Autonomous car build

in Arduino, hacks, sensors by DP | 2 comments

Jason Dorweiler blogged about his autonomous car build:

For the localization of the car I’ll be using a GPS sensor and accelerometer. First, the GPS will find the starting coordinates of the car. Then the car will start moving, somewhat blindly at first. Once the car is moving, data from the accelerometer and elapsed time can be used to calculate the velocity of the car. These two measurements are then passed into a Kalman filter to improve the accuracy of the car’s position.

At the same time, heading data from the GPS and gyroscope are passed into another Kalman filter to get an accurate heading on the car. The position and heading data from the Kalman filters is then compared to a GPS waypoint given to the sensor and motor control. Next, a heading toward the desired GPS waypoint is calculated, and the appropriate signal is sent to the steering servo in order to point the car in that direction.

Via Hacked Gadgets.

Check out the video after the break.

This entry was posted in Arduino, hacks, sensors and tagged , , .

Comments

  1. Robert Welch says:

    Are you recording the geometric dilution of precision (GDOP)?

  2. Lloyd Atkinson says:

    I don’t know what a Kalman filter is, but how accurate is GPS for this? It was my understanding it was accurate down to a few meters, not centimeters that would surely be required for this?

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