DARPA Grand Problem: 20 Years Later

The 2004 DARPA Grand Problem was a spectacular failure. The Protection Superior Analysis Initiatives Company had provided a US $1 million prize for the workforce that might design an autonomous floor car able to finishing an off-road course via typically flat, typically winding and mountainous desert terrain. As IEEE Spectrumreported on the time, it was “the motleyest assortment of autos assembled in a single place for the reason that filming of Mad Max 2: The Street Warrior.” Not a single entrant made it throughout the end line. Some didn’t make it out of the parking zone.

Movies of the makes an attempt are comical, though any laughter comes on the expense of the various engineers who spent numerous hours and tens of millions of {dollars} to get to that time.

So it’s all of the extra outstanding that within the second DARPA Grand Problem, only a yr and a half later, 5 autos crossed the end line. Stanley, developed by the Stanford Racing Group, eked out a first-place win to assert the $2 million purse. This modified Volkswagen Touareg [shown at top] accomplished the 212-kilometer course in 6 hours, 54 minutes. Carnegie Mellon’s Sandstorm and H1ghlander took second and third place, respectively, with instances of seven:05 and seven:14.

Kat-5, sponsored by the Grey Insurance coverage Co. of Metairie, La., got here in fourth with a good 7:30. The car was named after Hurricane Katrina, which had simply pummeled the Gulf Coast a month and a half earlier. Oshkosh Truck’s TerraMax additionally completed the circuit, though its time of 12:51 exceeded the 10-hour time restrict set by DARPA.

So how did the Grand Problem go from a complete bust to having 5 strong finishers in such a brief time frame? It’s positively a testomony to what may be achieved when engineers rise to a problem. However the final result of this one race was preceded by a for much longer path of analysis, and that plus just a little little bit of luck are what finally led to victory.

Earlier than Stanley, there was Minerva

Let’s again as much as 1998, when laptop scientist Sebastian Thrun was working at Carnegie Mellon and experimenting with a really totally different robotic: a museum tour information. For 2 weeks in the summertime, Minerva, which regarded a bit like a Dalek from “Physician Who,” navigated an exhibit on the Smithsonian Nationwide Museum of American Historical past. Its major activity was to roll round and dispense nuggets of details about the shows.

Minerva was a museum tour-guide robotic developed by Sebastian Thrun.

In an interview on the time, Thrun acknowledged that Minerva was there to entertain. However Minerva wasn’t only a folks pleaser ; it was additionally a machine studying experiment. It needed to be taught the place it may safely maneuver with out taking out a customer or a priceless artifact. Customer, nonvisitor; show case, not-display case; open ground, not-open ground. It needed to react to people crossing in entrance of it in unpredictable methods. It needed to be taught to “see.”

Quick-forward 5 years: Thrun transferred to Stanford in July 2003. Impressed by the primary Grand Problem, he organized the Stanford Racing Group with the purpose of fielding a robotic automobile within the second competitors.

In an unlimited oversimplification of Stanley’s major activity, the autonomous robotic needed to differentiate between street and not-road with the intention to navigate the route efficiently. The Stanford workforce determined to focus its efforts on growing software program and used as a lot off-the-shelf {hardware} as they may, together with a laser to scan the speedy terrain and a easy video digicam to scan the horizon. Software program overlapped the 2 inputs, tailored to the altering street situations on the fly, and decided a protected driving pace. (For extra technical particulars on Stanley, try the workforce’s paper.) A remote-control kill change, which DARPA required on all autos, would deactivate the automobile earlier than it may change into a hazard. About 100,000 traces of code did that and rather more.

The Stanford workforce hadn’t entered the 2004 Grand Problem and wasn’t anticipated to win the 2005 race. Carnegie Mellon, in the meantime, had two entries—a modified 1986 Humvee and a modified 1999 Hummer—and was the clear favourite. Within the 2004 race, CMU’s Sandstorm had gone furthest, finishing 12 km. For the second race, CMU introduced an improved Sandstorm in addition to a brand new car, H1ghlander.

Lots of the different 2004 rivals regrouped to strive once more, and new ones entered the fray. In all, 195 groups utilized to compete within the 2005 occasion. Groups included college students, lecturers, business specialists, and hobbyists.

After website visits within the spring, 43 groups made it to the qualifying occasion, held 27 September via 5 October on the California Speedway, in Fontana. Every car took 4 runs via the course, navigating via checkpoints and avoiding obstacles. A complete of 23 groups have been chosen to try the principle course throughout the Mojave Desert. Competing was a pricey endeavor—CMU’s Pink Group spent greater than $3 million in its first yr—and the names of sponsors have been splashed throughout the autos just like the logos on race vehicles.

Within the early hours of 8 October, the finalists gathered for the large race. Every workforce had a staggered begin time to assist keep away from congestion alongside the route. About two hours earlier than a workforce’s begin, DARPA gave them a CD containing roughly 3,000 GPS coordinates representing the course. As soon as the workforce hit go, it was fingers off: The automobile needed to drive itself with none human intervention. PBS’s NOVA produced a superb episode on the 2004 and 2005 Grand Challenges that I extremely suggest if you wish to get a really feel for the thrill, anticipation, disappointment, and triumph.

Within the 2005 Grand Problem, Carnegie Mellon College’s H1ghlander was one among 5 autonomous vehicles to complete the race.Damian Dovarganes/AP

H1ghlander held the pole place, having positioned first within the qualifying rounds, adopted by Stanley and Sandstorm. H1ghlander pulled forward early and shortly had a considerable lead. That’s the place luck, or slightly the shortage of it, got here in.

