Robocar: Unmanned Ground Robotics

Every robot relies on actuators to act upon its world. Robocar has three of these:

Figure 4. A nasty bird nest which also serves as the wiring for Robocar

To perceive its environment, Robocar needs sensors. We have given it cameras for detecting the track boundary lines painted in the grass, a scanning sonar for obstacle avoidance and an encoder wheel for speed detection. Robocar has some additional sensors for side projects which are not used during the competition.

Vision is supplied from two standard video cameras fed through two Matrox Meteor frame grabbers. We have two different Matrox cards: the Meteor and the Meteor/RGB. Both can read from multiple cameras and grab high-resolution 24-bit color images. The only difference is that the Meteor/RGB can grab frames from a split-RGB source, whereas the regular Meteor cannot. Even though we could plug two cameras into a single Meteor board, we are using two boards to get 30 frames per second per camera. Matrox's Meteor boards are inexpensive, reliable and well supported.

A single Panasonic sonar sensor mounted on top of a Futaba RC servo acts as an obstacle detection device. It scans the area in front of the car, rotating back and forth to cover a wider area. Using a single sonar has the advantage of removing any possibility of cross-talk and of being able to look in any direction. Using multiple statically-mounted sonar sensors would not give us this much flexibility. The Futaba servo, like the drive motors of the vehicle, is controlled using PWM.

An encoder wheel returns data to a speed sensor indicating how far it has turned. Since we know the diameter of the wheel, we know how far it has turned since last we checked. Thus, this sensor can compute our average speed during that time. The sensor's interface to the encoder wheel is through a CAN-PC board on our main computer. Robocar uses this sensor to ensure that it stays under the 5 MPH speed limit.

In addition to being a competition vehicle, Robocar acts as a test bed for Kevin Gifford's Ph.D. thesis, which is to develop an efficient navigation algorithm for (possibly off-world) autonomous rovers. An additional set of sensors has been added for this option: a GPS sensor and a “map” sensor. Using these, Robocar always knows exactly where it is and where it wishes to go; it can also plan the cheapest way of getting there.

The Trimble Series 4000 uses differential GPS and can make extremely accurate measurements—+ or - 10 centimeters—compared to normal civilian GPS. It comes with a base station, a receiver and radio modems. GPS information is supplied over a serial line.

During Kevin's research, Robocar knows about its environment by using a map sensor in addition to the competition and GPS sensors. The map sensor is basically a topological map of the research field. With this knowledge, Robocar can calculate the most efficient path to a set of destination coordinates.

In addition to the above sensors, we have a joystick for manually driving Robocar to and from the course (or around the test field just for fun). Without this, we would have to push or carry the heavy beast around—something we prefer to avoid. The joystick is plugged into a generic sound card on our main machine.