Robotics-2: Dynamics and movement control

Yulia Sandamirskaya

In this session, we will discuss the role of neuromorphic computing in movement control of articulated robotic systems, such as robot arms. The discussion will start with 3-4 short presentations (statements) from INRC researchers and quests who work in domain of arm and full-body control. These presentations will include work in arm control that has been done on Loihi so far, an overview of mechanisms behind human arm control, and a example of bio-inspired control or a bio-inspired robotic body. Thus, our discussion will unfold between the neuromorphic versions of conventional control (PID, MPC) and bio-inspired control strategies, for which a neuromorphic implementation is yet to be established. Along the discussion, we will try to find answers to the following questions:

• Which subtasks or levels in motor control are particularly attractive for neuromorphic solutions and which are not? What would be the criteria for success of a solution? Which bottleneck could neuromorphic realization solve: scalability? latency? throughput?

• What are the challenges to make Neuromorphic approaches enter the main stream in robot control: Algorithms? Interfaces? Performance? Ecosystem?

Other questions will be collected prior to the workshop.

• Prof. Elishai Ezra Tsur (Neuro-Biomorphic Engineering Lab, Open Univ. Israel)

  • http://nbel-lab.com/

• Florian Walter (Robotics, Artificial Intelligence and Real-time Systems, TUM)

  • https://www.in.tum.de/en/i06/home/

• Prof. Gregor Schöner (Institute for Neuronal Computation, Ruhr-Univ. Bochum)

  • https://www.ini.rub.de/

• Dr. Philipp Stratmann, Prof. Alin Abu-Schäffer (Robotics and Mechatronics, German Aerospace Center)

  • https://www.dlr.de/rm/en/desktopdefault.aspx/tabid-8017/

• Alona Kharchenko, Rafael Hostettler (Roboy, Munich)

  • https://roboy.org/

Link to a teaser for the guided discussion material coming soon. Please, add your questions and topic that you would like to discuss in the comments below.

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