Hi everybody,
I've been working on a completely autonomous vehicle based off of a Power Wheels, like the IGVC/mini DARPA vehicles. Right now, everything is controlled by a laptop programmed in Java and two Phidgets interface kits, giving me up to 16 analog inputs, 16 digital ins, and 16 digital outs.
The current sensors are simple potentiometers for PID threads with steering, limit switches, encoders for speed, and IR range sensors for object detection, along with a Sony DV camera.
I recently won a small grant, and wanted to update my whole platform - the next revision should be a tubular aluminum frame with 4hp motor and precision ackerman steering.
Along with the hardware improvements, I'd like to make it smarter. The eight IR range finders don't seem to be cutting it for navigation of a vehicle this large, as their FOV and range are limited. Sonar is difficult to interface through a Phidget, so I considered a basic stamp, but I do not like the potential for noise from the other sensors and there, perhaps, the FOV is too large.
What I'd really like to do is build/find a laser range finder, or something similar that updates fast enough to allow a decent 5mph speed while still remaining reasonably aware of the environment. I'm looking for at least 90 degrees FOV with maybe 10-15 degree precision, though obviously, more is better (180 degrees for full frontal, or two for 360, allowing easy backups).
Has anyone experimented with this type of technology? Anything that'd be easy to impliment on a USB/serial interface? My budget right now is about $350, so something like a Sick LMS200 is probably out of my range, and I don't think they do student discounts
.
Worse comes to worse, I can pick up another four IR sensors and get it to three per side.
On an unrelated topic, has anyone worked on large scale ackerman steering with PID threads? My high traction wheels are causing some trouble for the servo motors (a modified 18V drill), and was wondering what you might suggest. The total vehicle will weigh about 200lbs, I think.
Thanks!