151-0615-00L  Real-World Robotics - A Hands-On Project Class

SemesterHerbstsemester 2024
DozierendeR. Katzschmann
Periodizitätjährlich wiederkehrende Veranstaltung
LehrspracheEnglisch
KommentarRegistration is only possible up to 18.09.2024.
Students must also complete a Google Form (https://forms.gle/pnMHTCdZwgdawb519) by 18.09.2024 to be considered for the course.
Registered students and students on the waiting list will all be considered based on their submitted Google Forms.



Lehrveranstaltungen

NummerTitelUmfangDozierende
151-0615-00 AReal-World Robotics - A Hands-On Project Class
- The number of participants is limited to 40, spread across six teams.
- This project course has a dedicated classroom always accessible to the students.
- Focus talks, Q&A, and workshops will take place on Mondays from 14h to 16h.
120s Std.R. Katzschmann

Katalogdaten

KurzbeschreibungDuring this course, the students will develop an articulated robotic hand to solve a real-world robotic challenge: the robot must autonomously grasp and place objects. The students will learn the key theoretical concepts required to model, manufacture, control, and test their robot, alongside developing machine learning, programming, hardware, and engineering skills through the hands-on project.
Lernziel* Learning Objective 1: High-Level System Design
System and product design combined with requirement generation and verification are essential for this robotics project. The students will apply previously acquired system design knowledge and methods to a hands-on challenge.

* Learning Objective 2: Robot Design and Simulation
Students will gain experience implementing and simulating robotic systems using modern design, modeling, and simulation techniques such as CAD and Isaac Gym. These techniques are essential in any design process to understand the expected system behavior. This requires a thorough understanding of the system’s kinematics, dynamics, material, actuation principle, and physical limitations. Students will learn the theory and limitations behind modeling and simulation software.

* Learning Objective 3: Robot Fabrication
Students will learn to use the previously designed CAD models for successful robot fabrication. Additionally, the iterative nature of the process will allow them to develop their critical thinking skills in assessing the limitations of their design and possible sources for improvements. Building the robot will equip students with essential skills for using robots in the real world.

* Learning Objective 4: Control, Integration, and Testing
Students can apply the knowledge acquired in their control and machine learning courses. They will gain theoretical knowledge on modeling and developing intelligent control algorithms. They will be taught perception methods and state-of-the-art machine-learning techniques. They will gain experience testing their robots’ performance in both hard and software to enhance their design and suggest future improvements.
InhaltDuring this course, the students will be divided into teams, and each group will independently develop an articulated robotic arm to solve a real-world robotic challenge. The students will learn the key theoretical concepts required to model, manufacture, control, and test a robot and develop programming, machine learning, hardware, and engineering skills through hands-on workshops. The students will compete in a real-world robotic challenge that takes place at the end of the course.

This course is composed of tutorials, which will be available on the course website, where the lecturer will provide all the necessary theoretical input, focus talks where robotic experts will present a particular aspect of the manipulator in detail, and workshops where the students will have the possibility to hands-on learn how to implement the solutions required to solve their challenge. Finally, there will be time slots to autonomously work on the manufacturing and developing the team's robot. An online forum will be available to help the students throughout the course.

This course is divided into six parts:

Part 1: Challenge introduction
- Identify the functional requirements necessary for the final challenge
- Evaluate the existing manipulator designs to optimize them for the specific task

Part 2: Robot Design
- Develop a CAD model based on the high-level system design.
- Integrate motors, pneumatics components, and other required materials in the design

Part 3: Robot Fabrication
- Come up with a fabrication method and plan using the presented fabrication skills.
- Fabricate the robot and its actuators based on the CAD model.
- Evaluate, modify, and enhance the fabrication approach.

Part 4: Soft Robot Simulation
- Simulate the soft manipulator through a simulation framework
- Optimize the simulation parameters to reflect the experimental setup

Part 5: Control, Integration, and Testing
- Formulate the dynamic skills needed for real-life application.
- Develop traditional and learning-based control algorithms and test them in simulation.
- Integrate controller design into the fabricated robot.
- Build, test, fail, and repeat until the soft robot works as desired in simple tasks.
- Upgrade and validate the robot for performance in real-world conditions and verify requirements.

Part 6: Product development
- Understand the challenges associated with the manufacturing process to bring the robot from a prototype to the final product
- Optimize the robot for production
SkriptAll class materials, including slides, video tutorials, and supporting literature, can be found on the class webpage (https://rwr.ethz.ch) and Moodle, supported by discussion and Q&A forums. Focus talks, Q&A sessions, and workshops will happen on Mondays between 14:00 and 16:00.
Literatur1) Toshimitsu, Y., Forrai, B., Cangan, B. G., Steger, U., Knecht, M., Weirich, S., & Katzschmann, R. K. (2023, December). Getting the Ball Rolling: Learning a Dexterous Policy for a Biomimetic Tendon-Driven Hand with Rolling Contact Joints. In 2023 IEEE-RAS 22nd International Conference on Humanoid Robots (Humanoids) (pp. 1-7). IEEE.

2) Liconti, D., Toshimitsu, Y., & Katzschmann, R. (2024). Leveraging Pretrained Latent Representations for Few-Shot Imitation Learning on a Dexterous Robotic Hand. arXiv preprint arXiv:2404.16483.

3) Egli, J., Forrai, B., Buchner, T., Su, J., Chen, X., & Katzschmann, R. K. (2024). Sensorized Soft Skin for Dexterous Robotic Hands. arXiv preprint arXiv:2404.19448.

4) Yasa, O., Toshimitsu, Y., Michelis, M. Y., Jones, L. S., Filippi, M., Buchner, T., & Katzschmann, R. K. (2023). An overview of soft robotics. Annual Review of Control, Robotics, and Autonomous Systems, 6, 1-29.
Voraussetzungen / BesonderesStudents are expected to have attended introductory courses in dynamics, control systems, and robotics.

Registration for this course is limited due to the amount of resources needed to make this course happen. For this reason, it is required to apply through the following module: https://forms.gle/pnMHTCdZwgdawb519

The course's graded semester performance consists of the final team performance in the class challenge, a final team presentation and report, weekly Moodle quizzes, and attendance at the focus talks and workshops.

Focus talks, Q&A, and workshops are Mondays from 14:00 to 16:00.
Focus talks + Q&A will be from 14:00 to 15:00 in CLA E4.
Workshops will be from 15:00 to 16:00 in CLA E32.

The student teams can work every day at any time on their projects in the course room CLA E32.
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Entscheidungsfindunggeprüft
Problemlösunggeprüft
Projektmanagementgeprüft
Soziale KompetenzenKommunikationgeprüft
Kooperation und Teamarbeitgeprüft
Persönliche KompetenzenAnpassung und Flexibilitätgeprüft
Kreatives Denkengeprüft
Kritisches Denkengeprüft

Leistungskontrolle

Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Leistungskontrolle als Semesterkurs
ECTS Kreditpunkte4 KP
PrüfendeR. Katzschmann
Formbenotete Semesterleistung
PrüfungsspracheEnglisch
RepetitionRepetition nur nach erneuter Belegung der Lerneinheit möglich.

Lernmaterialien

Keine öffentlichen Lernmaterialien verfügbar.
Es werden nur die öffentlichen Lernmaterialien aufgeführt.

Gruppen

Keine Informationen zu Gruppen vorhanden.

Einschränkungen

PlätzeMaximal 40
VorrangDie Belegung der Lerneinheit ist nur durch die primäre Zielgruppe möglich
Primäre ZielgruppeRobotics, Systems and Control MSc (159000)
WartelisteBis 06.10.2024

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