The first real world trial in the DARPA Robotics Challenge (DRC) will be held on December 20-21 2013 at Homestead Freeway in Florida. Yes, it’s open to the public. Anyone can come along and watch humanoid robots try to perform difficult disaster relief human type tasks. This is the geekolympics, it’s nerdvana. Honestly, it’s like sport only better. Here’s the basic background and the rundown on the top teams.

The DRC was inspired in part by recent disasters like Fukushima. In the DRC 2013 trials, the robots will need to perform disaster response operations such as driving a utility vehicle, traveling dismounted across rubble, removing debris from doorway, opening doors, climbing ladders, using power tools, locating and closing valves near a leaky pipe and connecting and using a hose. Connectivity with the robot may also be compromised during the Challenge. Simple tasks for a human but very very difficult for a humanoid robot.

BACKGROUND

DARPA’s Grand Challenges are designed to speed up important research in an area that has been previously difficult but has the potential to provide great changes. The idea of a grand challenge has a long history. Great achievements have come from competitions for centuries, from the invention of the pocket watch for longitude calculations to Lindbergh’s transatlantic flight, from the introduction of the potato to the development of canning.

The rapid progress we’ve seen in driverless cars in the last decade owes everything to the last DARPA Grand Challenge. In 2004, DARPA held the first autonomous vehicle grand challenge, offering $1million prize money for a vehicle that could complete a 150 mile desert course. In 2004, the best result was 7.32 miles from the CMU team. DARPA offered a $2million prize for a repeat challenge in 2005 and this time all but 1 of the 23 finalists travelled further than 7.32 miles and 7 teams completed the course.

In 2007, the Grand Challenge was relaunched as an urban environment challenge. Eighty-nine applicants were whittled down to 35 contenders. Six teams successfully finished the course. By 2011, driverless vehicles were a commonplace sight on the 101 near Google HQ, with no reported accidents. That’s less than 10 years from zero to 65mph on the freeway.

Now we’re about to see the first real trials of the DARPA Grand Challenge for humanoid robots. Or at least for robots capable of working in a human environment. They don’t have to look humanoid but most of them do. In July of 2013, the first round of simulated trials was held to winnow down the 26 teams from 8 countries who had qualified to compete in the Gazebo VRC simulated environment.

”The reason we had this virtual challenge is that we wanted to open the contest to teams whose strength is primarily software,” said Dr Gill Pratt, DRC Program Manager.

After successfully completing 3 simulated disaster response tasks using Gazebo, the finalists should be able to transition their algorithms to ATLAS robots, built by Boston Dynamics for the physical DRC. The open source simulator will be an ongoing legacy for the robotics community, according to Brian Gerkey, the CEO of OSRF, the Open Source Robotics Foundation.

“The simulation work that we’re doing is really part of a broader effort to build a common ecosystem of software tools and libraries that everyone can use.” said Brian Gerkey, OSRF, in an earlier article on Robohub.

MEET THE TEAMS

The competing teams are either Track A; funded teams who are building their own robot and have passed various evaluations and reviews. Track B/C; funded/unfunded teams who successfully qualified in the simulator rounds (VRC) and have been given an ATLAS robot for the trials. And finally, Track D; unfunded teams from anywhere who have a humanoid and aren’t afraid to test it. The qualifying teams in the 2013 round will go on to compete again in December 2014, performing the same type of tasks, but with greater difficulty.

