Introduction to human and robotic hand grasping: control and manipulation
|Language of instruction||English|
|Position within curricula||See TUMonline|
- 17.04.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
- 24.04.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
- 08.05.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
- 15.05.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
- 22.05.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
- 05.06.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
- 12.06.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
- 19.06.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
- 26.06.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
- 03.07.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
- 10.07.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
- 17.07.2023 16:30-18:00 Online: Videokonferenz / Zoom etc.
After successful completion of the course, students have learned how to write the kinematic and the dynamic equations that describe a grasp. Also, they are able to control the fingers of a robotic hand, or a team of robots, to grasp, manipulate, and move objects. In addition, students are capable of designing new controllers for robotic hands.
Inhalt (Content): • Chapter 1: Introduction & Basic concepts o Introduction to the course o Power and precision grasp o The friction cone o The Grasp Matrix o Manipulation is more than pick-and-place o Open-world manipulation o Model-based design and analysis o Organization of these notes • Chapter 2: robot hands o Dexterous hands o Simple grippers o Soft/underactuated hands o Other end effectors o Sensors o Putting it all together • Chapter 3: Grasp modeling o Object Kinematics o Hand Kinematics o Contact models o Quasi-static model of the grasp o Grasp properties • Chapter 4: Grasp control o A simple model(Direct) force control o Force Control o Hand Control o Control of the object o Limitations of the rigid-body assumption o Indeterminate grasps o Graspability
Passion for human and robotic hands grasping, as well as some familiarity with mathematical foundations regarding linear algebra, differential equations, and control theory. Additionally, participation in the following courses is recommended: • Robotics I • Motion Planning for manipulation • Control Systems I The interim exercises and final project will require solid knowledge of MATLAB and ROS.
Teaching and learning methods
● Lectures (for direct transfer of theoretical knowledge) ● Exercises (for experimenting with various learned approaches) ● Home assignments (for preparing for the final project)
The course grade will be determined by the midterm test (40%) and final project (60%). The midterm test consists of solving some theoretical problems in written tests of a duration of 90 min. Additionally, there will be a final project on lab experiments then presenting it with 30 min in slides. The final project evaluates whether students can transfer the methods they have learned during the course to real-life challenges. The student will have to choose between different experiments on the grasping topic then tackle the topic and the requirement of solving the proposed experimental problem. This can be done within two/four weeks' time then they will have to present their approach in 30 min presentation. Specifically, the grade will be divided as follows: • 40% midterm test • 60% Final project o 20% Presentations o 40% Solving the task
● Lecture slides ● Prattichizzo, D., & Trinkle, J. C. (2008). Grasping. In B. Siciliano & O. Khatib (Eds.), Springer Handbook of Robotics (pp. 671–700). Springer-Verlag Berlin Heidelberg. ● Bicchi A, Gabiccini M, Santello M. Modelling natural and artificial hands with synergies. Philos Trans R Soc Lond B Biol Sci 366: 3153–3161, 2011. doi:10.1098/rstb.2011.0152. ● Santello M, Baud-Bovy G, Jörntell H. Neural bases of hand synergies. Front Comput Neurosci 7: 23, 2013. doi:10.3389/fncom.2013.00023. ● Khatib, Oussama. "A unified approach for motion and force control of robot manipulators: The operational space formulation." IEEE Journal on Robotics and Automation 3.1 (1987)