1. Team RoboTrek Matt Kabert Ryan Bokman Vipul Gupta Advisor: Rong Xu

2. Outline Possible Algorithms Possible Algorithms Algorithm we chose Algorithm we chose Problems we faced Problems we faced Correction schemes Correction schemes Results Results How can it be improved How can it be improved

3. Possible Algorithms Grid Mapping Grid Mapping Trace the path of lowest value sub cells Trace the path of lowest value sub cells Potential Grid Mapping Potential Grid Mapping Obstacle positive charge and GPS point negative charge. Obstacle positive charge and GPS point negative charge. Follow lowest resistance path Follow lowest resistance path Line Scanning Line Scanning Scan at different angles and take obstacle free path. Scan at different angles and take obstacle free path.

4. Algorithm Based on the line scanning method with the LIDAR Based on the line scanning method with the LIDAR Determines the best path to proceed towards the next GPS point Determines the best path to proceed towards the next GPS point Constantly re–evaluates the path to determine the best possible. Constantly re–evaluates the path to determine the best possible.

5. Obstacle Avoidance Uses LIDAR to find an obstacle Uses LIDAR to find an obstacle Starts Scanning from the center Starts Scanning from the center Finds a clears spread of 50° closest to the path straight ahead Finds a clears spread of 50° closest to the path straight ahead Checks for obstacles on each side of the robot and uses their distance for calculating turn rates Checks for obstacles on each side of the robot and uses their distance for calculating turn rates Highest Priority Highest Priority

6. Obstacle Avoidance

7. GPS points Waypoints hard coded in to the program Waypoints hard coded in to the program GPS to calculate the slope and heading GPS to calculate the slope and heading Problems with GPS data Problems with GPS data Very Noisy Very Noisy Use average in place of absolute value Use average in place of absolute value Canadian wide area differential correction scheme Canadian wide area differential correction scheme

8. Heading Heading turn rate was determined using the error between the desired heading and the current heading. Heading turn rate was determined using the error between the desired heading and the current heading. In this case error = 50 – 310 => -260. In this case error = 50 – 310 => -260. If-statements translate this by adding 360 so that we want to turn +100 degrees. If-statements translate this by adding 360 so that we want to turn +100 degrees. +100 is the main factor in calculating the turn rate. +100 is the main factor in calculating the turn rate. Positive is turning left, negative is turning right. Positive is turning left, negative is turning right.

9. Competition Required to cover a path defined by 33 GPS points Required to cover a path defined by 33 GPS points Avoid all obstacles Avoid all obstacles Stay with in 5 m Stay with in 5 m Team that takes Team that takes the least time wins. the least time wins.

10. Final Run

11. Results Successfully tracked all the 33 GPS points Successfully tracked all the 33 GPS points Without hitting any obstacle Without hitting any obstacle Took 11 min 05 sec to complete the course Took 11 min 05 sec to complete the course Other Team took 10 min 15 sec Other Team took 10 min 15 sec

12. How can this be improved Optimize the turn rate Optimize the turn rate Turn rate as a function of the distance from the next GPS point Turn rate as a function of the distance from the next GPS point Higher speed selection Higher speed selection

13. Questions ?