TRACK A

CHIMP
	CMU-NREC proposed to develop the CHIMP (CMU Highly Intelligent Mobile Platform) robot for executing complex tasks in dangerous, degraded, human-engineered environments. CHIMP will have near-human form factor, work-envelope, strength and dexterity to work effectively in such environments, yet avoid the need for complex control by maintaining static rather than dynamic stability.
Pittsburgh, PA	CMU Carnegie Mellon University | NREC National Robotics Engineering Center
Hubo
	Drexel University’s design focuses on a mature, open-architecture, bipedal robot call Hubo. Each member on Drexel’s team will be equipped with a stock Hubo, a complete, full sized humanoid. This infrastructure will catalyze a multi-university effort to “hit the ground running” and successfully address all anticipated DRC events in a “program-test-perfect” model.
Philadelphia, PA	Drexel University
RoboSimian
	JPL proposed to build RoboSimian, an apelike bio-inspired, limbed robot that will use deliberate and stable operations to complete challenging tasks under supervised teleoperation. The team, which includes contributions from the California Institute of Technology, Pasadena, Calif., Stanford University and the University of California, Santa Barbara, will employ design methods, system elements and software algorithms that have already been successfully demonstrated in JPL’s existing robots.
Pasadena, CA	Jet Propulsion Laboratory
Valkyrie
	NASA Johnson Space Center proposed to develop a next-generation humanoid robot and control paradigm capable of performing dynamic, dexterous and perception-intensive tasks in a variety of scenarios. NASA JSC’s development approach will apply successful practices that have been used to develop multiple generations of Robonaut and related technologies in collaboration with academic, commercial and other government partners.
Houston, TX	NASA Johnson Space Center
HRP-2 based biped
	SCHAFT Inc. proposed a bipedal robot based on mature hardware and software designed for its existing HRP-2 robot. SCHAFT will create an Intelligent Robot Kernel in which it will combine the necessary software modules for recognition, planning, motion generation, motion control and a user interface. The group will divide into three teams to execute the tasks: hardware design, software integration and scenario testing..
JAPAN	SCHAFT Inc.
THOR-OP
	Virginia Tech proposed to develop THOR, a Tactical Hazardous Operations Robot, which will be state-of-the-art, light, agile and resilient with perception, planning and human interface technology that infers a human operator’s intent, allowing seamless, intuitive control across the autonomy spectrum. The team will emphasize three essential themes in developing THOR: hardware resilience, robust autonomy and intuitive operation.
Blacksburg, VA	Virginia Tech

Here’s a short video of all the Track A teams in action:

TRACK B/C (with ATLAS robots)

Team IHMC
	The IHMC team is confident it has an innovative approach to combine the cognitive abilities of humans, computational power, and the physical abilities of robots to handle novel situations in a new way.
Pensacola, FL	Florida Institute for Human and Machine Cognition
WRECS
	Team WRECS strives to foster a dedicated and well-managed team, composed of students, professors, and professional engineers, collaborating to discover and lead the state-of-the-art research enabling advanced human-level performance for the Atlas humanoid. We aim to publicly demonstrate the successful completion of tasks related to major disaster response with the intent of leading to relevant peer-reviewed publications, credibility for future DARPA solicitations, and the ultimate goal of winning the DARPA Robotics Challenge.
Worcester, MA	WPI Robotics Engineering C Squad (WRECS) Worcester Polytechnic Inc
MIT
	The MIT team, based at CSAIL, is drawing on research that is underway in several MIT departments and labs. For example, Teller’s own research group is developing methods that make it possible for robots to interpret sensor data, allowing them to make sense of their surroundings and understand their movements. They are also creating human-robot interaction methods by which humans can help robots formulate and carry out plans. State-of-the-art, real-time planning and control methods that are being developed in Tedrake’s lab make it possible for humanoid robots to balance, walk and climb.
Boston, MA	MIT Massachusetts Institute of Technology
TRACLabs
	Over the past 15 years, TRACLAbs has used its 3T robot intelligence software to program robots to search for, find and recognize people, to recognize a user’s gestures to carry out tasks, to perform inspection tasks for the International Space Station, to hunt for mines underwater, and to form teams with humans to carry out repair and replacement tasks on earth or in space. We have also extended our approach to intelligent robotics to include graphical and natural language interfaces. So users of TRACLabs robots can motion-to, speak-to or just point-and-click the robots into action.
Webster, TX	TRACLabs
ViGir (Virginia-Germany Interdisciplinary Robotics)
	TORC engineers have been part of both the DARPA Grand Challenges and the Urban Challenge, where TORC led the software development VictorTango’s 3rd place finish. With two RoboCup world championship titles in autonomous humanoid robot soccer and two RoboCup Best-in-Class Autonomy awards for search and rescue robots, TU Darmstadt adds significant expertise in humanoid and rescue robotics to the team. The team will leverage experience from Virginia Tech’s Center for Human-Computer Interaction (HCI) – a world leader in design and research of novel HCI concepts – and winner of three straight 3D User Interface IEEE competitions. Oregon State will provide expertise in human-inspired robotic grasping and manipulation.
Blacksburg, VA	Torc Robotics | TU Darmstadt | Virginia Tech | Oregon State University
TROOPER
	“Our team’s software solution controls a robot in a state of ‘supervised autonomy,'” said Bill Borgia, director of Robotic Systems at Lockheed Martin ATL. “This means a robot completes simple tasks independent of the operator. Then, if there’s something tricky the robot can’t work independently, a remote, and largely untrained, operator will step in and assist.” Lockheed Martin ATL is partnered with Rensselaer Polytechnic Institute (RPI) and University of Pennsylvania (GRASP Lab) for the effort.
Cherry Hill, NJ	Lockheed Martin | University of Pennsylvania | Rensselaer Polytechnic Institute
Team HKU
	“It is a significant accomplishment for our new initiative to produce a team that made it into the top 10 worldwide in its first attempt,” said Professor Norman Tien, HKU Dean of Engineering. “It is encouraging to note that researchers from the US, Japan and partner institution like the university of Edinburgh will join hands with HJU Team in developing advanced and sophisticated software, ie. cultivating a brain for the robot,” he added.
Hong Kong	Hong Kong University | Team K Japan | Case Western University

