392253 ISY Project: Robotic In-hand Manipulation of Objects in Simulated Environments (Pj) (SoSe 2021)
Contents, comment
-
In the project, you will work with robot models in simulated environments, e.g. [1, 2, 3, 4], and build a controller for manipulation of objects using general-purpose deep reinforcement learning algorithms [5], modern neural network architectures and classic approaches. You will experiment with adding touch sensors [6] to the hand and explore generalization of learned policies over different objects with and without tactile information.
[1] OpenAI Robotics
http://gym.openai.com/envs/#robotics
https://drive.google.com/open?id=1J2H92AstGpcFYqjmVymMSRKI5xISdB1b[2] Robot open-Ended Autonomous Learning https://www.aicrowd.com/challenges/neurips-2019-robot-open-ended-autonomous-learning
[3] Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning
https://youtu.be/-L4tCIGXKBE[4] MoveIt
https://moveit.ros.org
https://youtu.be/0og1SaZYtRc[5] OpenAI Deep Reinforcement Learning Baselines
https://github.com/openai/baselines[6] Touch sensors
https://rebrand.ly/TouchSensors
Requirements for participation, required level
-
Introduction to Neural Networks or Advanced Neural Networks courses.
Python or C++ ( > 1 year).In case this would not find enough interest for a team project, this project proposal would be also offered (in reduced/modified form)
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period |
|---|
Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-M-Inf-GP Grundlagenprojekt Intelligente Systeme | Gruppenprojekt | Ungraded examination
|
Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
- Registered number: 0
- This is the number of students having stored the course in their timetable. In brackets, you see the number of users registered via guest accounts.
- Address:
- SS2021_392253@ekvv.uni-bielefeld.de
- This address can be used by teaching staff, their secretary's offices as well as the individuals in charge of course data maintenance to send emails to the course participants. IMPORTANT: All sent emails must be activated. Wait for the activation email and follow the instructions given there.
- If the reference number is used for several courses in the course of the semester, use the following alternative address to reach the participants of exactly this: VST_262902902@ekvv.uni-bielefeld.de
- Coverage:
- No students to be reached via email
- Notes:
- Additional notes on the electronic mailing lists
- Last update basic details/teaching staff:
- Thursday, February 4, 2021
- Last update times:
- Thursday, February 4, 2021
- Last update rooms:
- Thursday, February 4, 2021
- Type(s) / SWS (hours per week per semester)
- Pj / 4
- Language
- This lecture is taught in english
- Department
- Faculty of Technology
- Questions or corrections?
- Questions or correction requests for this course?
- Planning support
- Clashing dates for this course
- Links to this course
- If you want to set links to this course page, please use one of the following links. Do not use the link shown in your browser!
- The following link includes the course ID and is always unique:
- https://ekvv.uni-bielefeld.de/kvv_publ/publ/vd?id=262902902
- Send page to mobile
-
Click to open QR code
Scan QR code:
- ID
- 262902902