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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
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Software Architecture
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Camera Controlling used ptzProxy() Creating Image captureframe
undefined jpeg Headerfile not accessible cameraproxy framgrabber Undefined inbuilt function Downloaded header; not compiling
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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
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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
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LIDAR Function ID 2 : Intersection Scans 180 degrees
Translates points of objects detected Compare with intersection coordinates Wait/Go
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Way-point Following The Initial Problem The Solution (Look-Up Table)
The Implementation The Calibration
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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.
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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.
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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.
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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.
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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
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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.
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Intersection Problem How to determine if we are at an intersection
How to determine if there is a stop sign for the intersection
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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
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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
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Conclusion Control Issues Point Translation and Boundary Conditions
Driving Control LiDAR Function Obstacle Avoidance Intersection Navigation
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Questions
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