The ATLAS robot is based on the Petman humanoid robot platform and has been specifically developed by Boston Dynamics for teams in Track B/C of the DRC. ATLAS is a hydraulically powered robot in the form of an adult human. It is capable of a variety of natural movements, including dynamic walking, calisthenics and user-programmed behavior. ATLAS has:

• Near-human anthropometry
• 2 arms, 2 legs, torso and head.
• 28 hydraulically actuated joints with closed-loop position & force control
• On-board real time control computer
• Electric power & network tether
• On-board hydraulic pump & thermal mgmt
• Crash protection
• Modular wrists accept 3rd party hands
• Head-mounted sensor package with LIDAR, stereo sensors, dedicated sensor electronics and perception algorithms.

TRACK D

There will also be Track D teams who are unfunded and have built their own robots. Registration for Track D has now closed and DARPA have qualified 4 teams based on video footage of 3 tasks being attempted at the end of October.

Buddy
	Team Mojavaton developed an autonomous NISSan Xterra that finished in 13th place (out of 195) in the 2005 DARPA Grand Challenge. Now the self-funded, small but highly passionate and dedicated team of undergraduate students, professors and professional engineers take on the DRC with Buddy. Buddy features 34 electric servo motors that enable him to walk and use his two arms and hands. Buddy is special in that he’s a quadruped not a biped and we’ve made extensive use of 3D printing to build him, so that he’s a lot lighter than many of the other robots. While he’s only 4’8″ tall, his full wingspan is 6′.
Grand Junction, CO	Team Mojavaton
CHIRON
	Simple static motion and manipulation is very useful in tasks that require precision and reliability. The Chiron hexapod design gives great dexterity to travel over uneven terrain as well as stable manipulation. The majority of our team members have been focused primarily on hardware component creation, while a smaller number of team members have been focused primarily on software development. Team Chiron has benefited from numerous technology vectors produced by Kairos Autonomi.
Salt Lake City, UT	Team Kairos Autonomi
Intelligent Pioneer
	We divided the team into 6 groups, each one is responsible for a subsystem, and the subsystems include integration, machinery, controlling, perception, interaction and environment modeling. Software d and hardware are developed independently. Software in all subsystems is running under ROS architecture.
tbc	tbc
DRC-HUBO
	We separate team to develop basic technologies for tasks and each team conquer tasks. 1. Hardware and software Platform: Rainbow Co. 2. Vision: KAIST 3. Motion: KAIST and Rainbow Co. Each teams are involved to each task 1. Walking: SeoulTech and Rainbow Co. 2. Wall: Rainbow Co. 3. Other tasks: KAIST
Daejon Metro City, KOREA	Team KAIST
WATSON (not progressing to next round)
	Our biped WATSON (Without A Tether Stereoscopic OmniNavigation) was started 6 years ago, but early versions had trouble walking. We have since worked on the two major design areas that allow WATSON to walk and balance. We are now working on a neural net with our smaller platforms that will enable WATSON to learn to walk from the smaller platforms successes while avoiding mistakes with a larger heavier and more expensive robot.
Silicon Valley, CA	Team Walk Like A Man | Daniel Albert, Chris Mayer

Welcome to a wonderful month of robotics. Full reports on the DARPA Robotics Challenge (DRC) are on the DRC website.

Based on a media rountable discussion with DRC Program Manager Gill Pratt and CEO of the Open Source Robotics Foundation Brian Gerkey.

