DARPA Grand Problem: 20 Years Later

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

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

So it’s all of the extra exceptional 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 Crew, 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 occasions of seven:05 and seven:14.

Kat-5, sponsored by the Grey Insurance coverage Co. of Metairie, La., got here in fourth with a decent 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 sturdy 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 consequence of this one race was preceded by a for much longer path of analysis, and that plus a bit little bit of luck are what in the end led to victory.

Earlier than Stanley, there was Minerva

Let’s again as much as 1998, when pc scientist Sebastian Thrun was working at Carnegie Mellon and experimenting with a really completely different robotic: a museum tour information. For 2 weeks in the summertime, Minerva, which seemed a bit like a Dalek from “Physician Who,” navigated an exhibit on the Smithsonian Nationwide Museum of American Historical past. Its most important job 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 individuals pleaser ; it was additionally a machine studying experiment. It needed to be taught the place it might safely maneuver with out taking out a customer or a priceless artifact. Customer, nonvisitor; show case, not-display case; open flooring, not-open flooring. 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 Crew with the goal of fielding a robotic automobile within the second competitors.

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

The Stanford crew 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.

Most of the different 2004 opponents regrouped to attempt once more, and new ones entered the fray. In all, 195 groups utilized to compete within the 2005 occasion. Groups included college students, lecturers, trade consultants, 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 had been chosen to try the principle course throughout the Mojave Desert. Competing was a expensive endeavor—CMU’s Crimson Crew spent greater than $3 million in its first yr—and the names of sponsors had 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 crew had a staggered begin time to assist keep away from congestion alongside the route. About two hours earlier than a crew’s begin, DARPA gave them a CD containing roughly 3,000 GPS coordinates representing the course. As soon as the crew hit go, it was fingers off: The automobile needed to drive itself with none human intervention. PBS’s NOVA produced a wonderful episode on the 2004 and 2005 Grand Challenges that I extremely advocate 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 in every of 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 dearth 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 transferring ahead, it by no means regained its prime velocity, even on lengthy, straight, stage 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 flawed with H1ghlander remained a thriller, even after intensive postrace evaluation. It wasn’t till 12 years after the race—and as soon as once more hopefully—that CMU found the issue: Urgent on a small digital filter between the engine management module and the gas injector brought on the engine to lose energy and even flip off. Crew members speculated that an accident just a few 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 received 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 industrial autos. He then labored on Google’s Avenue View and its preliminary self-driving vehicles. CMU’s Crimson Crew labored with NASA to develop rovers for doubtlessly exploring the moon or distant planets. Nearer to residence, they helped develop self-propelled harvesters for the agricultural sector.

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

In fact, there was additionally a whole lot of hype, which tended to overshadow the race’s militaristic origins—keep 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 growth of those autonomous autos. The U.S. navy was nonetheless combating within the Center East, and DARPA promoters believed self-driving autos would assist reduce casualties, notably these attributable to improvised explosive units.

DARPA sponsored extra contests, such because the 2007 City Problem, wherein 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 navy conflicts, and hefty authorities contracts, precise advances in autonomous navy 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.

As we speak, there are only a few absolutely autonomous floor autos within the U.S. navy; as a substitute, the providers have solid 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. navy 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 modern 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 20 years after Stanley, the rollout of civilian autonomous vehicles has been confined to particular functions, resembling Waymo robotaxis transporting individuals 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 elements of rural America nonetheless wrestle to get sufficient cellphone protection. Will small cities and the areas that encompass them have the bandwidth to accommodate autonomous autos? As a lot as I’d prefer to assume self-driving autos are practically right here, I don’t anticipate finding one below 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 residence. He loaned it to the museum in 2006, and since 2008 it has resided completely within the museum’s collections, alongside different exceptional specimens in robotics and vehicles. In reality, 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” had been recognized for his or her nice craftsmanship. Fred Marriott set the land velocity document 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 velocity of 30.7 km/hr. To be truthful, 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 simple 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 may propel a Twenty first-century self-driving automobile. What is 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 completely new?

A part of a persevering with sequence historic artifacts that embrace the boundless potential of expertise.