Robocar: Unmanned Ground Robotics

We have several navigation algorithms to choose from and can switch among them on the fly. However, we have found that the simplest and easiest one works best. The Robocar needs to make only local decisions and does not need to keep a map of its environment. It just needs to make quick use of the data provided by its sensors.

Rather than looking at all the sensor information separately, the arbitrator merges the suggestions together into one total suggestion. It then looks at the occupancy grid portion of the total suggestion to find badness in relationship to itself. Badness can be either a painted line or an obstacle—it doesn't really matter to the robot which—and must be avoided. The robot looks left, then right to find the left-most and right-most badness. It then tries to steer between the two. If there is badness only on one side, it tries to give the badness wide clearance—at least half the track.

This is one of many algorithms to which we can switch, but it seems to work well and is fairly straightforward. Kevin, of course, uses different algorithms which take into account current and desired position as well as surrounding terrain. Our simple algorithm works well for the competition.

Working on the Robocar project has been a very rewarding and exciting experience. There is nothing quite so pleasant as watching something you have built and programmed move on its own. Switching to Linux has allowed us to improve our robotics software and to use our favorite development tools. We hope to do well in this year's contest as a result. But even if we do not, we will have a good platform for next year and will have learned a little more about building robots and robot navigation.

Contributors/Contacts

The Robocar Team

Robocar Race Results