The Fukushima Daiichi Nuclear disaster was a wake-up call to the robotics community. In Japan, many asked why a country known for its cutting-edge robotics sector was unable to respond to the emergency. Worldwide, robotics experts pointed to the event as a real-world test of what robots can and cannot do.

Whether man-made or natural — or like Fukushima, a combination of the two — major catastrophic events, while rare, are becoming increasingly costly as human populations worldwide move to urban areas. This is why, in an effort to spur the development of agile humanoid first-responders, the US Department of Defense’s strategic plan identifies disaster response as a priority area, and why it is funnelling tens of millions of dollars into the DARPA Robotics Challenge.

DRC Program Manager Dr. Gill Pratt envisions a future where tele-operated robots can be quickly deployed by disaster-response personnel with minimal robotics training: “In Fukushima, during the first 24 hours, the explosions would not have occurred if it would have been possible to vent the reactors,” said Pratt in a media round-table last month. “Human beings tried to do this but had to turn around [because of the radiation]. Our hope is to develop machines that can actually intervene and help make a disaster [like this one] less severe.” Estimates of the total economic loss due to the Fukushima disaster range from $250B – $500B US.

Why a humanoid?
Though having a robot that can safely navigate dangerous places like the inside of a nuclear plant is no-doubt useful, one has to question whether the extreme cost and design challenge of developing a humanoid that is capable of doing so is worth the effort. Yet as Pratt points out, a disaster scenario that is catastrophic to humans is also most likely to occur in an environment that has been engineered for humans, and what kind of robot would be more capable of navigating in a human environment and using the tools found there than a humanoid?

As DARPA project leaders were designing parameters for the Robotics Challenge, they consulted with first-response experts — including the Nuclear Regulatory Commission — and identified key capability requirements that indeed seem to point to a humanoid solution: the ability to go through doors, climb steep stairs, walk on rough terrain, and the ability to use whatever tools are oh hand, such as a utility vehicle or a screw driver.

“Our belief is that we will never know where the next disaster is going to hit and when it will be, and so we have to be prepared to use whatever tools are on hand,” said Pratt. “And at least for the foreseeable future, those are tools for people to use, and so we need to adapt our machines to use those tools as quickly as possible.”

Designing a roadmap for success
DARPA does not define the success of its programs through a profit and loss model, and its goal with the DARPA Robotics Challenge is not to bring a humanoid first-responder to every fire station in the country. As a government agency, DARPA focuses on bringing high-risk technologies to the point of prototype, and then handing these off to the military or commercial sector for development. It invests in challenges such as the DRC in order to spur radical innovation, and short-term technical failure is OK as long as the long-term potential payoff is high.

But despite these lofty goals, the question remains: what’s the roadmap for designing and overseeing a major robotics challenge such as this one? How does one gauge success when the potential payoff may be decades or more away?

DARPA’s previous autonomous car challenges offer some lessons, and one of them is that there isn’t always a winner.  Pratt admits that success for the DRC isn’t guaranteed, but says that the goal of the competition isn’t so much to declare a winner as it is to continually nudge the competitors towards greater achievements, while at the same time being realistic about what is actually doable. As a result, DARPA will be reevaluating the project’s milestones and adjusting the difficulty of the tasks in consultation with the participants along the way.

Previous autonomous car competitions are different from the current challenge in one major aspect, however: the older competitions were based on automotive technology, which already had a significant infrastructure in place. The robotics industry, by comparison, is still in its infancy, and so a great many hurdles exist for competitors, both at the software level and at the hardware level, and in terms of integration. Pratt has thus broken the competition down into three stages and four separate competitor tracks in an attempt to structure what is otherwise an extremely open-ended problem. (You can find a good explanation of how the competition breaks down on DARPA Robotics Challenge Fact Sheet.)

The first stage of the DRC — the Virtual Robotics Challenge (VRC) — offers particular insight into DARPA’s strategy for success. The VRC, for which the results were announced earlier this month, was a cloud-based competition designed to test software, and its goal was to evaluate the teams’ robot perception, manipulation and locomotion in a virtual environment as a first step before moving on to the physical trials, which will take place in December of 2013. The big idea here is that teams will be able to try out their strategies in simulation first, before investing in hardware. “The reason we had this virtual challenge is that we wanted to open the contest to teams whose strength is primarily software,” said Pratt.

