Autonomous Mobility on Demand: From Car to Fleet

Note

This is the old version. For current (Fall 2023) go to the Moodle

Description

Autonomous Mobility on Demand systems based on self-driving cars will make a huge impact in the world. This class describes the basics of modeling, perception, planning, control and learning for self-driving cars. The focus is on integration and co-design of components and behaviors. The course has a heavy experimental component based on the Duckietown platform.

Lectures

2 lectures per week for 14 weeks.

Policies

All organizational communication happens on the Duckietown Slack, in the external page#ethz-amod20-students channel.
All technical questions should be asked on the Duckietown StackOverflow. Answering other students' questions is strongly encouraged!
If you have any hardware issues with your robot or your city, contact Rafael Fröhlich either on Slack or via email.
Exercises form 100% of your grade.
Each one of you will have 15 days of personal "time bank" for late deliveries, throughout the course.

Lecture Materials

The lecture slides will be uploaded after each lecture.

Lecture 1 |

DownloadOn The Duckietown Project (PDF, 126 MB)

DownloadThe Duckietown Platform (PDF, 34 MB)

DownloadAIDO (PDF, 26.1 MB)

DownloadAMoD Class Organization (PDF, 3.4 MB)

DownloadQuestionnaire and Next Steps (PDF, 1.2 MB)

Lecture 2 |

DownloadWelcome to AMOD 2020 (PDF, 2.2 MB)

DownloadIntroduction to Autonomous Vehicles (PDF, 14.1 MB)

Lecture 3 |

DownloadModern Robotic Systems (PDF, 10.4 MB)

DownloadArchitectures (PDF, 10.3 MB)

DownloadTesting 1 - Testing systems (PDF, 4.5 MB)

DownloadWhat's in the box (PDF, 7 MB)

Lecture 4 |

DownloadTesting 2 - Testing in Duckietown (PDF, 2.8 MB)

DownloadVersion control (PDF, 7.3 MB)

DownloadContainerization (PDF, 14.1 MB)

Lecture 5 |

DownloadMiddleware and ROS (PDF, 9.7 MB)

DownloadAutonomy architectures (PDF, 12.4 MB)

Lecture 6 |

DownloadRepresentations (PDF, 885 KB)

DownloadModelling (PDF, 21.7 MB)

DownloadOdometry calibration (PDF, 8.9 MB)

DownloadIntroduction to control systems (PDF, 24.3 MB)

DownloadControl in Duckietown (PID) (PDF, 22.3 MB)

Lecture 7 |

DownloadComputer vision I: Overview (PDF, 72.2 MB)

DownloadComputer vision II: Image acquisition (PDF, 43.1 MB)

DownloadComputer vision III: Pinhole camera model (PDF, 61.9 MB)

DownloadComputer vision IV: Camera calibration (PDF, 17.9 MB)

Lecture 8 |

DownloadRobust Fitting (PDF, 2.8 MB)

DownloadImage filtering (PDF, 2.9 MB)

DownloadImage Gradients (PDF, 3.1 MB)

DownloadEdge and corner detector (PDF, 4.8 MB)

Lecture 9 |

DownloadRepresentations (PDF, 18 MB)

DownloadBayes filter (PDF, 16.1 MB)

DownloadParticle filter (PDF, 16.3 MB)

DownloadLane filter (PDF, 26.3 MB)

Lecture 10 |

DownloadPlanning I: Graphs (PDF, 7.5 MB)

DownloadPlanning II: Motion planning (PDF, 23.7 MB)

DownloadPlanning III: Sampling based (PDF, 9.3 MB)

Lecture 11 |

DownloadMachine learning in robotics (PDF, 18.8 MB)

Lecture 12 |

DownloadRobotic perception (PDF, 31 MB)

Lecture 13 |

DownloadReinforcement learning (PDF, 7.5 MB)

Information about the exercises will follow as the course progresses.

Assignment 1 |

Read and do the exercises in Units A1, A2, and A5 external pagehere.
Deliverable: external pagehttps://tinyurl.com/amod-ethz-hw-1-answers
Deadline: Monday Oct. 5th, 13:59 CET

Assignment 2 |

Read and do the exercises in Units B1-B6 external pagehere.
DO NOT DO B2.3, B5.4 and B5.5.
Deliverable: https://tinyurl.com/amod-ethz-hw-2-answersexternal page
Deadline: Tuesday Oct. 13th, 23:59 CET

Assignment 3 |

Read and do the exercises in:
- external pageRH1 Sections A-3, A-4, A-6 (Excluding A-6.2)
- external pageRH2 Sections B-2.3, B-5.4, and B-5.5
Deliverable: external pagehttps://tinyurl.com/amod-ethz-hw-3-answers
Deadline: Tuesday Oct. 20 2020, 23:59 CET

Assignment 4 |

Read and do the exercises in:
- external pageRH3 All sections
- external pageRH4 Sections D-1 and D-2.1
Deliverable: external pagehttps://tinyurl.com/amod-ethz-hw-4-answers
Deadline: Wednesday Oct. 28 2020, 09:59 CET