Virtual Robotic Cars¶
Tennessee Leuwenburg (sp?)
Why?¶
Loves robotics as an intellectual playspace
Submitted the talk partly as a motivation/excuse to spend more time playing
Real World¶
Brief history of auto racing
Many current “self-driving car” efforts
DARPA Grand Challenge video
Urban Grand Challenge video ($40k radar array!)
Traxxas X01 (video) - 100 MPH remote control car - controlled via iPhone
Range of technology - drive-by-wire(less) - remote drive-by-wire(less) - supervised autonomous (ABS, - fully autonomous
Few real world races - DARPA Grand Challenge - DARPA Urban Challenge - Audi Pikes Peak
Virtual World¶
TORCS - The Open Racing Car Simulator
TORCS video
Something anyone can do
Similar abstractions to a real robotic car - distance and other sensors - speed, steering, braking controls - noisy sensors - complex environments - open-ended design and problem definitions
Can go as far as you want in learning
Yearly TORCS competition - current entries Java & C++
Now has Python bindings, so can write car control systems in Python
pyScrcClient - uses a socket to talk to the TORCS server
Udacity course - programming a robotic car in 7 weeks
The TORCS Vehicles¶
Sensors - 20 range-finders - current angle to track bearing
Controls - accelerator - brake - gear changes
Trigonometry to get from distance sensors to an actual picture of the world
Getting Started¶
Just follow the track center line!
Beyond that - steering and path planning - acceleration and braking - collision avoidance (for racing) - strategy (beyond the scope of the talk)
No compass sensor, so first step is to build a motion model for the car itself
TORCS updates every 0.02 seconds
Places an upper limit on your processing time
Evil maths!¶
More trig to work out the expected centre point of a turn.
Simplify the model of the car to a bicycle rather than worrying about the four wheels
- How to model:
- assume you know the car positionss
- see what happens
- draw something so you can see what your car is “seeing”
Yakkety Sax goes with everything!
(Oops, wrong version of the slides, opened right version to get correct embedded video)
Localisation¶
Given a map, use it work out where you are
Feedback loop between deriving the map from sensors, and using the results of your sensors to determine where you are
SLAM and Filtering¶
Can use “mapping runs” to build up hypothesis maps
Can use track distances to filter particles after a complete lap (known location)
Great free resources online
Virtual Robotic Car Racing lets you explore and exploit most of the related algorithms
Resources¶
See slides for links (I’ll add a link to the slides once they’re up)
Q & A¶
(missed the first couple)
Polulu - remote control chassis with reversible wheels and an Arduino built in to embody your questions
Can download and run bots from the competition to see how good (or bad) you are.
No GPS in the sim software, so you can’t “pre-plan” too much (and competition uses novel tracks)
No accelerometer info in TORCS (which seems odd, since this is the first sensor you would add to a real version)
Strategy depth is immense! (e.g. blocking lines to prevent following cars using them)
My Thoughts¶
Sounds like an interesting way to explore various AI topics.