DARPA’s simulator models real-world physics and behaviours with incredibly high accuracy. Brian Gerkey, CEO of the Open Source Robotics Foundation (OSFR), the organization behind the VRC simulator, says that their goal is for the simulation to be the best possible stand-in for the real robot, so that teams that have done well in the VRC should be able to run their software virtually unchanged on the physical robot during the trials. And yet run to such a complex simulation — and to play that simulation back at interactive rates — takes a huge amount of computer power.

“One of the key developments over the past several years has been the advancement of cloud computing resources,” explained Gerkey. “It’s now possible to rent access to cloud computing resources so that you can have modest computer at your end and have the simulation run somewhere else. That’s a key aspect of this project and it’s really required in order to run the competition.”

The seven winning teams from the VRC challenge each received an Atlas furnished by Boston Dynamics for use in the DRC trials, where they will compete with other funded and unfunded teams that have been developing their own hardware (see DARPA’s Meet the Teams video to get a sense of what Atlas will be up against). They now have until late December to transfer their software algorithms to the Atlas hardware shell, and practice running a real machine in real environment. The physical trials should be a good demonstrator of the success of the simulator approach to competition design.

Building a legacy
DARPA takes a long view to technology development, starting with identifying a major national security need (in this case: disaster response), then determining the specific technologies and innovations needed to address that need (in this case: easily deployed agile humanoid robots), and finally working to support the fundamental breakthroughs required to make these technologies possible. DARPA’s disaster challenge is thus about creating infrastructure to support long-term software and hardware development in the robotics community; it’s also about attracting bright minds to solve some of the world’s most pressing problems.

One of the legacies of the VRC is that all the software code for the simulator is being distributed open source, and so, as Gerkey points out, there is no cost to reuse it later.

“The history of software development has shown that this is the best possible, most efficient development model for building the common platform that a whole community comes to rely upon,” says Gerkey. “The simulation work that we’re doing is really part of a broader effort to build a common ecosystem of software tools and libraries that everyone can use. There are computers that are powerful enough to run this simulation that you can rent for on the order of a couple of dollars an hour.”

The hope is that, ultimately, the open-source VRC simulator will help speed up the development of robots in general by lowering the barrier of entry and that this, in turn, will lead to more capable robots – perhaps ones capable enough to be of service in a Fukushima-like disaster. Says Gerkey: “Once we can run this very realistic simulation in a competition, we can then try this in a classroom scenario. You don’t have to outfit your classroom with expensive powerful computers.”

Pratt agrees: “Right now we have a few really talented designers and a few companies that are beginning to be strong in the robotics field. We would like to see those numbers go way up, and we believe that the way to do it is to give people a tool to develop these machines without having to incur the cost of first building them.”

Fostering international cooperation
Fukushima is used as an example to motivate the need for robotic platforms in dangerous environments, and the VRC is being promoted as an internationally beneficial endeavour, so I asked Pratt what specifically is being done to foster international cooperation, and whether there was a possibility that DARPA would work with other countries on future challenges.

Pratt answered that a key measure for success in this project is engagement with the international community. “All the code that we’re writing is distributed under the Apache 2 licence which is a very permissive open source license that allows anyone in the world to do anything that they want with this software. We would love for the challenge (once we are done with it in the next year and a half) to move around the world, and we have been in discussions with our counterparts in Japan and the EU about the possibility of this becoming a rotating contest. We think that [making societies more resilient to disasters] is a need that the whole world has, and so and I’m spending quite a lot of my time having lots of discussions about what the future of this is going to be once we are done … I personally think that the international part of this is a key way to measure how well we have done, so if we’re successful in having the DRC continue on somewhere else in the world, then it will be clear that we have done well.”

Though Pratt hesitates to predict how long it will be before we have robots capable of helping out in situations such as the one in Fukushima, he is convinced that DARPA’s Robotic Challenge will result in some major developments for the field:

***

More info:

DARPA Robotics Challenge Website
DARPA Robotics Challenge Fact Sheet

Look out for DRC trial coverage in December!

A week ago the DARPA Robotics Challenge unveiled the ATLAS humanoid robot, which will be used by seven competing teams. Developed by Boston Dynamics, ATLAS is an imposing 1.8m 150Kg bipedal humanoid robot, powered via a tethered cable. Another six teams have designed their own robots, and interestingly five of these are humanoid, and one a four-limbed simian-inspired robot.

