行走机器人对地形变异具有高适应性,因此预计在不均匀地形,楼梯,森林,沼泽表面和冰上有效移动平台。另一方面,执行诸如矿山检测或原子发电厂的检查的诸如危险任务的移动机器人通常由来自遥控场所的运营商控制。对于遥操作系统,从安装在机器人身体上的相机的视觉信息非常有用。然而,与轮式车辆不同,由于行走的影响,相机安装在行走机器人上,并且所获得的不稳定图像导致操作性低。在本文中,我们使用高速CCD相机和陀螺仪介绍了用于步行机器人的远程操作的图像稳定系统。图像稳定化以两个阶段执行,即,通过模板匹配方法和陀螺仪的组合来估计振荡量,以及显示区域的变化。 Pentium MMX指令用于模板匹配计算,并且每12张[MSEC]中估计振荡量。此外。发达的图像稳定机制可以从视觉信息中使用外部姿态传感器,以及机器人身体的阻尼控制也是可能的。实验结果表明,即使机器人动态移动或验证使用姿态传感器的姿态控制的姿态控制性能几乎与使用姿态传感器几乎相同的情况,也显示了消除振荡部件的稳定图像。

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