Tank Steering

[biojae]

I have noticed that most of the robots here use a skid steering drive.
How do most teams decide which values to use in the autonomous mode for getting to a location on the field?

[Chexposito]

we have switches on the robot to flip to indicate what positition it is at. our programers found it easier to do that

[biojae]

Originally Posted by Chexposito

we have switches on the robot to flip to indicate what positition it is at. our programers found it easier to do that

so, then its just experimented values?

[Chexposito]

yes and no, we had a lot of encoders on our robot so we knew exactly how far it went, but the turning we did was experimental. (we had a crab drive)

here's a pic: http://www.teamdriven.us/media_page/...s/102_2390.jpg

[biojae]

Originally Posted by Chexposito

yes and no, we had a lot of encoders on our robot so we knew exactly how far it went, but the turning we did was experimental. (we had a crab drive)

here's a pic: http://www.teamdriven.us/media_page/...s/102_2390.jpg

oh, crab has several advantages over tank for navigation.
I wish that kinematically modeling a skidsteer was easier for navigation.
If my team would use crab, I would already have made a navigation model, and have a route planning algorithm.
Navigation with skid steer is harder, and it seems no teams have done much with it

[MrForbes]

Originally Posted by biojae

Navigation with skid steer is harder, and it seems no teams have done much with it

almost requires some type of position/orientation feedback, eh?

Skids are difficult to predict.

[biojae]

Originally Posted by squirrel

almost requires some type of position/orientation feedback, eh?

Skids are difficult to predict.

A combination Gyro, encoder, + inertial mesurements?

[AdamHeard]

Originally Posted by biojae

A combination Gyro, encoder, + inertial mesurements?

Pretty solid results have been achieved with just encoders and a gyro. I think the entire 08 season was a testament to this.

[biojae]

Originally Posted by AdamHeard

Pretty solid results have been achieved with just encoders and a gyro. I think the entire 08 season was a testament to this.

so just a simple formula like

X pos = X0 + (((Left encoder + Right encoder)* wheel radius) /2 ) * cos(Gyro Theta)
Y pos = Y0 + (((Left encoder + Right encoder)* wheel radius) /2 ) * sin(Gyro Theta)

[AustinSchuh]

This year, 971 integrated the ground speed sensors to get our position. We couldn't measure sideways sliding, though one more sensor and vex omni wheel would have dealt with that. Our programmer then wrote a PD loop to get the robot to follow a spline.

One of the most important lessons he learned during this process is that it helps a lot to have plots on your computer showing what you wanted, and what the bot did. He used the dashboard port, a piece of ruby code, and Gnuplot to get the data back and display it.

An easy way to go to a position on the field is to write a PD loop that controls the steering to get the angle right, and apply forwards power to get to the point. If you care if you stop there, you'll then need some sort of control for the throttle as well. A simple way to follow a path is to string these points together and move on to the next one when you get close to the first one. This all assumes you have encoders and/or gyros to measure where you are.

[biojae]

Originally Posted by AustinSchuh

This year, 971 integrated the ground speed sensors to get our position. We couldn't measure sideways sliding, though one more sensor and vex omni wheel would have dealt with that. Our programmer then wrote a PD loop to get the robot to follow a spline.

Could an accelerometer account for the deflection?

and how was the spline calculated?

One of the most important lessons he learned during this process is that it helps a lot to have plots on your computer showing what you wanted, and what the bot did. He used the dashboard port, a piece of ruby code, and Gnuplot to get the data back and display it.

That sounds like an application for a touchscreen dashboard

An easy way to go to a position on the field is to write a PD loop that controls the steering to get the angle right, and apply forwards power to get to the point. If you care if you stop there, you'll then need some sort of control for the throttle as well. A simple way to follow a path is to string these points together and move on to the next one when you get close to the first one. This all assumes you have encoders and/or gyros to measure where you are.

The steering seems to me the hardest part. What variables did the PD loop control ?

[Al Skierkiewicz]

Crab steering should be no harder than any other steering and perhaps more easy. You need to know how far the wheels have driven (preferably more than one to increase accuracy), which direction the steering is turned and where you want the robot to be at various intervals. The big variables occur when you run into objects on the field like goals and other robots. With other steering methods you have to compensate for turning radius when moving in other than a straight line.
As far as travel, we have used wheel encoders, either scratch built optical or off the shelf rotational encoders. The data is then used in calculating the distance traveled by incorporating wheel circumference and rotations. Steering is a simple pot but you should have used that already for feedback control with manual steering. A gyro will help you to maintain preset way points and can help in collision correction. We used one to great effect during 2003 when climbing the ramp in auto.

[AustinSchuh]

Originally Posted by biojae

Could an accelerometer account for the deflection?
and how was the spline calculated?

We might have been able to use an accelerometer, but we heard enough stories about people trying to use one for traction control and determining that it wasn't working well that we didn't bother to try. It also was at the point of diminishing returns, since the bot didn't skid sideways very much anyways.

I don't recall the equation, but you can spend some time on the wikipedia page or the internet in general and get a parametric equation for the cubic spline.

Originally Posted by biojae

The steering seems to me the hardest part. What variables did the PD loop control ?

turn = error * k1 + (error - lasterror) * K2
left = 1.0 + turn
right = 1.0 - turn

Like always, the hard part is tweaking the constants.

[Akash Rastogi]

Originally Posted by AdamHeard

Pretty solid results have been achieved with just encoders and a gyro. I think the entire 08 season was a testament to this.

Our best results have been from gyros, ecoders, PD loops and PID.

Once StanGPS was released people learned A LOT about how to write a good autonomous.

[Chris Hibner]

Originally Posted by biojae

Navigation with skid steer is harder, and it seems no teams have done much with it

That's a pretty bold claim, as well has a VERY inaccurate one. A lot of teams have been doing skid steer navigation since autonomous began in 2003.

Here's the best advice I can give you: do NOT put your encoders on your drive wheels - put them on non-driven "dummy" wheels that do nothing but measure distance. By using non-driven wheels, all of the skidding and associated wheel slippage do not influence the measured distance.