In Europe, strategic funding happens when a need (or series of needs) is identified that has a potential robotic solution. A consortium is formed combining industry with educational research facilities. A roadmap is developed. Then the plan is funded by the government. Upon completion all the members of the consortium are privy to the resulting solutions. Similar strategic public-private partnerships exist in Korea and Japan. As these consortiums succeed, more are added to the pipeline. But not in the U.S.
There isn't a corresponding public-private process in most areas of American scientific discovery although the NSF and NIST have awards programs for targeted research in areas such as health care, energy, bio and nano technologies, and communications. Also, last month Pres. Obama outlined his forthcoming manufacturing initiative which may include some funding for robotics, but this initiative is an exception. All of these fundings are small in comparison to the need, thus the American funding solution tends to be through venture capital and charismatic entrepreneurs getting loans from family, friends and the SBA. This combo has worked in many, many areas of science. But robotics these days is multi-disciplined. Every robot is a collection of computers, engineering, electrical, mechanical, psychological, motion and vision algorithms, and software. They are a marvel, processing formulae and moving precision parts to do wondrous things, sometimes autonomously and other times interacting with computer networks, humans or other robots. The complexity and multi-disciplinary aspects of robotics cry out for project and funding management.
There are core metrics involved in worthwhile robotic projects. Metrics that ask necessary questions like whether there is a real business need; whether costs (including amortization of initial research costs) equals what would willingly be paid to satisfy that need; whether the solution proposed is one that correctly and fully solves the need better than other solutions; whether the research can be translated into a long-term commercially feasible solution; and defining the main obstacles and how can they be solved.
The latter (what are the main obstacles and how can they be solved?) is really interesting to a scientist; the former isn't. But the former is necessary to commercialize and pay for robotic science development. Which brings up CMU's strawberry project.
National Robotics Engineering Center (NREC) at Carnegie Mellon's Robotics Institute.
To maintain good strawberry yields, growers must replace their plants every year using manual labor to sort several hundred million nursery-grown plants into "good" and "bad" categories. They needed a precise, mechanized solution combining many sciences to accomplish their goal - and they were willing to fund that effort.
CMU's solution is a plant sorter that uses computer vision and software to classify strawberry plants into groups beyond the previous good and bad. Groups of sizes, varieties and stages of growth enable new efficiencies for co-op members helping them improve quality, streamline production and deliver better plants to growers (which, in turn, produce better strawberries for consumers).
During a 10-day field test in October, 2009 NREC engineers tested the strawberry plant sorter under realistic conditions, where rain and frost change plants’ appearance and roots may contain mud and debris. The prototype system had to sort plants of different varieties and levels of maturity. While in the field, it sorted over 75,000 strawberry plants. On average, it sorted 5,000 plants per hour, several times faster than human sorting. NREC hopes to achieve sorting rates of 20,000-30,000 plants per hour with the final system. While the sorter’s overall error rate was close to that of human workers, it inspected and sorted plants more consistently.There are three more phases to complete the strawberry project which include better methods to separate harvested strawberry plants, improve the equipment's robustness and ease of use, and integrate it into the nurseries' harvesting and packaging processes.
“That’s the beauty of it,” said one grower. “Hand sorting varies more and has more drift in quality.”
To me, this project is unique in that there are few American robotic projects initiated by corporations or business groups to solve a problem with robotics. UPS, GM and Ford, Deere, Boeing and Lockheed - have funded university research to solve their problems in the past. MIT has a small program enabling directed research. And NIST and the SBA fund selected projects. But NREC is to be congratulated for making Carnegie Mellon's Robotics Institute rich set of core capabilities available to industry to solve their strategic problems.