About two hours into the race, H1ghlander slowed down and began rolling backward down a hill. Though it will definitely resumed shifting ahead, it by no means regained its prime pace, even on lengthy, straight, degree sections of the course. The slower however steadier Stanley caught as much as H1ghlander on the 163-km (101.5-mile) marker, handed it, and by no means let go of the lead.

What went unsuitable with H1ghlander remained a thriller, even after in depth postrace evaluation. It wasn’t till 12 years after the race—and as soon as once more optimistically—that CMU found the issue: Urgent on a small digital filter between the engine management module and the gasoline injector brought on the engine to lose energy and even flip off. Group members speculated that an accident a couple of weeks earlier than the competitors had broken the filter. (To be taught extra about how CMU lastly figured this out, see Spectrum Senior Editor Evan Ackerman’s 2017 story.)

The Legacy of the DARPA Grand Problem

No matter who gained the Grand Problem, many success tales got here out of the competition. A yr and a half after the race, Thrun had already made nice progress on adaptive cruise management and lane-keeping help, which is now available on many business autos. He then labored on Google’s Avenue View and its preliminary self-driving vehicles. CMU’s Pink Group labored with NASA to develop rovers for doubtlessly exploring the moon or distant planets. Nearer to house, they helped develop self-propelled harvesters for the agricultural sector.

Stanford workforce chief Sebastian Thrun holds a $2 million examine, the prize for profitable the 2005 Grand Problem.Damian Dovarganes/AP

After all, there was additionally plenty of hype, which tended to overshadow the race’s militaristic origins—bear in mind, the “D” in DARPA stands for “protection.” Again in 2000, a protection authorization invoice had stipulated that one-third of the U.S. floor fight autos be “unmanned” by 2015, and DARPA conceived of the Grand Problem to spur improvement of those autonomous autos. The U.S. army was nonetheless preventing within the Center East, and DARPA promoters believed self-driving autos would assist reduce casualties, significantly these attributable to improvised explosive gadgets.

DARPA sponsored extra contests, such because the 2007 City Problem, through which autos navigated a simulated metropolis and suburban surroundings; the 2012 Robotics Problem for disaster-response robots; and the 2022 Subterranean Problem for—you guessed it—robots that might get round underground. Regardless of the competitions, continued army conflicts, and hefty authorities contracts, precise advances in autonomous army autos and robots didn’t take off to the extent desired. As of 2023, robotic floor autos made up solely 3 % of the worldwide armored-vehicle market.

In the present day, there are only a few absolutely autonomous floor autos within the U.S. army; as an alternative, the companies have cast forward with semiautonomous, operator-assisted techniques, resembling remote-controlled drones and ship autopilots. The one Grand Problem finisher that continued to work for the U.S. army was Oshkosh Truck, the Wisconsin-based sponsor of the TerraMax. The corporate demonstrated a palletized loading system to move cargo in unmanned autos for the U.S. Military.

A lot of the up to date reporting on the Grand Problem predicted that self-driving vehicles would take us nearer to a “Jetsons” future, with a self-driving car to ferry you round. However twenty years after Stanley, the rollout of civilian autonomous vehicles has been confined to particular functions, resembling Waymo robotaxis transporting folks round San Francisco or the GrubHub Starships struggling to ship meals throughout my campus on the College of South Carolina.

I’ll be watching to see how the expertise evolves outdoors of massive cities. Self-driving autos could be nice for lengthy distances on empty nation roads, however components of rural America nonetheless wrestle to get ample cellphone protection. Will small cities and the areas that encompass them have the bandwidth to accommodate autonomous autos? As a lot as I’d wish to assume self-driving autos are practically right here, I don’t look forward to finding one beneath my carport anytime quickly.

A Story of Two Stanleys

Not lengthy after the 2005 race, Stanley was able to retire. Recalling his expertise testing Minerva on the Nationwide Museum of American Historical past, Thrun thought the museum would make a pleasant house. He loaned it to the museum in 2006, and since 2008 it has resided completely within the museum’s collections, alongside different outstanding specimens in robotics and vehicles. In truth, it isn’t even the primary Stanley within the assortment.

Stanley now resides within the collections of the Smithsonian Establishment’s Nationwide Museum of American Historical past, which additionally homes one other Stanley—this 1910 Stanley Runabout. Behring Heart/Nationwide Museum of American Historical past/Smithsonian Establishment

That distinction belongs to a 1910 Stanley Runabout, an early steam-powered automobile launched at a time when it wasn’t but clear that the internal-combustion engine was the best way to go. Regardless of clear drawbacks—steam engines had a nasty tendency to blow up—“Stanley steamers” have been recognized for his or her high-quality craftsmanship. Fred Marriott set the land pace file whereas driving a Stanley in 1906. It clocked in at 205.5 kilometers per hour, which was considerably quicker than the Twenty first-century Stanley’s common pace of 30.7 km/hr. To be honest, Marriott’s Stanley was racing over a flat, straight course slightly than the off-road terrain navigated by Thrun’s Stanley.

Throughout the century that separates the 2 Stanleys, it’s straightforward to hint a story of progress. Each are clearly recognizable as four-wheeled land autos, however I think the science-fiction dreamers of the early twentieth century would have been hard-pressed to think about the suite of applied sciences that will propel a Twenty first-century self-driving automobile. What’s going to the autos of the early twenty second century be like? Will they even have 4 tires, or will they run on one thing solely new?

A part of a persevering with sequencetaking a look at historic artifacts that embrace the boundless potential of expertise.