In the euRathlon project we are taking a different approach in that we don’t expect, or require, the competing robots to be humanoid or zoomorphic. None of the euRathlon competition scenarios demand a humanoid robot to, for example, be able to step inside a vehicle and drive it. However, for the land robots at least, there is nothing stopping euRathlon teams from bringing humanoid robots to the competition.

As I wrote when we launched euRathlon early this year, the big vision of euRathlon is a competition scenario in which no single type of robot is, on its own, sufficient. Inspired by the Fukushima accident of March 2011, the 2015 euRathlon competition will require teams of land, sea and flying robots to autonomously cooperate, survey the scene, identify critical hazards and undertake tasks to make the plant safe. Leading up to this grand challenge in 2015, will be related and preparatory land and underwater robot competitions in 2013 and 2014, respectively.

The difference of our approach is not the result of an in-principle decision. Rather, it flows naturally from several factors. First, we are specifically creating competition scenarios that require cooperating teams across the three domains of land, sea and air. Second, we are looking for very high levels of autonomy, so the robot teams will, ideally, complete their mission with hands-off human monitoring only. Any human interventions will be penalised in the euRathlon scoring schema. And third, we are not looking to push innovation in the robot platforms themselves, but rather in their cognition, autonomy and system level team working. Thus, euRathlon teams who make use of existing and proven robot hardware will gain a big advantage in that they can focus all of their efforts on the software, communications and systems engineering; the AI and the autonomy. And by autonomy we mean both control and energy autonomy. The euRathlon competition scenarios preclude the use of tethered power connections, so robots must carry their own energy supplies sufficient to last the whole mission.

For these reasons the euRathlon robots are likely to look rather conventional: wheeled or tracked land robots; fixed or rotary wing (i.e. quadcopter) flying robots, and ROV-type underwater robots. Not as dramatic as the DARPA robot challenge humanoid or animal-like robots perhaps, but looks can be deceptive: the real innovation in the euRathlon robots will be in the autonomous cooperation across the three domains. Something that has not been demonstrated in realistic outdoor disaster response scenarios.

Of course there is nothing to stop euRathlon teams from using a bio-mimetic approach, so fish-like underwater robot cooperate with bird-like flying robots, and legged animal-like land robots. That really would be something!

Related blog posts:
euRathlon is go! (Feb 2013)
Real-world robotics reality check (May 2010)
A truly Grand Challenge (August 2007)

Over the last 20 years or so, a sense that science has become conservative or incrementalist has developed, and calls for change in the approaches to public funding of research have been heard from various quarters. Several notions have been suggested of what should be supported instead of “normal science” or “incremental innovation.” Among them we have heard calls for more “high risk-high reward” research, or for more “highly creative” science, or for more “cutting edge” or “frontier” research and, more recently in language adopted by funding agencies, that more “transformational research” is needed.

The main idea is that there isn’t enough risk taking, and little scientific or technological creativity is reflected in proposals that might “revolutionize” our understanding of the nature or society. “Business as usual” in the support of science and technology seems not to be satisfactory for producing the sort of radical change and rapid advance in science needed to solve important problems we face in economic development, health care and general social wellbeing.

This discussion does not fully address the situation in the private sector. However, the fate of many top-performing R&D centers in companies such as IBM, Texas Instruments, AT&T, among others, over the same period indicates that corporate willingness to take risks in research is not precisely at its most adventurous. Having said that, our focus here is on public funding since the sense of risk and reward of innovation by private industry in the market does not have the severe principal-agent problem faced by public funding. Companies invest their own money and either lose it or make a profit for themselves. Researchers funded by government do not lose their own money in the risk taking. The government takes virtually all the risk, at least in the financial sense.

When it comes to radical innovation in robotics, this distinction about risk taking must be kept in mind. In any case, the participation of the public sector in the development of robotics technology has the purpose of reducing the risk for private companies that, without at least partial subsidies from government, would not have a safe enough business case to get involved. This is the well-known market failure justification for public support of R&D.

In the context of public funding, the capacity of the government to take on R&D risk is not infinite. And moving from the intuition on the desirability of more scientific and technological breakthroughs to a clear understanding of how it would be recognized, what exactly is the difference between incremental research and proposals for future scientific revolutions, and what the proper incentive and support mechanisms are for it has proven difficult. It is not clear what in the research process has the attribute that is looked for. Is it the projects that are special? Are certain scientists capable in a different way? Is it the organization that can provide an unusual environment for research? Or is it groups of projects, that is, portfolios that must be assessed for their combined effects? So far, none of these questions has a clear answer.

