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

This Small Business Innovation Research (SBIR) Phase I project addresses the effort to design and prototype a new high-performance but low-cost integrated robotic manipulator comprising of the tight integration of mechanical, electrical, and computational subsystems. A significant part of the effort is to address the computational challenges involved in developing a new generation of intelligent robotic manipulators. Real-time general vision processing and dexterous planning, for example, are not feasible using conventional embedded processors. The consequence is that advanced robotic applications are only possible in environments where the robotic arm can outsource computationally expensive 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 robotic manipulator systems. Therefore a research effort is to develop a scalable high-level intelligence framework applied to robotic manipulators, and to implement robust and real-time algorithms that take advantage of highly parallel computing environments. Application computations will integrate seamlessly across wireless and wired networks of heterogeneous robotic and computer systems. The goal is a highly capable, computationally scalable, low-cost intelligent robotic arm platform for research 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-end robotic manipulators that have little commercial potential and the high-end robotic arms that are expensive and have high operating costs for setup and operation. High-performance computation integrated with advanced robotic manipulator systems are applicable for agile light industry and other desktop manipulator applications in unstructured environments. This will have a tremendous impact on the future of commercial robotics and make capable robotic systems affordable to small manufacturing businesses. Highly parallel computing power will greatly increase the range of applications and environments to which robots are suited. For example, an intelligent robotic manipulator can be used in agricultural applications or autonomously caring for plants in highly unstructured environments. The same manipulator could easily be adapted for use in a classroom setting; with a simple scripting interface students can experiment with advanced robotic control, allowing them to concentrate on discovering 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 lowpower HPC clusters applied to sensor network integration solutions in general.