SBIR Phase I: Scalable Computer Clusters Applied to Sensing and Control of Intelligent Manipulators for Agile Manufacturing

这个小型企业创新研究(SBIR)第一阶段项目致力于设计和制作一种新的高性能但低成本的集成机器人机械手，包括机械、电气和计算子系统的紧密集成。这项工作的一个重要部分是解决开发新一代智能机器人机械手所涉及的计算挑战。例如，使用传统的嵌入式处理器，实时的普通视觉处理和灵活的规划是不可行的。其结果是，只有在机械臂可以将计算成本高昂的过程外包给更强大的计算机的环境中，先进的机器人应用才可能实现。低功耗、高性能计算(HPC)集群将用于扩展目前在自主和半自动机器人操作手系统中可能实现的功能。因此，研究开发一种适用于机器人的可扩展的高级智能框架，并利用高度并行的计算环境来实现健壮和实时的算法。应用程序计算将在不同种类的机器人和计算机系统的无线和有线网络中无缝集成。该项目的目标是为研究和轻工业提供一个高性能、可计算扩展、低成本的智能机械臂平台，该平台可以很容易地适应各种复杂的应用。该项目的更广泛的影响/商业潜力是填补低端机械臂和高端机械臂之间的市场空白，低端机械臂几乎没有商业潜力，高端机械臂价格昂贵，安装和操作成本较高。与先进的机器人机械手系统集成的高性能计算适用于敏捷轻工业和非结构化环境中的其他桌面机械手应用。这将对商业机器人的未来产生巨大影响，并使小型制造企业能够负担得起有能力的机器人系统。高度并行的计算能力将极大地增加机器人适用的应用范围和环境。例如，智能机器人机械手可以用于农业应用或在高度非结构化环境中自主照料植物。同样的机械手可以很容易地改装成在课堂上使用；通过一个简单的脚本界面，学生可以试验先进的机器人控制，使他们能够专注于发现令人兴奋的新应用。这在学术和工业环境中创造了广阔的市场，无论是用于敏捷制造的高性能、低成本智能机器人机械手，还是一般应用于传感器网络集成解决方案的低功率HPC集群。

This Small Business Innovation Research (SBIR) Phase I project addresses the effort to design andprototype a new high-performance but low-cost integrated robotic manipulator comprising of the tightintegration of mechanical, electrical, and computational subsystems. A significant part of the effort is toaddress the computational challenges involved in developing a new generation of intelligent roboticmanipulators. Real-time general vision processing and dexterous planning, for example, are notfeasible using conventional embedded processors. The consequence is that advanced roboticapplications are only possible in environments where the robotic arm can outsource computationallyexpensive processes to more powerful computers. Low-power, High-Performance Computing (HPC)clusters will be used to extend what is currently possible in autonomous and semi-autonomous roboticmanipulator systems. Therefore a research effort is to develop a scalable high-level intelligenceframework applied to robotic manipulators, and to implement robust and real-time algorithms that takeadvantage of highly parallel computing environments. Application computations will integrateseamlessly across wireless and wired networks of heterogeneous robotic and computer systems. Thegoal is a highly capable, computationally scalable, low-cost intelligent robotic arm platform forresearch and light industry, which can easily be adapted to a variety of complex applications.The broader impact/commercial potential of this project is to fill a market niche between the low-endrobotic manipulators that have little commercial potential and the high-end robotic arms that areexpensive and have high operating costs for setup and operation. High-performance computationintegrated with advanced robotic manipulator systems are applicable for agile light industry and otherdesktop manipulator applications in unstructured environments. This will have a tremendous impact onthe future of commercial robotics and make capable robotic systems affordable to small manufacturingbusinesses. Highly parallel computing power will greatly increase the range of applications andenvironments to which robots are suited. For example, an intelligent robotic manipulator can be used inagricultural applications or autonomously caring for plants in highly unstructured environments. Thesame manipulator could easily be adapted for use in a classroom setting; with a simple scriptinginterface students can experiment with advanced robotic control, allowing them to concentrate ondiscovering exciting new applications. This creates a broad market in academic and industrial settings,both for highly-capable, low-cost intelligent robotic manipulators for agile manufacturing and for lowpowerHPC clusters applied to sensor network integration solutions in general.