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Vision-based high-speed manipulation for robotic ultra-precise weed control

机译：基于视觉的高速操纵，可实现机器人的超高精度除草

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摘要

In this system paper we present a novel approach for autonomous, mobile manipulation for agricultural robots. Our target application is mechanical weed control which for example is needed in organic farming. Today, this task is often performed by field workers, whose availability is declining and the quality of their work differs greatly. In addition, manual weeding is a very tedious task with adverse health effects. Hence, mechanical weed control is considered as a prime example for automation. One of the challenges in order to perform the task efficiently is the need for fast plant detection and precise treatment of single plants with a mobile manipulator. The unstructured environment and rough field conditions raise additional challenges. We introduce a first system concept and control design known to handle these issues. In particular, high speed image processing and visual servoing are applied to precisely position a specially designed weeding tool. To evaluate the performance of the mobile manipulator we run experiments with a mobile test vehicle in field-like conditions and demonstrate that our system can treat single plants in less than 1s as it is required to be competitive.
机译：在本系统论文中，我们提出了一种用于农业机器人的自主，移动操纵的新颖方法。我们的目标应用是机械除草，例如有机农业中需要的除草。如今，这项任务通常由现场工作人员执行，他们的可用性正在下降，工作质量也有很大差异。此外，人工除草是一项非常繁琐的工作，会对健康造成不利影响。因此，机械除草被认为是自动化的主要例子。为了有效地执行任务，挑战之一是需要使用移动机械手对植物进行快速检测和精确处理。非结构化的环境和恶劣的野外条件带来了更多的挑战。我们介绍了第一个已知的可解决这些问题的系统概念和控制设计。特别是，高速图像处理和视觉伺服技术可用于精确定位特殊设计的除草工具。为了评估移动机械手的性能，我们在类似野外的条件下使用移动测试车进行了实验，并证明了我们的系统可以在不到1秒的时间内处理单个植物，这是竞争所必需的。

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