Quote:
|
s. On top of the programming prowess and processing power needed to anticipate, a robot has a limited field of vision.
|
That would be the point of using data from the FMS or using human drivers as "sensors"--your tactical data isn't neccesarily limited by your robot's on-board devices or its physical location.
Quote:
|
The cRio is good, but I doubt that a team could implement a full AI that would replace human drivers anytime in the next 10 years.
|
You don't need a full AI, you need a domain-specific expert system, since it doesn't need to do anything else other than play whatever the game of the year is. The ability of an expert system to control the robot is also going to depend on the game of the year--for example, since we had such a simple strategy for Overdrive(go as fast as we can aroun the track, avoiding stuff), the only barrier to being able to have a fully autonomous robot was some instability in our Ackermann system, which was a signal-processing problem, not an AI one.
Quote:
|
In one match at one regional, a team attempted to throw a match to draw a triple G14 after an alliance partner didn't make the field on time. How would a robot anticipate that?
|
Most likely a system of "match priorities" set before each match. This would basically be a weighted table that the robot stores which determines how much a particular event occuring influences the action that the robot takes in response.