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# \[ME336] Collaborative Robot Learning

2022 Spring

## Course Description

The course introduces collaborative robots and robot learning, connecting robot design and perception with machine learning, neural networks, sequential decision-making and artificial intelligence. The introductory lecture describes the aim as a structural, object-centric decomposition of unstructured physical interactions into shareable and reproducible machine intelligence through design and learning.

## Course Instructor & Teaching Team

**Instructor:** Song Chaoyang\
**Institution:** Southern University of Science and Technology (SUSTech)\
**Term:** 2022 Spring

## Grading Policy

Course assessment consists of classroom participation and three individual projects:

| Component               | Weight | Requirements                                                                    |
| ----------------------- | ------ | ------------------------------------------------------------------------------- |
| Classroom participation | 10%    | One point per attendance check, over 15 weeks, normalized to the 10% component. |
| Individual project 1    | 30%    | Code submission 10%; video report 10%; presentation slides 10%.                 |
| Individual project 2    | 30%    | Code submission 10%; video report 10%; presentation slides 10%.                 |
| Individual project 3    | 30%    | Code submission 10%; video report 10%; presentation slides 10%.                 |

Each project is completed individually. Code is assessed for successful execution, coverage of the assigned task, documentation, readability and reuse. Videos and presentation slides are assessed for technical background, implementation explanation, demonstration, structure and discussion; compliance with submission requirements and timing also appears in the rubric.

[Download the assessment criteria (DOCX)](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FGfgbP8iEw2AIFmFw742m%2F220629-%E3%80%8CME336%E5%8D%8F%E4%BD%9C%E6%9C%BA%E5%99%A8%E4%BA%BA%E5%AD%A6%E4%B9%A0%E3%80%8D%E8%AF%BE%E7%A8%8B%E8%AF%84%E5%88%86%E6%A0%87%E5%87%86.docx?alt=media\&token=de21c81e-b009-49aa-a9d1-caea3ed08da2)

## Teaching Schedule

* [Lecture 01 — Course Introduction](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FrZr0Pb5depXOa3f2gys8%2FLec01-CourseIntro.pdf?alt=media\&token=a2b5096b-2a50-4041-9785-46131f59f630)
* [Lecture 02 — Cobot Design](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FT3n6Rf6Fayml86WFoisW%2FLec02-CobotDesign.pdf?alt=media\&token=3cbab339-d68a-4488-9bd2-13336dde0700)
* [Lecture 03 — Robot Perception](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FNnEt6bTnkFvzEbleM36z%2FLec03-RobotPerception.pdf?alt=media\&token=36e9234d-156e-46ab-93f7-294263063025)
* [Lecture 04 — Machine Learning I — Machine Learning Basics](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2Fw4deQWQn4BtPxhngCJwA%2FLec04-LearningBasics.pdf?alt=media\&token=b25d271d-658f-40af-9b4a-7a669293e89c)
* [Lecture 05 — Machine Learning II — Statistical Binary Classification](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FYHrgfuaoDIMkPRYRFdHf%2FLec05-Classification.pdf?alt=media\&token=173b155a-1673-4e2f-b568-efb4b6c8818f)
* [Lecture 06 — Deep Networks I — Neural Networks](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FmQPs2xsTbGLPn44j3O30%2FLec06-NetworkBasics.pdf?alt=media\&token=ca828f87-8980-4206-a727-323948bb1b24)
* [Lecture 07 — Deep Networks II — Convolutional Networks](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FB4BHjYFI1FGGt0kYWR7A%2FLec07-ConvNetworks.pdf?alt=media\&token=ef858557-1db5-437c-8b3f-09f19a0621b8)
* [Lecture 08 — Network Tuning I — Regularization](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FOtW0RAvsWLSfJ6odNBGx%2FLec08-Regularization.pdf?alt=media\&token=260e19ba-2539-413f-89b1-b3ff3da55ea5)
* [Lecture 09 — Network Tuning II — Optimization](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FgmBRJcErVEICVeBQqfhi%2FLec09-Optimization.pdf?alt=media\&token=0c968e9d-20b0-4829-a352-c51c8ac6c8be)
* [Lecture 10 — Markovian Modeling I — Sequential Decision Problems](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FY6oLDcfu0jGhzXqDX6vj%2FLec10-MarkovianBasics.pdf?alt=media\&token=e70ebbf1-6126-4df8-83c1-708c127acb41)
* [Lecture 11 — Markovian Modeling II — Policy Iteration](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FVOCftDmHLTOM0VB5DVW2%2FLec11-MarkovianLearning.pdf?alt=media\&token=bb0e4e18-7ad2-4112-baaf-dee309ee03cd)
* [Lecture 12 — Artificial Intelligence](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FUpLbhY8zYc2PTkmE9uva%2FLec12-Artificial%20Intelligence.pdf?alt=media\&token=8dc67a62-d08e-4b9d-a9f7-dfff21985b52)
* [Lecture 13 — Rational Agents](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FaId7wUvtb9fSj7WCQoji%2FLec13-Rational%20Agents.pdf?alt=media\&token=a699881f-fb42-4549-bd08-61b29bc745f5)
* [Lecture 14 — AI meets Design](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FTJ4b7hzwMQT327aVYKMP%2FLec14-AImeetsDesign.pdf?alt=media\&token=93e27a78-99d6-4614-851a-2c937117aa2f)

