Funded projects target the creation of next-generation collaborative robots, or co-robots, with applications in areas such as advanced manufacturing; civil and environmental infrastructure; health care and rehabilitation; military and homeland security; space and undersea exploration; food production, processing and distribution; assistive devices for improving independence and quality of life; and safer driving.

Examples of co-robots envisioned include the co-worker in manufacturing, the co-protector in civilian and military venues, and the co-inhabitant assistant in the home of an elder living independently.

Last year, NSF issued a solicitation and managed the merit review process for more than 700 individual proposals requesting more than $1 billion in funding. NSF’s Directorates for Computer and Information Science and Engineering; Engineering; Education and Human Resources; and Social, Behavioral, and Economic Sciences worked collaboratively with the other agencies. Together, NSF, NASA, NIH and USDA participated in the review process and in all funding decisions.

Each agency applied the goals of NRI against its mission criteria: encouraging robotics research and technology development to enhance aeronautics and space missions for NASA; developing robotic applications for surgery, health intervention, prostheses, rehabilitation, behavioral therapy, personalized care and wellness/health promotion for NIH; promoting robotics research, applications, and education to enhance food production, processing and distribution that benefits consumers and rural communities for USDA; and advancing fundamental robotics research across all areas of national priority for NSF, including advanced manufacturing.

Of the projects, NSF funded two specifically related to advanced manufacturing:

• The Intelligent Workcell - Enabling Robots and People to Work Together Safely in Manufacturing Environments. $690,000 to Carnegie-Mellon University.

  The research objective of this award is to investigate methods to enable people and industrial robots to work safely within the same workspace. Current robotic manufacturing practice requires the physical separation of people and robots, which ensures safety, but is inefficient in terms of time and resources, and limits the tasks suitable for robotic manufacturing. This research will develop an “Intelligent Workcell,” which augments the traditional robotic workcell with perception systems that observe workers within the workspace.

  Methods to explicitly track workers and estimate their body pose will enable dynamically adaptive safety zones surrounding the robot, thereby preventing the robot from injuring workers. Algorithms will be developed to recognize the activities that workers are performing. These algorithms will learn a task-independent vocabulary of fundamental action components, which will form the building blocks for a hierarchical activity recognition framework. Finally, mechanisms for providing feedback to workers about the robot's intended actions will be studied.

  This research is expected to provide new capabilities in robotic workcell safety and monitoring, allowing people and industrial robots to work safely and effectively in the same environment. Such capabilities would improve the efficiency of existing robotic workcells, since the robot would not be required to stop whenever a person enters the workspace (as is current practice). Furthermore, new manufacturing processes that involve robots and people working together on a single task would be enabled.

• Virtualized Welding: A New Paradigm for Intelligent Welding Robots in Unstructured Environment. $800,000 to the University of Kentucky Research Foundation.

  This project is to develop a new robotic platform with novel 3D modeling and visualization algorithms. An existing “dumb” welding robot will be augmented with sensors to observe the work piece, as well as its surroundings. New algorithms will be developed to record and reconstruct in 3D the welding process.

  The reconstructed data are transmitted to a control room and visualized with augmented reality techniques: A skilled welder can look at the welding process from different angles, as if he/she was right next to the actual welding system. Welding parameters can be adjusted by the human (with intelligence) and executed by the robot (with precision). More importantly, the adjustment, together with the reconstructed welding process, will be recorded and analyzed. System modeling techniques will be developed to correlate the human adjustment with the 3D reconstruction of the welding process. In this way, a welding robot can “learn by examples” the knowledge and experiences of a human welder and make similar intelligent adjustments by itself in the future.

  The primary use for this new technology is in manufacturing. Successful completion of the proposed project paves the foundation for intelligent welding robots with closed-loop intelligent control. Such a robotic system can perform high-speed and high-precision welding while allowing more variations in the work pieces and environments. In addition, virtualized welding can be integrated with a mobile platform to allow welding in places that are hazardous or unsuitable for human welders. The proposed welding extension platform will significantly expand the use of welding robots as well as reduce manufacturing costs.