Archives for posts with tag: omniwheel

In case you might wonder how fast or accurate Agilis is, here are some numbers.

Setup

• The gear ratio of the motors to the wheels is 1:2, making the wheels rotate twice as fast as the motors. (It is possible to change the gear ratio to 1:3).
• Prototype orange Rotacaster wheels. This is the hard compound. There isalso a medium compound (gray) and soft compound (black) available.
• The batteries were rechargeable NiMH, 2500 mAh batteries. These were not fully charged.
• The test surface was a clean linoleum floor.

Speed

• Reliable top speed is about 60 cm/sec, equivalent to 2.16 km/h or 1.35 mph. At this speed the robot is still accurate as there is ample margin for the PID controllers of the motors.
• Unreliable top speed is about 75 cm/sec, equivalent to 2.7 kmh or 1.68 mph. At this speed the robot is not very accurate, especially the heading.

Accuracy

• The test track is a square with sides of one meter each. During each run the test track is traveled 4 times. Making the total distance of the test track 16 meters.
• The robot finishes the test track on average within 10 cm of its starting position. Expressed as a percentage of the total distance the error is about 0.6%.
• The movement error is systematic. The robot always ends up above and to the right of the starting position.
• The robot is more accurate at slower speed and acceleration settings.

The images shows the result of the accuracy testing. For each test the robot was placed exactly on the origin (bottom left in the picture). It then traveled a square with sides of one meter for four times, making the total distance traveled 16 meters. The finish location of the robot was then marked on the floor. This test was repeated three times for a single set of settings of speed and acceleration. Three different dynamic sets were used,  speed: 50 cm/sec and  acceleration at 100 cm/sec^2, speed 50 cm/sec and acceleration at 750 cm/sec^2 and speed 30 cm/sec and acceleration 60 cm/sec^2.

I want to repeat the tests with a 1:3 gear ratio and also with the black Rotacaster wheels.

Remember my plan to make a ball balancing robot? Last year I set myself the goal to make a ball balancing robot. I even build the robot. Since then I wondered off my original goal and made a guardbot, Koios, from this platform. Now I am having another shot at making a balancing robot.

Programming a balancing robot is easy in theory. You just need a sensor that tells you how much the robot is tilted, most often people use a gyro for this. I use my IMU for this, so that I do not suffer from gyro drift. The tilt angle is then feeded to a PID-controller that transformes tilt to motor speed. The hard part is to tune the PID controller, it has to translate tilt into just the right amount of motor speed, too little and the robot falls of the ball, too much and the robot goes over the top and falls of on the other side of the ball. Falling of the ball damages the robot. So I had a problem, how to tune the PID controller without damaging the robot?

To be able to tune the PID-controller without damaging the robot I made a special platform. It is a large disk with a small pole in the middle pointing down Due to the pole the disk will always be tilted when lying on the ground, only when it balances perfectly on the pole it is level. Therefore this disk can be used to tune the controller.  The robot can ride off the disk, but it doesn’t fall then, it just comes on the floor with one or two wheels.

When I tested this setup I discovered that the disk whas too smooth, the wheels didn’t have enough grip and slipped. To increase the friction I coated the surface of the disk with sillicon rubber, It is the light blue surface you see in the picture. Now I have a very “slick” surface.I only hope it lasts under the forces the NXT motors generate.But for the moment this problem is solved.

But there are other problems. One is the fact that these holonomic wheels make the robot vibrate, this affects the IMU filter, there is still some drift although it stays within certain limits. I do have prototype rotacaster wheels. The manufacturer told me that the production wheels are more round and generate less vibrations. If you are ever going to by these wheels, and they are a lot of fun, I advice you to take the black ones. They have the best grip. Anyway, I will have to tune the IMU as well.

Tuning PID controllers is difficult and very, very time consuming. There is some theory around tuning PID controllers but in the end it is mostly trial and error. Everytime I want to try a new set of parameters I’ll have to modify the program, download it to the brick, run the program and evaluate the results by watching the robot. It is hard to understand what goes wrong when you see the robot ride of the disk and make a run for the door to the staircase.

But not anymore. Kirk, one of the developers of Lejos made a very nice program that allows you to tune a running PID controller during over bluetooth. The tool is still under development so you won’t find it in Lejos 0.9.1 yet. This program is an add-on to the charting logger I often use to evaluate internals of the robot on the PC. So basicly, this program shows me what is going on in my robot and allows me to modify PID parameters on the fly. I think this is a great tool. Below is a screen shot of it.

So, now I have the robot, a test platform and a efficient tuning tool. That must mean immediate succes! Well, to be honest I don´t think so. I´m still not sure if I can get this robot to work as there are problem with weight and inertia as well. The robot weigths 998 grams. This is quite heavy, even for three powerful NXT motors. The robot is quite stiff, but there it still bends a bit under weight. This affects the IMU sensor. And I´m working on other projects as well. So in the end I think there is a bigger chance to fail than to succeed.

To be continued.