Implementing Traction Control for an advantage in the 2009 game

[Jared Russell]

Methods for doing traction control:

1. Use what you know about the physics of your environment (open-loop):

1a. Limit acceleration of the wheel to the acceleration that provides the maximum tractive force. Works great in theory, but the dynamics of the robot (i.e. weight transfer from wheel to wheel when turning, irregularities in the wheel tread) make this style slightly unreliable. Still, it should be much better than nothing.

2. Sense the difference between your true robot velocity and your wheel velocity:

2a. Combine driven and non-driven wheels. Sense the speed of both. This will absolutely detect wheel slip, but you lose some downforce to the non-driven wheels.

2b. Use inertial sensors (accelerometer + gyro) to get your robot speed. The problem is that these sensors are noisy and will drift when integrated.

2c. Use a camera/mouse/ultrasonic range finder/RADAR/LIDAR to detect true robot speed. I've yet to see a reliable implementation of one of these methods on a FIRST robot, however.

3. There are other clever ways as well:

3a. Kalman filters are based on complicated mathematics, but can take different types of sensors with known uncertainty characteristics and fuse together their outputs to get a generally reliable view of the overall picture. This would be a robust way to use inertial guidance, for example.

3b. Even in a 4WD robot with 4 independently-powered wheels with encoders, you can detect (some kinds of) slip without the need for additional sensors. You know where on your robot the wheels are mounted. You can measure the speeds of all four wheels. If you examine the speeds of three wheels at a time, you can compute what the speed of the fourth you HAVE to be in order for there to be no slippage. You can do this for all 4 combinations of three wheels and deduce which wheel(s) are lying to you. If all four (or even three, and sometimes two) wheels are slipping, you're still out of luck, but if one wheel loses traction before the others, you will know.

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How much agility will we really gain with these methods on this floor? I don't know - but I do know that in the kingdom of the blind, the one-eyed man is king. A small edge might tip the balance of an otherwise level playing field this season.