The DARPA RACER program’s goal is to develop and demonstrate autonomy technologies that enable unmanned ground vehicles (UGVs) to maneuver in unstructured off-road terrain at the limit of the vehicle’s mechanical systems and at, or beyond, human-driven speeds and efficiencies. “RACER is intended to disruptively advance the integration and fielding of autonomy for robotic combat vehicles into the Army, Marine Corps, and Special Forces communities,” said Stuart Young, RACER program manager in DARPA’s Tactical Technology Office.
In November, the selected teams received the first of the DARPA-provided RACER Fleet Vehicles (RFVs) – a high performance all-terrain vehicle outfitted with world-class sensing and computational abilities – that they are using to develop platform-based autonomy for testing at upcoming DARPA-hosted field experiments.
RFV robots include 360o range and image sensing such as multiple LIDARs, stereo camera pairs, color and infrared imaging cameras, RADAR, event sensors, and inertial measurement sensing. Computation tools have multiple best-of-class graphical processing units (GPUs) in an environmentally protected, shock/vibration proof, and thermally managed Electronics Box (E-Box) that’s specifically engineered for the demands of the RACER high speed, off-road terrain expected in DARPA’s tests.
The sensor and E-box combination currently collects four terabytes of sensor data per hour to support artificial intelligence, machine learning-based autonomy algorithms and stack approaches required of fast-paced combat maneuvers in complex terrain. Modifications for roll protection, sensor/E-box integration, autonomous control, and increased 7kW of power are included in each RFV. The RFVs were integrated by Carnegie Robotics LLC (CRL) and are housed on a Polaris RZR S4 1000 Turbo base drive-by-wire platform.
Four RFVs have been completed, with three already delivered to RACER Phase 1 performers in November 2021. Four more are expected to be built prior to DARPA’s first RACER-hosted field experiment, scheduled for March of 2022.
DARPA has also collected over 100 terabytes of RFV-based sensor data from more than 500 kilometers of terrain in the Mid-Atlantic and West Coast. Shared with teams and managed within a RACER development tool for efficiency and security, this data will assist with learning approaches.
Future RACER program activities include continuation into a RACER Phase 2 effort with a more representative 10T combat vehicle surrogate. The plan is to evolve in speed, scale, and mobility beyond the RFVs, as well as add a research track exploring tactics-based derivation of the new platforms.
Written By Brian Wang, Nextbigfuture.com
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.
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11 thoughts on “DARPA Unmanned Cars Will Have Offroad Race”
GM-backed Cruise opens driverless robotaxi service to SF public.
basic onboard sensors and systems can react to the heightened traffic flow. special and exclusive lanes and timing may be required.
more sensors means more failures more recalls more maintenance…
there has to be some net gain in convenience not just the whiz-bang effect…
not only that. you could make it 100 times more 'safe' than humans, but its more than that. How well would autonomous vehicles be assimilated into 'driving culture'. No one wants millions of grandma AI drivers out there – slower than speed limit, brakes at every shadow or shifting pedestrian, waits 2 – 5s at each light for each car ahead to move (leading to many minutes for a long line of 20+), putters behind a bike that strays a bit too far from curb, etc… there's a certain amount of initiative and 'ruling the road' that has to happen.
depends on the vehicle. Commercial delivery? One person mini? Dedicated route transit?
but how do you integrate and address the 'normies' with their hmuan-directed automobiles… what kind of standardized system and penetration valeus before the actual flow and effectivenes of street travel increases… decades… at least in highway/ built-up/ dedicated arteries…
sounds like a great opportunity to me. Local fixed sensor and data transmission to autonomous vehicles (in specilaized lane/ area) allow autobahn-like speeds, tight traffic flows, flow and turn optimization.. all for one low toll at each pass… a municipal gold mine.
Level 5 will never happen on interstate, major municipal roads without hard, fixed support on the ground and along the autonomous routes considered.
Agreed. more than sensors and onboard AI… environmental modeling and vehicle limits…
Best way to train your Level 5++ – uneven, unpredictable, unforgiving terrain.
DARPA helped kick off the autonomous vehicle industry in 2007 with their Grand Challenge off-road autonomous vehicle race
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