Soft Computing 1 Matlab Tutorial Kai Goebel, Bill Cheetham RPI/GE CRD [email protected]@cs.rpi.edu.
Goebel ROS SLAM - College of Science and Engineering
Transcript of Goebel ROS SLAM - College of Science and Engineering
Agenda Mobile Robots
Agenda March 29, 2021
1_Go Over HW 5 1 & 1a_5437_HW5_Answers_TLH.pdf
1b_Good_Sensor References for HW5.pdf
2_Talk about Project HW6 Due in 2 weeks
2a_Example Projects (See Folder Examples)
2b_New Research in Mobile_References.pdf
3_ Let’s See a Few Examples of Robot Navigation
My Introduction to Navigation Slides
IntroToNavigation_Presentation1.pptx
4_SLAM Examples from Textbook Page 145 to 200 in Textbook
5_Goebel Parameters
Goebel_ROS_SLAM.docx
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6_Useful SLAM Article Cyrill, John, and Sebastian
46.2 The Three Main SLAM Paradigms
Thurn_ProbabilisticRoboticsTheBook.pdf
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AGENDA CENG 5437 March 22, 2021 HW5 Due
REMIND ME TO RECORD WHEN NECESSARY. TURN OFF MY MIKE FOR
YOUTUBES!
1_5437_4391_Review_3_22_2021_Presentation1.pdf
2_5437_4391_Review_3_22_2021_FromMarch1_Presentation2.pdf
HOW DO ROBOTS NAVIGATE?
"Little Lost Robot" is a science fiction short story by American writer Isaac Asimov. It was first
published in the March 1947 issue of Astounding Science Fiction and reprinted in the collections I,
Robot (1950), The Complete Robot (1982), Robot Dreams (1986), and Robot Visions (1990).
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A few Definitions: Gaussian, Variance, Covariance
Odometry Errors and Variance:
3_Navigation_OdometryErrors&Variance3_22_2021Presentation1.pdf
(References Below)
SHOW MATLAB
4_Cook_varianceFiltered.pdf
Cook_varianceFiltered.m (Code and figures Below)
5_SensorFusion 5_sensor Fusion_References_3_2021.pdf
Play for about 4 minutes – MATLAB Tech Talk #1 Sensor Fusion
https://www.youtube.com/watch?v=6qV3YjFppuc&t=678s
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References for Navigation_Odometry_Errors Presentation_1 Magnus – DD Robot
https://www.youtube.com/watch?app=desktop&v=aE7RQNhwnPQ&sns=em
https://link.springer.com/chapter/10.1007/978-3-319-62533-1_5
Accurate odometry and error modelling for a mobile robot
https://www.google.com/search?q=accurate+odometry+and+error+modelling+f
or+a+mobile+robot&rlz=1C1GCEB_enUS887US887&oq=Accurate+odometry+and
+error+modeling&aqs=chrome.1.69i57j0i22i30.11974j1j15&sourceid=chrome&ie
=UTF-8
Aaron Becker
MATLAB
Nikolaus Correll 673 subscribers
The error propagation law explained in one and multiple dimensions using odometry as the running example. Matlab code is available on github. https://github.com/correll/Introducti...
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https://www.youtube.com/watch?v=ubg_AAM7Zd8 29:20
https://github.com/Introduction-to-Autonomous-Robots/Introduction-to-Autonomous-
Robots/tree/master/matlab
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March 8, 2021
Sensor Characteristics 2_SensorCharacteristicsPresentationiss_l2_Laplace.pdf
3_SensorsErrors2__Examples_Nike_TLH_AtoD.pdf
Sensor_Errors_Examples_Niku_R_AtoD
Niku and TLH Examples
Comparison of Types of Sensors
Sensor Chart from TI 4_SensorSummaryRadaretcChart.pdf
Let’s Drive
5_SensorsForSelfDrive_Videos_SP2021.pdf
How do self-driving cars “see”? - Sajan Saini 310,437 views •May 13, 2019 5:24 https://www.youtube.com/watch?v=PRg5RNU_JLk
TAKE A LOOK AT THE LIDAR AND INTEGRATED PHOTONICS TECHNOLOGIES THAT HELP SELF-DRIVING CARS
NAVIGATE OBSTACLES, NO MATTER THE ENVIRONMENT, WEATHER OR LIGHT.
Elon Musk on Cameras vs LiDAR for Self Driving and Autonomous Cars 149,830 views •Apr 27, 2019 10:23 See why Elton Musk thinks Cameras are better than Lidar sensors.
https://www.youtube.com/watch?v=HM23sjhtk4Q
TESLA AND ELON MUSK OUTLINE WHY THEY BELIEVE CAMERAS (VS LIDAR) ARE ALL THAT IS NEEDED FOR FULL SELF
DRIVING DURING THE TESLA AUTONOMY DAY FOR INVESTORS ON APRIL 22, 2019. ELON ALSO TOUCHES ON WHY
THEY DON'T CONSIDER HD MAPS AND PRECISION LANE MARKINGS TO BE ELON MUSK SAYS LIDAR "IS A FOOL’S
ERRAND" AND THAT ANYONE USING LIDAR IS "DOOMED."
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HE GOES ON TO SAY THAT THEY ARE "EXPENSIVE SENSORS THAT ARE UNNECESSARY. IT’S LIKE HAVING A WHOLE
BUNCH OF EXPENSIVE APPENDICES. LIKE, ONE APPENDIX IS BAD, WELL NOW YOU HAVE A WHOLE BUNCH OF THEM,
IT’S RIDICULOUS, YOU’LL SEE." THERE QUITE A BIT OF DEBATE IN THE SELF-DRIVING WORLD WHETHER LIDAR IS
TRULY REQUIRED FOR FULL SELF-DRIVING CAPABILITIES ON AUTONOMOUS VEHICLES. LIDAR PROVIDES VERY A VERY
ACCURATE, HIGH PRECISION DEPTH MAP OF THE WORLD AROUND THE CAR, BUT IS CURRENTLY STILL FAIRLY
EXPENSIVE AND ALSO HAS CHALLENGES SEEING THROUGH OCCLUSIONS, LIKE RAIN, SNOW AND FOG. TESLA'S
ARGUMENT IS THAT ROADS WERE BUILT FOR HUMAN DRIVERS WITH VISION AND THAT VISION SYSTEMS, SUCH AS
CAMERAS WILL DO A BETTER JOB TRAVERSING THAT ENVIRONMENT THAN OTHER SENSORS, READING ALL THE
VISION QUEUES MEANT FOR DRIVERS, LIKE ROAD SIGNS, ETC. IN ADDITION, TESLA BELIEVES THEIR VISION SYSTEM
(PLUS RADAR) ACCURATELY HANDLES DEPTH SENSING PROBLEMS AND THAT LIDAR IS NOT NEEDED FOR THAT
FUNCTION.
6_TI Radar Video.pdf
7_TI_radarSensors_spry311_ROS.pdf
Sensor Fusion 9,706 views •Jun 16, 2016 3:55
https://www.youtube.com/watch?v=JamDa-qNjPI
SensorPhysicsPresentation1.pptx