Models, Metaphors, Analogies to Produce Meaning
One way to begin to clarify the problem is to take the models that are being used either implicitly or explicitly to suggest courses of action. We have identified at least four that have appeared repeatedly in documents and speeches about the “special” research that might have higher impact. They work as analogies for highlighting one or more important attributes or their consequences. These are the models of stock investment portfolios; biological evolution; “hot” trends; and exploration of the wild.

Stock Investment Portfolios
Many calls to support more “high risk” research that has the potential to offer “high reward” appeal to the intuition of investment risk. In this analogy, each project that is up for support is similar to a stock considered for inclusion in an investment portfolio. As in stock portfolios, a balance of risk is sought across the portfolio so that a number of safer bets compensate for riskier ones that might payoff disproportionately.

The important implication of this perspective on research support is that the unit is the project and that each one is assessed in comparison with the others in the portfolio. The overall balance of risk of a good portfolio means that projects are not selected on the same criteria. Some will be “good” low risk projects to compensate for potential losses of the high risk ones. This is clearly not current practice in public funding of research since all projects are assessed on the same criteria and only the best are funded. All projects have approximately equal risk.

There are a few consequences that must be given further thought. First, what attribute of projects must be risk assessed on? Are risks across disciplines considered, for example? Or are risks across organizations or types of projects? No clear answer to this question has been offered. Second, how much failure will be tolerated? If risk is real, then high risk means high probability of failure and a high failure rate should be observed. Otherwise, the risk is not as high as it was assumed. No clear answer for this question is available either. Much talk about “high risk-high reward” is superficial and really suggests that most high reward projects could be identified with some special assessment mechanism without a high risk of failure. Actual failure would probably be pinned on the proposal assessment mechanism rather than the risky nature of the projects.

Evolution in Science
This analogy implies that new ideas in science appear much like genetic mutations do in living organisms. If our selection mechanism allows for the more radical mutations to survive, more radical change in science would probably follow. Most attention has been drawn to the selection mechanisms, assuming implicitly that the size of the pool of variation for the chance of selecting viable large jumps is sufficiently large.

The consequences of this line of thinking are also intriguing. First, the necessity of a random generation of variation in scientific ideas is not a familiar one. The image of a rational scientific method has a strong cultural effect of keeping random idea generation hidden from view, if not largely muted. In other words, attention would have to be put on the environment that allows for a large pool of very diverse scientific ideas to emerge continuously in order to have large jumps that might be selected. Secondly, a large measure of randomness in the consideration of scientific ideas would have to be acceptable to the establishment. Otherwise, just as the reduction in biological diversity is a serious problem for environmental health, there will be very little to select from to have many “viable new scientific organisms.”

Hot Trends in Science
Science is not different from other cultural phenomena in that novel trends generate “icons” and “hits” that the community rallies around. As a matter of fact, many new ideas in science and technology are followed during the first period of their public diffusion to assess whether they are substantive or only a fad. It is often heard of researchers gaining prominence in their fields that they are new “stars” or that they are “hot.” These trends and their icons attract a following, and researchers that join the movement fashion their professional identity around the key features of the emerging field.

The main lesson to drive home from the analogy is that this cultural phenomenon is an integral part of science even if it is not formalized into the assessment of proposals and projects. Individual projects are not the main focus. The “movement” is the main concern. But, how does the perception of a hot trend and its icons affect the assessment of project proposals that promise to continue in its wake? How does the system deal with the possibility of a fad that wastes energy and resources on a trend that does not pan out? A rapid recognition mechanism to tease out indicators of faddish elements seems to be necessary to address this issue. But this would be a “conservative” reaction. Should the system be more liberal in embracing hot trends to avoid killing off potential revolutionary developments? This would be another type of risk that might have to be accepted. With its acceptance comes another departure from a common view of rational science that looks askance at enthusiasm and bandwagon effects as illegitimate passions. Maybe science should have a few “moments of madness”.

