Problem 2103. Simple Robotics 1: On track?

Created by Marcel

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>As a small extension to problem:</w:t></w:r><w:r><w:t> </w:t></w:r><w:hyperlink w:docLocation=\"http://www.mathworks.com/matlabcentral/cody/problems/2100-distance-to-a-straight-line-2d-given-any-2-distinct-points-on-this-straight-line\"><w:r><w:t>http://www.mathworks.com/matlabcentral/cody/problems/2100-distance-to-a-straight-line-2d-given-any-2-distinct-points-on-this-straight-line</w:t></w:r></w:hyperlink><w:r><w:t>, imagine that Pe represents the attitude of a robotic end effector with 3 degrees of freedom (x,y and tht).</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>The end-effector (kind of orange) has to stay parallel to the straight line within a distance indicated by \"errorlevel\". The error levels for the distance are 1 cm (ridiculous accuracy) and .5 degrees for the end effector angle.</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:t>Write a function which returns true if the end-effector is \"on track\" and false if the position of the origin of the coordinate frame which is considered to be attached to the centre of the end effector, falls outside the area indicated by the dash-dotted line. Also return false if the end effector orientation is too far off from the direction of the straight line.</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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"}]}

As a small extension to problem: <a href = "http://www.mathworks.com/matlabcentral/cody/problems/2100-distance-to-a-straight-line-2d-given-any-2-distinct-points-on-this-straight-line">http://www.mathworks.com/matlabcentral/cody/problems/2100-distance-to-a-straight-line-2d-given-any-2-distinct-points-on-this-straight-line</a>,
imagine that Pe represents the attitude of a robotic end effector with 3 degrees of freedom (x,y and tht).<img src = "http://3.bp.blogspot.com/-Quk1HnM9BF4/UtU4GvT5NhI/AAAAAAAAAC4/wSltlKZRlok/s1600/ontrack.jpg">The end-effector (kind of orange) has to stay parallel to the straight line within a distance indicated by "errorlevel". The error levels for the distance are 1 cm (ridiculous accuracy) and .5 degrees for the end effector angle.Write a function which returns true if the end-effector is "on track" and false if the position of the origin of the coordinate frame which is considered to be attached to the centre of the end effector, falls outside the area indicated by the dash-dotted line. Also return false if the end effector orientation is too far off from the direction of the straight line.

Solve

Solution Stats

16 Solutions
7 Solvers

Last Solution submitted on Apr 01, 2019

Last 200 Solutions

Problem Comments

Problem Recent Solvers7

Problem Tags

Community Treasure Hunt

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

Start Hunting!

Problem 2103. Simple Robotics 1: On track?

Solution Stats

Last 200 Solutions

Problem Comments

Problem Recent Solvers7

Suggested Problems

More from this Author10

Problem Tags

Community Treasure Hunt

Problem 2103. Simple Robotics 1: On track?

Solution Stats

Last 200 Solutions

Problem Comments

Problem Recent Solvers7

Suggested Problems

More from this Author10

Problem Tags

Community Treasure Hunt

Players