CS 371 - Introduction to Artificial Intelligence
Fourth Hour Robotics Project


Due: Last day of class
Note: Work is to be done in three teams (formed in class).

Fall 2024 Robotics Challenge

The Fall 2024 Robotics Challenge consists of 2 challenges for 3 teams. There is a Google Doc distributed to the class early this semester to support construction of the robots.

Pioneer Team

Constructor Teams

Line-Following Challenges

In addition to making line-following code more reliable and/or better performing, there are a hierarchy of additional challenges that past Lego robotics teams have worked to achieve. Their documentation can help provide some insight to such challenges, although the kinematics of the new PiCar-X robot makes some aspects easier (additional sensor information) or more difficult (non-zero turning radius).

  1. Challenge #1 - Line-Following: Implement robot line-following that will follow a line through sudden turns up to 90 degrees.
  2. Challenge #2 - Intersection-Finding: Implement robot line-following that will follow a line as in (1), but stop when it comes to an intersection of two or more lines.
  3. Challenge #3 - Intersection-Choosing: Implement robot line-following that will, beyond (1) and (2), exit the intersection at the nth spoke clockwise from the line it travelled.
  4. Challenge #4 - Intersection-Traversing: Implement robot line-following that will perform (3) in succession given n1, n2, n3, ...
  5. Challenge #5 - Search and Traverse: Implement robot line-following that, given a graph topology, its current intersection and heading, and its goal intersection and heading, will generate a sequence of moves and perform (4).
  6. Challenge #6 - Localize, Search, and Traverse: Implement robot line-following that, given all that is given in (4) except its current intersection and heading, will take action to ascertain its state (localize), and then perform (5).
  7. Challenge #7 - Explore, Search, and Traverse: Implement robot line-following that explores lines and intersections, forms a graph roadmap, and navigates to a graph intersection with the following property: Let d(i,j) be the minimum number of edges to travel to get from intersection i to intersection j.  Let D(i) be max(d(i,j)) for all j.  A goal intersection has the minimum D(i).

Reference Links