This paper describes an open-source
implementation of an event-based dynamic and
active pixel vision sensor (DAVIS) for racing
human vs. computer on a slot car track. The
DAVIS is mounted in "eye-of-god" view. The
DAVIS image frames are only used for setup and
are subsequently turned off because they are not
needed. The dynamic vision sensor (DVS) events
are then used to track both the human and
computer controlled cars. The precise control of
throttle and braking afforded by the low latency of
the sensor output enables consistent outperformance
of human drivers at a laptop CPU
load of <3% and update rate of 666Hz. The sparse
output of the DVS event stream results in a data
rate that is about 1000 times smaller than from a
frame-based camera with the same resolution and
update rate. The scaled average lap speed of the
1/64 scale cars is about 450km/h which is twice as
fast as the fastest Formula 1 lap speed. A feedbackcontroller
mode allows competitive racing by
slowing the computer controlled car when it is
ahead of the human. In tests of human vs.
computer racing the computer still won more than
80% of the races.Unión Europea FP7-ICT-270324Unión Europea FP7-ICT-60095
