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

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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.