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CMPUT 412 Experimental Mobile Robotics

CMPUT 412 Experimental Mobile Robotics. Csaba Szepesv ári University of Alberta. Plan for today. Topic of the course Introduction/admin Expectations Requirements/Marking Course contents. Topic: Autonomous Driving. Goal: Cars should drive themselves

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CMPUT 412 Experimental Mobile Robotics

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  1. CMPUT 412Experimental Mobile Robotics Csaba Szepesvári University of Alberta

  2. Plan for today • Topic of the course • Introduction/admin • Expectations • Requirements/Marking • Course contents

  3. Topic: Autonomous Driving • Goal: Cars should drive themselves • Advantages: Less accidents, increased efficiency • History: 1961: Stanford cart 1987-1995: Dickmanns 180km/h, 1000km,human intervention,driving on highways 2005: DARPA Grand Challenge, 211 km desert course

  4. 2007 Autonomous parking systems (Lexus, Mercedes, Toyota,..) 2007: DARPA Urban Challenge Cybercars project

  5. Course project

  6. The tasks • Following prespecified routes in a "city" • [14 January - 28 January] • Task #1: Build a robot that follows a white tape, taped to the floor • Task #2: City-like environment, follow a prespecified route • Taxiing on demand,obstructions on the road • [29 January - 25 February] • Task #1: Picking up passengers at various locations and taxiing them to other locations. Uses bluetooth • Task #2: Parts of the route can become blocked. • Parking, dealing with traffic • [26 February - 7 April] • Task #1: Parallel parking • Task #2: Multiple robots on the road at the same time, avoiding collisions

  7. Admin

  8. Me.. • Studies: • Mathematics (Stat. and Prob.) • Computer Science • Research • Reinforcement learning (theory) • Machine learning (vision, robotics,..) • Experience • 5 years in industry (sw firm, speech, text, video) • 15 years of C++

  9. You..? • Fill out form!

  10. Schedule! • Lecture: TR 15:30-17:00 • Room: ETL E1 018 • Lab: W 14:00-17:00 • Room: CSC 229

  11. Office hours • Appointment: • szepesva@cs.ualberta.ca • Stop by! • Room: Ath 3-11 • Phone: x2-8581

  12. Information sources • Course webpage:ugweb.cs.ualberta.ca/~c412 • RLAI page:http://rlai.cs.ualberta.ca/openpages2/CMPUT412+2008 • Teaching Assistants: Azad Shademan, Neesha Desai • Instructional group support: • John Rodson (rod@ugrad.cs.ualberta.ca)

  13. Prerequisites • No official prerequisites • Brush up your knowledge in: • Calculus (MATH 114,115, 214) • Linear algebra (MATH 120 or 125) • Probability & stat (STAT 221) • Good to know about • Machine learning (CMPUT 466/551) • Programming: • C/C++

  14. Expectations

  15. Goals • Learn about robotics • Concepts • Techniques • Challenges • Complete the project • Have fun!

  16. Course format • Formal lectures (~3 weeks) • Background • Weekly project meetings • Discussion of progress • Challenges • Planning (to meat deadline) • Steady workload

  17. My contribution • I act like a supervisor • I define tasks • I provide background material (lectures, resources) • I answer questions • I evaluate your performance

  18. My expectations • You try your best to solve the assignments (it’s fun!) • You will act in a self-initiated manner • You ask questions • Cooperate, but contribute • You come to the lectures • You come to the labs • No cheating, plagiarism, misrepresentation of facts (see course webpage for detailed info)

  19. Marking

  20. How to get (good) marks? • This is a project based course => no final, or midterm • “Just” solve the problems

  21. Marking • No predefined grading system • Individual performances: Based on the reports, participation in the meetings, presentations, lectures • You are going to evaluate each others’ presentations

  22. (Your) class presentations • Be prepared • Keep structure: • Problem definition • Proposed solution • Evaluation • Conclusions • Use slides • Keep time limits [20 min]

  23. Reports • Title, authors • Introduction (max. 1 page): • the task and the challenges faced • Proposed solution (max. 1 page + figs): • possible alternatives, the decisions you took, how you arrived at them, measurements, data, related work • Evaluation (max. 1-2 pages + figs): • Evaluate your solution. Show to what extent it achieves the goal, describe its limitations • Conclusions (max. 1 page) • summarize your work • Sharing the work (1 page): • Who did what, how was the time spent • Format: • Preferably use LaTeX, high quality, compressed presentation

  24. 0th assignment • Task #1: SUBSCRIBE to the course’s open pages! • Task #2: Learn to use the open pages • Open pages: • Anyone can edit them (in the browser) • Send notification to subscribers • Add comments/questions to the end of the page

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