151-0636-00L  Soft and Biohybrid Robotics

SemesterSpring Semester 2022
LecturersR. Katzschmann
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
151-0636-00 GSoft and Biohybrid Robotics3 hrs
Mon09:15-12:00LEE E 101 »
R. Katzschmann

Catalogue data

AbstractSoft and biohybrid robots are emerging fields taking inspiration from Nature to create integrated robots that are inherently safer to interact with. You will be able to create the structures, actuators, sensors, models, controllers, and machine learning architectures exploiting the deformable nature of these robots. You will apply the learned principles to challenges of your research domain.
Learning objectiveLearning Objective 1: Convert any robotics challenge into a functional soft robotic physical prototype
Step 1: Formulate suitable functional requirements
Step 2: Select actuator material
Step 3: Design + fabricate suitable for the task
Step 4: Controller for basic functionality
Step 5: Learning Approach for complex robotic skills

Learning Objective 2: Formulate control and learning frameworks to highly articulated robots in real life scenarios
Step 1: Formulate the dynamic skills needed for the real life scenario
Step 2: Pick or combine suitable control and learning frameworks given the robot at hand
Step 3: Evaluate the control approach for a real life scenario
Step 4: Modify and enhance the control approach and repeat the evaluation

Learning Objective 3: Apply the principle of mechanical impedance and embodied intelligence to any research challenge within any domain
Step 1: Identify the moving aspects of the problem
Step 2: Choose and design the passive and actively-controlled degrees of freedom
Step 3: Pick the actuation material based on suitability to your challenge
Step 4: Design in detail multiple combinations of body and brain
Step 5: Simulate, build, test, fail, and repeat this often and quickly until the soft robot works for simple settings
Step 6: Upgrade and validate the robot for performances in real world conditions

Learning Objective 4: Rethink approaches to robotics by moving towards designs made of living materials
Step 1: Identify what problems could be easier to solve with a complex living material
Step 2: Scout for available works that have potentially tackled the problem with a living material
Step 3: Formulate a hypothesis for your new approach with a living material
Step 4: Design a minimum viable prototype (MVP) that properly highlights your new approach
ContentStudents will cover a range of latest research insights on materials, fabrication technologies, and modeling approaches to design, simulate, and build soft and biohybrid robots.

Part 1: Functional and intelligent materials for use in soft and biohybrid robotic applications
Part 2: Design and design morphologies of soft robotic actuators and sensors
Part 3: Fabrication techniques including 3D printing, casting, roll-to-roll, tissue engineering
Part 4: Biohybrid robotics including microrobots and macrorobots; tissue engineering
Part 5: Mechanical modeling including minimal parameter models, finite-element models and ML-based models
Part 6: Closed-loop controllers of soft robots that exploit the robot's impedance and dynamics for locomotion and manipulation tasks
Part 7: Machine Learning approaches to soft robotics, for design synthesis, modeling, and control

A mandatory semester-long project will teach the participants to implement the skills and knowledge learned during the class by building their own soft robotic prototype or simulation. There is a mandatory pass/fail assignment to be submitted within the first two weeks of class to get a spot in the project.
Lecture notesAll class materials including slides, recordings, class challenges infos, pre-reads, and tutorial summaries can be found on Moodle: https://moodle-app2.let.ethz.ch/course/view.php?id=14501
Literature1) Wang, Liyu, Surya G. Nurzaman, and Fumiya Iida. "Soft-material robotics." (2017).
2) Polygerinos, Panagiotis, et al. "Soft robotics: Review of fluid‐driven intrinsically soft devices; manufacturing, sensing, control, and applications in human‐robot interaction." Advanced Engineering Materials 19.12 (2017): 1700016.
3) Verl, Alexander, et al. Soft Robotics. Berlin, Germany:: Springer, 2015.
4) Cianchetti, Matteo, et al. "Biomedical applications of soft robotics." Nature Reviews Materials 3.6 (2018): 143-153.
5) Ricotti, Leonardo, et al. "Biohybrid actuators for robotics: A review of devices actuated by living cells." Science Robotics 2.12 (2017).
6) Sun, Lingyu, et al. "Biohybrid robotics with living cell actuation." Chemical Society Reviews 49.12 (2020): 4043-4069.
Prerequisites / Noticedynamics, controls, intro to robotics
Only for students at master or PhD level.
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Decision-makingfostered
Media and Digital Technologiesassessed
Problem-solvingassessed
Project Managementassessed
Social CompetenciesCommunicationassessed
Cooperation and Teamworkassessed
Customer Orientationfostered
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityfostered
Negotiationfostered
Personal CompetenciesAdaptability and Flexibilityassessed
Creative Thinkingassessed
Critical Thinkingassessed
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection fostered
Self-direction and Self-management assessed

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits4 credits
ExaminersR. Katzschmann
Typeend-of-semester examination
Language of examinationEnglish
RepetitionA repetition date will be offered in the first two weeks of the semester immediately consecutive.
Mode of examinationwritten 120 minutes
Additional information on mode of examinationThe assessment will be a written examination with 50% weight and a compulsory continuous assessment throughout the semester with 50% weight.

The written exam covers all contents of the course, including the lectures, exercises, and learning activities. The exam counts 50% towards the final grade.

The compulsory continuous assessment throughout the semester will consist of one short pass/fail essay due after the first two weeks and two graded assignments: (1) a written proposal that has 15% weight of the final grade, and (2) a project with final demonstration, presentation, and short paper (35%). Not handing in an assignment will result in the grade 1.0 for that assignment. The remaining 50% of the final grade will be based on the written exam.
Written aidsNone

Learning materials

 
Main linkSoft and Biohybrid Robotics Class
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

Places40 at the most
Waiting listuntil 06.03.2022

Offered in

ProgrammeSectionType
Biomedical Engineering MasterRecommended Elective CoursesWInformation
Biomedical Engineering MasterRecommended Elective CoursesWInformation
Biomedical Engineering MasterRecommended Elective CoursesWInformation
Mechanical Engineering MasterBioengineeringWInformation
Computational Science and Engineering MasterRoboticsWInformation
Robotics, Systems and Control MasterCore CoursesWInformation