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Machine learning for robotics & control

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ROCON & Lucian Buşoniu

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2021 Research Conference of the Technical University of Cluj-Napoca

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October 21st, 2021

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Structure

  1. ROCON introduction: overview, topics, key people
  2. Project spotlight: SeaClear
  3. Algorithm spotlight: reinforcement learning for mapping

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Slides for parts 2 and 3 available on request, please email lucian@busoniu.net

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@TUCluj: Robotics & Nonlinear Control

  • Established 2014 (evolution of the earlier Robotics Research Group)
  • Topics: robotics, AI & ML, computer vision, fundamental perception & control
  • 6 staff, 8 PhD students, 10+ MSc & BSc on paid positions
  • More than 1.5 MEUR funding attracted
  • Industry connections: Accenture, Analog Devices, Bosch, Braintronix, etc.
  • http://rocon.utcluj.ro :

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Machine learning for robotics

Assistive mobile manipulator (IROS 2016)

UAV monitor for at-risk persons (CESCIT 2018)

Topics: assistive robotics, reinforcement learning, AI planning�

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Machine learning for robotics

Communicating drone learns the wireless rate map (CEP 2020)

Topics: assistive robotics, AI planning, reinforcement learning�

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Industry 4.0 (3rd talk)

Topics: cobot, MES integration, augmented reality,�human-robot interaction�

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2D/3D computer vision (3rd talk)

Tools: 2D/3D data fusion, deep learning,�recognition�

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Rehabilitation robotics (2nd talk)

Topics: biomechanical modeling, 3D sensing, rehabilitation assistance

Assistive robot predicting intention-of-motion

Autonomad Mobility assistive wheelchair

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Control algorithms

Rotary inverted pendulum (Automatica 2018)

Topics: reinforcement learning, fuzzy control, optimal and sliding-mode control�Systems: nonlinear dynamics, hybrid dynamics, multiagent systems

Ball-bot balancing (IFAC World Congress 2020)

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TS fuzzy control and estimation

Tools: fuzzy systems, stability analysis, observer and controller design�Topics: nonlinear control, state estimation, fault detection�Applications: parameter identification, ICE estimation, fault detection

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Fuzzy control for a cart-pole system (TFS 2020)

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Key people

Lucian Busoniu, busoniu.net:�AI & machine learning, nonlinear optimal control

Levente Tamas, rocon.utcluj.ro/levente/: Industry 4.0, computer vision, robotics

Zsofia Lendek, lendek.net:�fuzzy control and estimation, fault detection

Tassos Natsakis, natsakis.com:�biomechanics, rehabilitation robotics

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Alexandru Codrean, rocon.utcluj.ro/node/199: nonlinear and robot control

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Thank you!

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Machine learning for robotics & control

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Contact:

lucian@busoniu.net

http://rocon.utcluj.ro

Next up: Tassos on biomedical robotics apps,�Levente on industrial robotics research

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