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Final Report Alpha Squad Seven

Final Report Alpha Squad Seven. Members: Erik Bass Benjamin Carter Rahul Kapoor Steven Koegler Jared Schlicher Matthew Werner Coach: Alex Hsieh Date: 3/15/07. Software Architecture. Camera. Controlling used ptzProxy() Creating Image. Point Translation and Boundaries.

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Final Report Alpha Squad Seven

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  1. Final ReportAlpha Squad Seven Members: Erik Bass Benjamin Carter Rahul Kapoor Steven Koegler Jared Schlicher Matthew Werner Coach: Alex Hsieh Date: 3/15/07

  2. Software Architecture

  3. Camera • Controlling used ptzProxy() • Creating Image

  4. Point Translation and Boundaries • Use Direction and Robot relative points to find global points • Robot relative points come from the lidar • Robot direction based on Δx and Δy • Global points checked to with boundary conditions • Boundaries are the G.P.S. coordinates of the walls

  5. LIDAR Function • ID 1 : Object Avoidance • Filters out objects out of the box • Returns y-distance (R) of closest object • Y-dimension is a variable • X-dimension hardcoded at .7 m

  6. LIDAR Function • ID 2 : Intersection • Scans 180 degrees • Translates points of objects detected • Compare with intersection coordinates • Wait/Go

  7. Way-point Following • The Initial Problem • The Solution (Look-Up Table) • The Implementation • The Calibration

  8. The Initial Problem • The way-point program initially had problems when the robot was not aligned properly with the first way-points. • Swerve back and forth on the ideal line from one way-point to the next. • However if the robot was aligned properly to the first way-point, the robot could navigate the given seven way-points with some what of a smooth line.

  9. The Solution • Create a look up table based on two values the angle and distance to the way-point. • The look up tables angle was incremented in units of fifteen degrees until it reached seventy five degrees. • The distance started at 0.5 m and was incremented by a full meter until the distance reached 4.5 m. • With five distance states and six angle states the table gives a total combination of thirty steering inputs.

  10. The Implementation • The look-up table was implemented in C++. • Six stacked if-else conditional statements for the angle check. • Nested if-else statement for the distance check. • With in the appropriate if-else statement the steering angle is assigned.

  11. The Calibration • First every steering input was set at the maximum steering. • Adjusted the steering for the table by multiplying the maximum steering by a value from zero to one, basically to take a percentage of the maximum steering available depending on the state. • Then entered a guess for each state, through trial and error for way-point following, tuned the steering. • Applied the table to the intersection problem, the lane change problem, and then to object avoidance problem and made adjustments where they were needed.

  12. Object Avoidance • Use Lidar to scan for object • When object is found check distance • Ignore large distances • If distance too small stop • If distance in between then • If link has 1 lane then stop • If link has 2 lanes then switch lanes

  13. Lane Switch Logic • Find current lane position • Create line based on opposite lane points • Found using two closest opposite lane points • Once line is found create a new waypoint in the other lane. • Once past the object switch back into original lane.

  14. Intersection Problem • How to determine if we are at an intersection • How to determine if there is a stop sign for the intersection

  15. Reading the Network File • The Intersection Problem is solved by reading the Network File • The Network file contains node and stop sign information • The code reads this information to determine if the robot is at the end of a link • Then the code determines if there is a node at the end of the link the robot is located at • Finally, the code determines if the node contains a stop sign

  16. Navigating an Intersection • If stop sign, then stop for set time • During stop use lidar data to determine if an object is within defined intersection • If object is, pause for more time than initial stop • If object is not, proceed after initial pause • If node has no stop sign, continue driving

  17. Conclusion • Control Issues • Point Translation and Boundary Conditions • Driving Control • LiDAR Function • Obstacle Avoidance • Intersection Navigation

  18. Questions

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