Spring2010RobotLabAssignment3 - Revision history

Urlass: /* Assignment 3: "Where am I" */

2010-05-06T15:42:48Z

Assignment 3: "Where am I"

2010-05-05T13:09:40Z

THIS ASSIGNMENT IS NOT COMPLETE YET, READ AT YOUR OWN RISK!!

2010-05-05T13:09:25Z

Additional Requirements

2010-05-04T23:44:56Z

Assignment 3: "Where am I"

2010-05-04T23:43:45Z

Grading

2010-05-04T23:43:28Z

Grading

2010-05-04T23:42:46Z

Grading

2010-05-04T23:41:24Z

Assignment 3: "Where am I"

2010-05-04T23:40:26Z

Additional Requirements

2010-05-04T21:53:06Z

Grading

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 In this assignment, you will use the Roomba model robot to perform simultaneous location and mapping (SLAM).  Your robot will be placed in a random location in the world, and needs to construct a map of the world.  The robot does not know it's location or orientation.  The robot should create the map as it explores it, that is, it should NOT wait until it has explored the entire world to produce a map.  If your robot is stopped at an arbitrary point in time, it should have ''some'' kind of map written, representing what it has seen so far.
-In the first part of the problem, you will generate a map using dead-reckoning.  In the second part, you will generate a map using an odometer-based technique.  In the optional extra credit, you will combine measurements from these techniques to make a more accurate map.
+In the first part of the problem, you will generate a map using dead-reckoning.  In the second part, you will generate a map using an odometer-based technique.  In the optional extra credit, you will combine measurements from these techniques to make a more accurate map.  In both parts, you may use the laser range finder.
 ===Configuration Files===

← Older revision		Revision as of 13:09, 5 May 2010
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−	~~='''THIS ASSIGNMENT IS NOT COMPLETE YET, READ AT YOUR OWN RISK!!'''=~~
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	[[Category:Robot Lab (Spring 2010)]]		[[Category:Robot Lab (Spring 2010)]]
	==Assignment 3: "Where am I"==		==Assignment 3: "Where am I"==

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 * You may not hard code turns or rely on anything particular to the provided map.  If your robot were to run on a map with the landmarks in a different location it should still work.
-* In the dead-reckoning portion, you may not use getX(), getY(), getYaw(), getData(), or getGeom() in the Position2DInterface class.  If you find some other functions that report the robots location or orientation, you can't use them either.
+* In the dead-reckoning portion, you may not use getX(), getY(), getYaw(), getData(), or getGeom() in the Position2DInterface class.  If you find some other functions that report the robots location or orientation, you can't use them either.  For the odometry portion, you should use these functions.
 * The maps produced by your robot should be in some reasonably common image format such as XPM, PNG, JPEG, etc.

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 ==Assignment 3: "Where am I"==
-In this assignment, you will use the Roomba model robot to perform simultaneous location and mapping (SLAM).  Your robot will be placed in a random location in the world, and needs to construct a map of the world.  The robot does not know it's location or orientation.  The robot should create the map as it explores it, that is, it should NOT wait until it has explored the entire world to produce a map.
+In this assignment, you will use the Roomba model robot to perform simultaneous location and mapping (SLAM).  Your robot will be placed in a random location in the world, and needs to construct a map of the world.  The robot does not know it's location or orientation.  The robot should create the map as it explores it, that is, it should NOT wait until it has explored the entire world to produce a map.  If your robot is stopped at an arbitrary point in time, it should have ''some'' kind of map written, representing what it has seen so far.
 In the first part of the problem, you will generate a map using dead-reckoning.  In the second part, you will generate a map using an odometer-based technique.  In the optional extra credit, you will combine measurements from these techniques to make a more accurate map.

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 ** Capturing all of the shapes on the map:  5 pts.
 ** Accuracy of the shapes and their relative positions:  5 pts.
-* Quality of techniques for fusing (combining) the data, and quality of the map it produces: up to 6 extra points.
+* Quality of techniques for fusing (combining) the data from both approaches, and quality of the map it produces: up to 6 extra points.
 '''TOTAL = 20 points + 6E.C.'''
 ===Map===
 [[File:Slam-map.png]]

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 ===Grading===
 * Quality of odometry-based map: up to 10 pts.
 * Quality of dead-reckoning-based map: up to 10pts.
 * Quality of data fusion techniques and map: up to 6 extra points.
 '''TOTAL = 20 points + 6E.C.'''

← Older revision		Revision as of 21:53, 4 May 2010
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	* Quality of data fusion techniques and map: up to 6 extra points.		* Quality of data fusion techniques and map: up to 6 extra points.
	'''TOTAL = 20 points + 6E.C.'''		'''TOTAL = 20 points + 6E.C.'''
		+
		+	===Map===
		+	[[File:Slam-map.png]]