很难否认AI已经以多种方式被视为优于人类。它坚固，快速，几乎没有错误，不需要休息。当需要连续地以一致的质量和出色的性能可靠地进行工作运营时，这种优势尤其重要。
图片来源：IDS成像开发系统GmbH
AI在机器视觉环境中使用的原因之一是提高过程效率和成本效益。“视觉指导的机器人”用例突出了机器人和集成的AI视觉摄像机如何智能地自动化常见的拾取和位置任务，甚至使PC已过时。
对于“智能抓地力”，各种学科必须能够有效地合作。例如，如果工作涉及使用机器人根据其材料，尺寸或质量对产品进行分类，则必须首先对产品进行掌握，识别，评估和本地化。
When it comes to rule-based image processing systems, this is not only extremely time-consuming, especially in small batch sizes, but it is not really economically viable.
机器人以及基于AI的推断，可以配备有经验的工人所需的产品知识和专业知识。
可以公平地说，对于特定的子任务，不再需要技术开发的重大飞跃：简单地将正确的产品以跨学科的方式有效地一起起作用，因为“智能机器人视觉系统”就足够了。
Eyebot用例
在生产线中，物体倾向于随机分布在输送带上。然后，这些对象必须首先被识别，选择，例如，包装在包装中或发送到适当的电台以进行进一步处理或分析。
软件公司Urobots GmbH设计了一种基于PC的方法来指导机器人和检测对象。AI模型经过了广泛的培训，能够识别相机图片中对象的方向和位置，从中可以确定哪种握把最适合机器人。
这启发了下一个目标：将此解决方案调整到IDS成像开发系统GMBH的基于AI的嵌入式视觉系统。根据Urobots的说法，创建该解决方案时要考虑的两个最重要的因素是：
- 用户应该能够在没有任何特定的AI专业知识的情况下轻松地适应多个用例的系统。这意味着即使例如，与对象外观，照明甚至其他对象类型的集成之类的与生产相关的因素也被更改。
- 整个系统必须完全无PC，并在设备组件之间具有直接的连接，以使其既可以节省光线又节省空间，并且具有成本效益。
IDS已经为这两个先决条件提供了IDS NXT推理相机系统.
All image processing runs on the camera, which communicates directly with the robot via Ethernet. This is made possible by a vision app developed with the IDS NXT Vision App Creator, which uses the IDS NXT AI core. The Vision App enables the camera to locate and identify pre-trained (2D) objects in the image information. For example, tools that lie on a plane can be gripped in the correct position and placed in a designated place. The PC-less system saves costs, space and energy, allowing for easy and cost-effective picking solutions.
Alexey Pavlov, Managing Director, urobots GmbH
位置检测和直接机器通信
A trained neural network can recognize all of the items in an image and also their location and orientation. AI can even do this when there are a lot of natural variations, such as with food, plants, or even other flexible objects, and when there are fixed objects that generally look the same.
This results in an orientation recognition of the objects and a very stable position. The network was trained for the client by urobots GmbH using its own software and was then uploaded to theIDS NXT摄像头.
为了完成此操作阶段，必须将网络转换为独特的优化格式，该格式类似于类型的“链接列表”。
IDS NXT渡轮工具使将训练有素的神经网络移植到推理相机中非常简单。CNN网络的每个层都将成为一个节点描述符，在整个过程中精确定义了每个层。最终结果是CNN的完整串联列表，以二进制为代表。
CNN Accelerator IDS NXT Deep Ocean Core是专门为相机构建的，是基于FPGA的，然后可以最佳地执行此通用CNN。
The vision app built by urobots was then used to calculate optimal grip positions for a robot based on the detection data — but this did not offer a solution to the challenge. In addition to the results of what, where, and how to grip, direct communication between the IDS NXT camera and the robot was essential.
这项任务不被低估至关重要。这个决定通常是必须将多少钱，时间和劳动力的决定因素投入到解决方案中。为了将具体任务指令直接传输到机器人，Urobot使用摄像机的视觉应用中创建了一个基于XMLRPC的网络协议IDS NXT Vision App创建者.
AI Vision应用程序实现了+/- 2°的位置精度。它还检测到大约200毫秒的物体。
图1。The neural network in the IDS NXT camera localizes and detects the exact position of the objects. Based on this image information, the robot can independently grasp and deposit them. Image Credit: IDS Imaging Development Systems GmbH
无PC：不仅仅是人为智能的
It is not just the artificial intelligence that made this use case so intelligent. There are two more intriguing aspects that allow this solution to function without the need for an additional PC. The first reason is that, as the camera does not merely transmit images but also provides image processing results, the PC hardware and its accompanying infrastructure can be omitted.
当然，这降低了系统的购买和维护成本。通常在生产地点直接做出过程决策通常也很重要。因此，以下过程可以更快，毫不延迟地完成，从而使某些情况下时钟速率增加。
另一个有趣的方面是发展成本。AI视觉或网络培训尚未在通常的基于规则的经典图像处理方法中进行，该方法改变了图像处理任务的处理和接近。
结果的质量不再由图像处理专家和应用程序开发人员手动创建的程序代码决定。换句话说，如果可以使用AI来解决应用程序，则IDS NXT可以节省用户的时间和金钱。
这是由于用户友好且健壮的软件环境所致，它允许每个用户训练神经网络，构建相应的视觉应用程序并在相机上执行。
概括
This EyeBot use case has illustrated the future of computer visions: how they can become PC-less integrated AI vision applications.
There are other benefits to the modest embedded system, like expandability via the vision app-based notion, application development for diverse target groups, and end-to-end manufacturer support.
Eyebot中的能力有效地分布在应用程序中。用户的注意力能够专注于相关产品，而ID和Urobot可以专注于训练和运行AI以完成图像处理和机器人控制。
Another benefit is that the vision app may be readily customized for other objects, different robot models, and thus many other related applications using Ethernet-based communication and the open IDS NXT platform.
图片来源：IDS成像开发系统GmbH
This information has been sourced, reviewed and adapted from materials provided by IDS Imaging Development Systems GmbH.
For more information on this source, please visitIDS成像开发系统GmbH。