Exploration of the Wild (or the Endless Frontier)
The idea that science is a sort of exploratory venture into the unknown unexplored regions of nature is an old one. It was made into influential policy discourse by a prominent scientist in the aftermath of World War II: Vannevar Bush. It assumes that what we don’t know is contiguous with what we know, and we just have to “venture out” into this unexplored territory to get to know it. The only difference between conservative, incremental science and the highly creative or transformational research is that the exploratory journey should go deeper and farther into the unknown in one single expedition.

This image suggests that the main way to achieve sizable leaps to advance science is by organizing well-equipped and supported expeditions into unexplored territory. The skeptics in policy making recognize immediately that this analogy suggests that research always requires more funding: “If you give us more money, we can go deeper into the unknown.” This was already recognized as a subtext of the original idea of the “endless frontier.” Risk is downplayed in this analogy. Only underprepared expeditions are risky. There is always unknown territory to discover. The question is rarely raised that there may be little of value in vast regions of the unknown.

A Path Forward?

It seems that before we can define a path forward it is necessary to come to terms with the full consequences of what must be achieved. First, the simple formula of “high risk-high reward” hides the complexity of the goal. There are many interrelated issues that must be addressed simultaneously if this objective will be pursued with a committed effort. A simple set of criteria for evaluating proposals will not do the job. Second, a part of the public image of science as a highly rational activity is tied to the status quo of low risk incremental change in science. Higher risk and randomness that seem to be inherent in increasing the magnitude of change in science may open the enterprise to criticism and loss of legitimacy because of an appearance of irresponsible gambling with public resources. The idea is that the payoff of a few initiatives that succeed will compensate for many that fail. Is there any publicly supported system in today’s political environment that can operate legitimately under those conditions? Not likely.

The DARPA Robotics Challenge has an interesting approach to encourage the pursuit of “leaps forward” in the development of these technologies while reducing how much risk it takes on at any point in time. It does so with two crucial measures. First, it specifies a well defined target of technological capabilities. So, in terms of the metaphors we used, it is not looking at the entire evolutionary environment of technology or at the entire frontier of technology. It limits how much randomness must be accepted and how far into the unknown it may be necessary to travel before something of value is shown. Second, by making several teams compete in stages and granting a limited amount of funding to compete in progressively more difficult challenges, it reduces potential losses and requires the return of something of value before more risks are taken. At most, no team will advance to the next stage, so what has been granted will be lost, but it cuts its future losses as soon as nobody can show progress. However, the risk of pursuing those technological objectives rather than others has not been mitigated, and the stages might cut losses too early.

For this reason, in fields where objectives cannot be specified with such clarity, program design is more difficult. But the lesson remains. As the DARPA program shows, the flexibility may have to be transferred to the very support mechanisms themselves. Attempting to derive a fixed set of procedures and criteria to identify and support something that is highly variable, with an irreducible measure of randomness, culturally unstable and insatiably adventurous may be the wrong path to go down. The criteria and support mechanisms may have to become “experimental” themselves. The future development of scientific and technological research may be pressing for some institutional change.

The first competition of the DARPA Robotics Challenge (DRC) was a software simulation of humanoid rescue work. The 6 best teams were to be allocated ATLAS robots for the next stage of the challenge, but there’s been an interesting change. Gill Pratt, the DRC program manager, and Nate Koenig, the CTO of OSRF, will be on reddit from 1:00 – 2:00 PM ET today (June 27) to discuss the results of the Virtual Robotics Challenge (VRC) and the future of the DARPA Simulator with the community.

In the Virtual Robotics Challenge (VRC), teams competed in a simulated suburban obstacle course. Twenty-six teams from eight countries qualified for the VRC, which ran from June 17-21, 2013. Competing teams applied software of their own design to a simulated robot in an attempt to complete a series of tasks that are prerequisites for the next stages of the grand challenge.

Gill Pratt: “The reason we wanted to have this virtual challenge is that we wanted to open the contest to teams that were strong not just in both building hardware for robots and programming them with software, but to include a wide variety of teams including those that had experience with just software. So for those teams whose strength is primarily software, we are having this contest in simulation. They will essentially be programming and interacting with a robot that we will provide for the people who will do the best in the contest, which is a robot called Atlas that was designed by Boston Dynamics. The government, at its expense, will give up to six teams who do the best in the VRC this robot to use in the [final] event itself.”

While DARPA had only allocated resources for the top six teams to move through, a combination of good sportsmanship and generosity will see members of the top nine teams move forward: