CS/EE/ME 75, 2006-07

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CS/EE/ME 75 Schedule Projects DGC Wiki Team Caltech

Instructors

  • Richard Murray, murray@cds.caltech.edu
  • Joel Burdick, jwb@robotics.caltech.edu
  • Lectures: TDB

Teaching Assistants

  • Noel duToit
  • Pete Trautman
  • Nok Wongpiromsarn

Announcements

Archive
  • 27 Aug 06: web page created

Course Syllabus

Course Description

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CS/EE/ME 75 presents the fundamentals of modern multi-disciplinary systems engineering in the context of a substantial design project. Students from a variety of disciplines will conceive, design, implement, and operate a system involving electrical, information, and mechanical engineering components. Specific tools will be provided for setting project goals and objectives, managing interfaces between component subsystems, working in design teams, and tracking progress against tasks. Students will be expected to apply knowledge from other courses at Caltech in designing and implementing specific subsystems. During the first two terms of the course, students will attend project meetings and learn some basic tools for project design, while taking courses in CS, EE, and ME that are related to the course project. During the third term, the entire team will build, document, and demonstrate the course design project, which will differ from year to year.

The third term of the course may be used to satisfy specific graduation requirements in the CS, EE, and ME options and may be taken for up to 18 units of total credit, with permission of the instructors. Freshman must receive permission from the instructor to enroll.

Course structure

CS/EE/ME 75 is designed to be integrated with the curriculum in the individual engineering disciplines. This is accomplished by linking the activities in the first two terms with regular classes in CS, EE and ME. These courses are used to design subsystems for the overall project, with the system integration occuring in the third term and the final implementation and operation occuring over the summer.

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Fall Courses
  • ME 72 - Design
  • CDS 110 - Control Systems
  • EE/CS/CNS 148 - Machine Vision
Winter Courses

Grading

In the first two terms, the course grade will be equally weighted between course homework sets (one each for the first three weeks), course participation in project and team meetings, and the final project presentation. For the third term, the course grade will be based on the following factors:

  • Homework (20%): Homework sets will be handed out weekly for the first five weeks of the class. Most sets will consist of some work that is done by the student's team, as well as a (short) individual portion
  • Team project reviews (20%): Each team will be required to present a review to an outside review team the end of the term. Each student on the team should give a portion of at least one of the presentations.
  • Project documentation (40%): All work performed as part of the class should be documented in an appropriate format (to be decided by the teams). Each individual will turn in the documentation for the items they are responsible by the end of the term.
  • Participation (20%): Students are expected to attend project and team meetings and to participate in a constructive manner toward the over goals of the team. Team coordinators and instructors will provide assessments for each student based on the level and quality of participation in project activities.

2006-07 Project

This year's project is the development of an autonomous vehicle capable of participating in the 2007 Urban Challenge, scheduled for 3 November 2007. The Urban Challenge is an autonomous vehicle competition involving up to 60 miles of autonomous driving in urban-like environments, including moving traffic, intersections, parking lots and traffic circles. The vehicle that completes the route in the shortest time under 6 hours wins the $2M grand prize.

For 2007, students in CS/EE/ME 75 will design, build, and document an autonomous vehicle capable of winning the urban challenge. The vehicle must be capable of operating in dynamic environments for 6 hours, at speeds of up to 30 miles per hour. This will require a level of sophistication in planning algorithms, sensor fusion and driving software substantially beyond current capabilities for autonomous vehicles.

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