The goal of the LAGR program is to develop a new generation
of learned perception and control algorithms that will address
the shortcomings of current robotic ground vehicle autonomous
navigation systems through an emphasis on learned autonomous
navigation. DARPA wanted the ten independent research teams
they selected to immediately focus on algorithm development
rather than be consumed early in the project with getting
a baseline robotic platform working. DARPA also wanted a
common platform so that software could be easily shared between
teams and so that the government could make an objective
evaluation of team results.
In just seven months, NREC designed and then built 12 LAGR
robots which allowed DARPA to hold the LAGR kick-off meeting
on time and to provide each research team with a fully functional
autonomous platform for development.
Teams were given 4 hours of training at kick-off and were
able to program basic obstacle avoidance capability the same
day. Developers were able to focus immediately on learning
algorithm research because all basic autonomy capabilities
along with well documented APIs were provided with delivery.
Careful configuration control for all platforms enables
developers to develop software at their home station, load
their software on a memory stick, and ship the memory stick
to DARPA, which then runs the software on their LAGR robot.