## Course Materials & Resources

### Supporting Readings

* [A Review of Robot Learning for Manipulation](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FpnQJCHRxdjUUahBee3Io%2FReadings-A%20Review%20of%20Robot%20Learning%20for%20Manipulation.pdf?alt=media\&token=783c5a2f-e2cb-4651-81b2-8d382fb93d9c)
* [Cobot Design — original patent reading US8614559](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2F76L7uVGExSawCuLUvgtZ%2FLec02-CobotDesign-Reading-US8614559.pdf?alt=media\&token=49ed2679-6d7f-4f0a-b506-93ba756d6027)

### AI meets Design

The final-week lecture credits adaptation from AI meets Design. Resources and worksheets:

* [AI meets Design Attachments.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FSEB1eSgWmORojTStNL27%2FAI%20meets%20Design%20Attachments.pdf?alt=media\&token=028aaf20-55bd-41df-bf09-a48d34e9d38c)
* [AI meets Design Card Deck V1.0.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2Fui3HfzGerimGh5LwJtHB%2FAI%20meets%20Design%20Card%20Deck%20V1.0.pdf?alt=media\&token=f1212c3c-e9bc-4e5e-b8e8-440b9e69d7f1)
* [AI meets Design Toolkit V1.0.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FJvbaYNU4x7QUj9bhTtOp%2FAI%20meets%20Design%20Toolkit%20V1.0.pdf?alt=media\&token=5e5a2268-f521-4360-bcaf-6b485f998f81)
* [DfH-Card-Deck-manual.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FfWaqG720qKGI7UwdZof9%2FDfH-Card-Deck-manual.pdf?alt=media\&token=438c16a6-2c39-459f-8ed0-90cc5e12def7)
* [DfH\_Card\_Deck\_online.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FyJgalSCk2B6qh7eqRWT1%2FDfH_Card_Deck_online.pdf?alt=media\&token=34e55763-34ba-491e-8cb0-ade6f42a74c3)
* [machine-learning-for-designers.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FwOsBzsD6UP8GVN5Woe90%2Fmachine-learning-for-designers.pdf?alt=media\&token=df20893c-13ca-4b38-87ae-a7d451c9c61c)

#### Worksheets

* [AI x Design - Benchmarking.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FhPVTl19d6sm5h8T1cfEG%2FAI%20x%20Design%20-%20Benchmarking.pdf?alt=media\&token=cb7671a9-b907-4387-adbf-6f6f47ca47d3)
* [AI x Design - Confusion matrix.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FPEVZQDntP9I7RP7GeXsJ%2FAI%20x%20Design%20-%20Confusion%20matrix.pdf?alt=media\&token=8ffeaf6b-be55-4283-8b53-f341171ad5f7)
* [AI x Design - Consequence wheel.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2F1eI6fUHIq57oB2Ki1bhK%2FAI%20x%20Design%20-%20Consequence%20wheel.pdf?alt=media\&token=d010278f-4fb8-48a9-ad75-b66096bccde9)
* [AI x Design - Plotting your model.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2F5RLK7Sx2gNpkerijDhIU%2FAI%20x%20Design%20-%20Plotting%20your%20model.pdf?alt=media\&token=1e58d7d1-3575-492c-83da-fd53b2d4544d)
* [AI x Design - UX of AI.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2F39MaahMljLAUKlcSv8Et%2FAI%20x%20Design%20-%20UX%20of%20AI.pdf?alt=media\&token=8f966854-1c3e-483b-bf86-e0048f871f11)
* [AI x Design - Value polarities.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2FQW5gK7NK39xPGa9Ueetl%2FAI%20x%20Design%20-%20Value%20polarities.pdf?alt=media\&token=43f803c9-d7f1-40b5-bffb-92bee6349bf6)
* [AI x Design - Value proposition statement.pdf](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYvpzAsXljzlV13XLZ7h2%2Fuploads%2F5RVVFYujzd7XOaDhkTXe%2FAI%20x%20Design%20-%20Value%20proposition%20statement.pdf?alt=media\&token=8ef9a95b-44c2-426b-a706-d68a29ec8231)

### Academic Calendar

![SUSTech academic calendar for 2021–2022 Spring and Summer semesters](https://content.gitbook.com/content/YvpzAsXljzlV13XLZ7h2/blobs/Jyk1KtTNgGE2jTLCsQ5t/22Calendar.jpg)


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