> For the complete documentation index, see [llms.txt](https://x.ancorasir.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://x.ancorasir.com/des5002/des5002-2025-autumn/readme.md).

# DES5002 Designing Robots for Social Good

Autumn 2025

## Course Description

This course exemplifies the technical and ethical guidelines in designing robots for social good. The course introduces the principles, materials, design, and modeling of robotic agents for physical interactions with the environment, helping students understand the basic concepts and core technologies of robotics. The course further takes a theme-based and case-driven approach to help students identify the key factors in designing robots for social good and practice them in a design challenge.

## Learning Outcomes

At the end of this course, students will be able to:

1. Conduct analysis of robotic systems in terms of technical and ethical aspects.
2. Adopt advanced technologies in designing robotic systems.
3. Demonstrate ability to align technical and ethical guidelines in designing robots for social good.

## Content Summary

The course covers robotics and social good, soft robotics, humanoids, data and machine learning, AI applications in sound, image, text and body, and AI risk. Lectures are complemented by case-study workshops, tutorials, an interim review and a final review. Students review three cases individually and work in teams of three to propose a robot for social good, communicating hardware design, intelligence and human–robot interaction through two posters.

## Course Instructor & Teaching Team

* Lead Instructor: Dr. Wan Fang
* Teaching Assistant: Zhang Tuo
* Office: Level 3, Zhiyuan

## Grading Policy

* (10%) Attendance — recorded during each class by Teaching Assistants.
* (20%) Individual Assignment — review three case studies and submit and present slides.
* (70%) Team Project / Final Presentation — team posters on the design of robots for social good.

#### Individual Assignment — 20%

Choose a topic from a robot perspective (for example, robotic dogs or humanoids) or a social-good perspective (for example, education, companionship or public health). Search for and review three case studies: papers or products. Submit and present your slides.

#### Team Project — 70%

Propose a robot for social good using the robotics and AI knowledge learned in the course, focusing on the user, scenario, hardware/system design and interaction.

* Form a team of three students.
* Prepare two posters: one on hardware design and modeling; the other on intelligence/AI and human–robot interaction.
* Hardware/software prototypes are encouraged but are not required.

## Academic Integrity

This course follows the SUSTech Code of Academic Integrity. Students are expected to abide by that code. Work submitted by a student for academic credit must be the student's own work. Violations, including cheating, copying and non-approved collaborations, will not be tolerated.

## University Calendar

![](https://1357936236-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-62bb38515456ae47b45e2081eb48957f23e852bd%2Funiversity-calendar-2025-autumn.webp?alt=media)

## Recommended Textbook(s)

1. Ethically Aligned Design: A Vision for Prioritizing Human Well-being with Autonomous and Intelligent Systems.
2. Designing Robots, Designing Humans.
3. [Soft Robotics Toolkit](https://softroboticstoolkit.com/).
4. Coyle, Stephen, et al. “Bio-inspired soft robotics: Material selection, actuation, and design.” Extreme Mechanics Letters 22 (2018): 51–59.

![](https://1357936236-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-046ab40ed9445f2e041d01bc27c8c9635e207dcb%2FGuestLectureSeries-25Autumn-DES5002-Yoshihiko-Nakamura.webp?alt=media)

## Teaching Schedule

Dates follow the archived teaching-week table and university calendar, including the Week 05 Wednesday make-up class on Sat Oct 11.

[**Class 01: Introduction to Robots**](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-a9a4deca94c7ccfe9e2f5c95a74d31c13abd6387%2FWeek-01-Lecture-01-Introduction-to-Robots.pdf?alt=media) **|** Wed Sep 10, 1400–1550

[**Class 02: The Rise of Robotics and AI**](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-5cdc62d37bef6c235741dc506a09d80cd2a67a23%2FWeek-01-Lecture-02-The-Rise-of-Robotics-and-AI.pdf?alt=media) **|** Mon Sep 15, 0800–0950

[**Class 03: What is Social Good?**](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-9732f70ac6a5db0c30502d38cd86d61388b972d6%2FWeek-02-Lecture-03-What-is-Social-Good.pdf?alt=media) **|** Wed Sep 17, 1400–1550

~~**Class 04: Cancelled: Weather |** Wed Sep 24, 1400–1550~~

* *Team formation (Week 03).*

**Class 05: Workshop: Design case study |** Mon Sep 29, 0800–0950

* *Assignment submission (Week 04).*

**Class 06: Workshop: Design case study |** **Sat Oct 11, 1400–1550 (make-up class)**

[**Class 07: Soft Robotics I**](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-160c7051918b015a2744e89bda32ce871e2ebd9f%2FLecture-04-Soft-Robotics-I.pdf?alt=media) **|** Mon Oct 13, 0800–0950

[**Class 08: Soft Robotics II**](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-72708665695bce768ee9253d483eee66ae53b825%2FLecture-05-Soft-Robotics-II.pdf?alt=media) **|** Wed Oct 15, 1400–1550

[**Class 09: Humanoid**](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-9bda6099bf893b1c5483c5461b1c517470e3fd6e%2FLecture-06-Humanoid.pdf?alt=media) **|** Wed Oct 22, 1400–1550

**Class 10: Tutorial |** Mon Oct 27, 0800–0950

**Class 11: Workshop: Interim Review |** Wed Oct 29, 1400–1550

[**Class 12: Intro to Data and ML**](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-2195dd134769378a806178c728370320aa2fdaee%2FLecture-08-Intro-to-Data-and-ML.pdf?alt=media) **|** Wed Nov 05, 1400–1550

[**Class 13: AI + Basics**](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-83412c05ff72222008717c0ec1a6e288a3c6c649%2FLecture-09-ANN-and-CNN.pdf?alt=media) **|** Mon Nov 10, 0800–0950

[**Class 14: AI + Sound**](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-1254d1c815e2c65d68f210662d0b64ea4c77ec54%2FLecture-10-AIIDSound.pdf?alt=media) **|** Wed Nov 12, 1400–1550

[**Class 15: AI + Image**](https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2gGjXy5z7clF3yuXM2eT%2Fuploads%2Fgit-blob-061fdacaa6d6003c519fe53d7f6b805400872ef9%2FLecture-11-AIIDImage.pdf?alt=media) **|** Wed Nov 19, 1400–1550

**Class 16: AI + Text |** Mon Nov 24, 0800–0950

**Class 17: AI + Text |** Wed Nov 26, 1400–1550

**Class 18: AI + Body |** Wed Dec 03, 1400–1550

**Class 19: AI Risk |** Mon Dec 08, 0800–0950

**Class 20: Tutorial |** Wed Dec 10, 1400–1550

**Class 21: Tutorial |** Wed Dec 17, 1400–1550

**Class 22: Tutorial |** Mon Dec 22, 0800–0950

**Class 23: Final Review |** Wed Dec 24, 1400–1550

## Important Deadlines

* Team formation — Week 03.
* Assignment submission — Week 04.
* Interim review — Wed Oct 29.
* Final review — Wed Dec 24.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://x.ancorasir.com/des5002/des5002-2025-autumn/readme.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.