触觉机器人绘制未知表面:在油井勘探中的应用

Francesco Mazzini, Daniel T. Kettler, S. Dubowsky, Julio Guerrero
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引用次数: 20

摘要

世界石油需求和先进的采油技术使得修复废弃油井具有经济上的吸引力。这需要相对快速地绘制井下井结构的形状和位置。实际因素禁止在这种情况下使用视觉和其他距离传感器。在此,研究了机器人触觉映射的可行性。开发了一种仅使用机器人关节编码器的方法,避免了在这种恶劣环境中复杂且不可靠的任何力或触觉传感器。本文解决了智能触觉探索受限内部几何形状的一般问题,其中时间是关键的。假定移动机械手获取新接触点所需的时间大于计算时间。该方法利用几何原语对井下结构进行建模,并通过智能搜索新的接触点来建立几何模型,以提高勘探效率。本文开发的算法在仿真和硬件实验中得到了证明,可以大大减少触觉机械手探索数据采集的工作量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tactile robotic mapping of unknown surfaces: an application to oil well exploration
World oil demand and advanced oil recovery techniques have made it economically attractive to rehabilitate previously abandoned oil wells. This requires relatively fast mapping of the shape and location of the down-hole well structures. Practical factors prohibit the use of visual and other range sensors in this situation. Here, the feasibility of robotic tactile mapping is studied. A method is developed that only uses the robot joint encoders and avoids any force or tactile sensor, which are complex and unreliable in such a hostile environment. This paper addresses the general problem of intelligent tactile exploration of constrained internal geometries where time is critical. It is assumed that the time required to move a manipulator to acquire a new touch point outweighs computational time. This approach models the down-hole structures with geometric primitives and focuses on exploration efficiency by intelligently searching for new touch points to build the geometric models. The algorithms developed here are shown in simulations and hardware experiments to substantially reduce the data acquisition effort for exploration with a tactile manipulator.
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