The driverless vehicles churning up the dust as they attempted to speed the
142 miles from Barstow, CA to Primm, NV across the desert this past March were
not what seemed like another episode of a robot reality television show. In fact
these autonomous vehicles were contenders in DARPA's Grand Challenge (http://rbi.ims.ca/XXXX-XXX deep link is www.darpa.mil/grandchallenge).
That program tests the abilities of students and engineers to design vehicles
that can maneuver through a Mojave Desert obstacle course in less than 10 hours,
with the winner taking home a $1 million cash prize.
What such teams were up against and how they surmounted the
design challenges is typified by "The Blue Team," assembled by graduate student
Anthony Levandowski at the University of California at Berkeley. Instead of
modifying a car or truck, Levandowski's group chose a motorcycle, an inherently
unstable vehicle. They reasoned a motorcycle would better remain within the
race's narrow course since only one "axis" needed to conform to terrain. But as
if desert conditions aren't bad enough, the trek included an underpass, an
overpass, and water hazards. Levandowski funded most of the project out of
pocket, although sponsors such as Raytheon, National Instruments, and Vicor
The team used the Virtual Engineering Environment (VEE) from Agilent
Technologies (Palo Alto, CA) to develop control software. According to
Levandowski, "Coding in VEE makes it easy to modify routines and add modules as
needed." The team has moved some control software to C, though, because of its
speed advantage over VEE.
First efforts used VEE to simulate the motorcycle, named Ghost Rider (http://rbi.ims.ca/XXXX-XXX, deep link is
www.ghostriderrobot.com), and the
controllers. Programmers could observe the program pass data and control between
various function blocks. That high-level view of operations simplified testing
How it works
The autonomous motorcycle relies on a GPS receiver, a MEMS
gyroscope, radar, several cameras, and other sensors and actuators to put it at
the right place at the right time. "We use fast algorithms to control steering
and to keep the vehicle upright," notes Levandowski. To stop and stay upright,
the front wheel turns 90 degrees and the front wheel motor "rocks" the
motorcycle in a direction opposite a pending tip over.
Sensors also help the motorcycle avoid obstacles. "Say a camera sees a big
rock, but the millimeter radar sees nothing," Levandowski says. "Does the PC
choose a conservative approach and guide the vehicle around the 'rock,' or does
it just continue on? That's not an easy decision to make." This sort of
situation highlights the need for good software and careful programming.
The motorcycle and other robots receive their racecourse coordinates-GPS
readings-only two hours before the race. The vehicles then must operate on their
own. Teams cannot guide vehicles by remote control.
In early versions, the Ghost Rider proceeded for a short distance and then
lost control. Some problems centered on the mechanics. "When we built the
full-scale motorcycle, we purchased a motor for $250, but we should have bought
a motor that has better specifications," says Levandowski. "That motor would
have cost about $3,000, but it would have been worth it. It's difficult to keep
the inexpensive motor in control." Specifically he was referring to the use of
neodymium magnets in the steering dc servo motor, which do not demagnetize under
shock loads encountered by the bike. So, cautions Levandowski, don't skimp on
hardware in a critical portion of a design.
The electronics portion of the Ghost Rider relies on an embedded PC with
peripheral devices communicating through standard USB- and serial-port
connections. According to Levandowski, two additional lessons relate to
software. First, the visual environment provided by VEE greatly simplified
program development and it let programmers quickly make changes during field
tests. Second, the use of standard interfaces reduced software overhead.
Did the Ghost Rider reach the finish line? No-but
neither did any other robot claim the prize. During launch, a less-experienced
crew member failed to activate the guidance system properly and the bike crashed
beyond repair. The most successful vehicle went through many turns to 7.4 miles
before hanging up on a berm in mountainous switchbacks.
"The bar was high," says DARPA Spokesman Jan Walker. "It was the first
opportunity for such vehicles to 'get out of the company parking lot' and into a
trail environment that DARPA is interested in." The agency is planning the next
Challenge to take place at least a year after the first and has sweetened the
pot to a $2 million prize.
DESERT BLOOM: The autonomous Ghost Rider
motorcycle not only had to navigate across a desert course but remain
upright as well (Credit: Anthony