Problem 1650. LASER Tracker - Mirror Distance and Angle

Created by Richard Zapor

Solve Later

{"relationships":[{"relationshipType":"http://schemas.mathworks.com/matlab/code/2013/relationships/document","targetMode":"","relationshipId":"rId1","target":"/matlab/document.xml"},{"relationshipType":"http://schemas.mathworks.com/matlab/code/2013/relationships/output","targetMode":"","relationshipId":"rId2","target":"/matlab/output.xml"}],"parts":[{"partUri":"/matlab/document.xml","relationship":[{"relationshipType":"http://schemas.mathworks.com/matlab/code/2013/relationships/image","targetMode":"","relationshipId":"rId1","target":"/media/image1.JPEG"}],"contentType":"application/vnd.mathworks.matlab.code.document+xml","content":"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<w:document xmlns:w=\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\"><w:body><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:t>Determine the mirror's distance and relative angle to the LASER Tracker given the distances to a reference SMR (Spherical Mounted Retro-reflector) and the angle to the SMR.</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:customXml w:element=\"image\"><w:customXmlPr><w:attr w:name=\"height\" w:val=\"-1\"/><w:attr w:name=\"width\" w:val=\"-1\"/><w:attr w:name=\"relationshipId\" w:val=\"rId1\"/></w:customXmlPr></w:customXml></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:t>Theta is the included angle between d1 and d2.</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:t>Phi is the angle of interest and is between d2 and d3.</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:t>The Test method is locate the SMR to capture the mirror reflectance. Record L. Rotate the SMR to be directly viewed by the Tracker. Record d1 and Theta.</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:t>Given Theta, d1, and d2+d3 determine d2 and Phi.</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:rPr><w:b/></w:rPr><w:t>Input:</w:t></w:r><w:r><w:t> [d1, L, Theta] where L=d2+d3 and d1*cos(Theta) &lt; d2</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:rPr><w:b/></w:rPr><w:t>Output:</w:t></w:r><w:r><w:t> [d2 Phi]</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:rPr><w:b/></w:rPr><w:t>Examples:</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:t>Input: [2^.5, 2+2^.5, pi/4]..... Output: [2 pi/4]</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:t>Input: [2.3994, 4, .2991]..... Output: [3, pi/4 ]</w:t></w:r></w:p></w:body></w:document>"},{"partUri":"/matlab/output.xml","contentType":"text/xml","content":"<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\" ?><embeddedOutputs><metaData><evaluationState>manual</evaluationState><layoutState>code</layoutState><outputStatus>ready</outputStatus></metaData><outputArray type=\"array\"/><regionArray type=\"array\"/></embeddedOutputs>"},{"partUri":"/media/image1.JPEG","contentType":"image/JPEG","content":"data:image/JPEG;base64,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"}]}

Solve

Solution Stats

68 Solutions
27 Solvers

Last Solution submitted on Sep 10, 2021

Last 200 Solutions

Problem Comments

Problem Recent Solvers27

Problem Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Problem 1650. LASER Tracker - Mirror Distance and Angle

Solution Stats

Last 200 Solutions

Problem Comments

Problem Recent Solvers27

Suggested Problems

More from this Author255

Problem Tags

Community Treasure Hunt

Problem 1650. LASER Tracker - Mirror Distance and Angle

Solution Stats

Last 200 Solutions

Problem Comments

Problem Recent Solvers27

Suggested Problems

More from this Author255

Problem Tags

Community Treasure Hunt

Players