We develop smart sensors and control algorithms for assistive robots using brain-inspired neuromorphic technology: e.g. event-based vision systems, taktile sensors and robotic controllers. This technology will enable fast real-time perception, cognition, motion planning, and control, required for safe and effective robotic manipulation in human vicinity.

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Our collaboration partners in the context of robotics: Neuromorphic Computing Lab at Intel  I  EURA Robotics  I  ECSPECD  I  Prophesee  I  INIVation  I  SynSense

Contact: yulia.sandamirskaya@zhaw.ch

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Our collaborator partners in the context of robotics: Healthcare organisations (i.e. hospitals, care homes)  I  Associations  I  Interest groups

Contact: nicole.gerber@zhaw.ch

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Our collaboration partners in the context of robotics: Digital health center bülach  I  Healthcare organisations  I  Associations  I  Public authorities

Contact: gekont@zhaw.ch

Within the research area Autonomous Learning Systems at the ZHAW Centre for AI (CAI), the design and development of intelligent systems is investigated that have a feedback loop between perception (processing of incoming sensor data) and action (execution of actions that have an influence on the environment to be perceived). An important methodology for this is deep learning, in particular reinforcement learning, which enables agents to learn by trial and error. This reward-based learning will open up completely new areas of application that go beyond the usual learning by means of hand-selected input-output pairs – in almost every sector, for example in industry and in the field of neurotechnologies. Linking such systems with hardware that has suitable sensors and actuators creates additional training potential for the algorithms of autonomous systems through physical interaction (embodied AI or physical AI, for example through machine learning on and for robots). 

Physical AI and the research field of autonomous learning systems play a role in the work of the following research groups at the CAI: Industrial AI by Prof Alisa Rupenyan, Machine Perception and Cognition by Prof Thilo Stadelmann, and Cybernetic Learning Systems (currently vacant). Here, research and development is carried out on issues raised by practice partners and in collaboration with the drone and robotics community in the Zurich area: From the safe and efficient testing of drones and autonomous vehicles in Dübendorf to the creation of methods for the safe and robust control of industrial plants, frameworks and algorithms for human-machine collaboration for the operation of critical infrastructure, object recognition for walking machines or large language models on humanoid robots.

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Our collaboration partners in the context of robotics: Flatland  I  LINA  I  Matternet  I  Mindfire  I  NCCR Automation  I  SBB  I  Skyguide  I  Stiftung Rieter  I  Zurich UAS Racing

Contact: Thilo Stadelmann, Alisa Rupenyan-Vasileva

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Our collaboration partners: Hocoma AG  I  Myoswiss AG  I  TA-Swiss Stiftung für Technologiefolgen-Abschätzung  I  VAMED Management und Service Schweiz AG

Contact: Institute of Occupational Therapy  I  Institute of Nursing  I  Institute of Physiotherapy

We solve complex problems in applied research projects as an interdisciplinary team at the Institute of Applied Mathematics and Physics (IAMP), collaborating with partners from industry, science, and politics. Our expertise spans research, consulting, services, and education and training, with a particular focus on modeling, quantitative simulation, design, and analysis of complex physical and socio-technical systems. Robotics applications are explored from diverse perspectives across our various labs.

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Applied Complex Systems Science

We explore complex socio-technical systems using a variety of mathematical and physical tools with a focus on statistical mechanics, artificial intelligence, bio-inspired and evolutionary engineering. In robotics, we develop innovative solutions such as soft, elastic robots that are lightweight, robust and safer for human interaction, particularly in medical and rehabilitation contexts. By combining physical modelling with AI, we develop algorithms to improve the performance and adaptability of robots.

Safety-Critical Systems Research Lab

We specialize in the development, implementation and verification of complex socio-technical systems for safety-critical applications, with robotics and artificial intelligence at the core of our expertise. We combine advanced technologies with thorough verification processes to ensure that our innovative systems meet the required technical specifications, guarantee user safety and comply with all relevant regulatory requirements for market approval.

Scientific Computing and Algorithmics Lab 

We develop customized solutions for complex and computationally intensive problems ranging from nonlinear optimal control, trajectory planning, multi sensor fusion, simulation and optimization of sensors to more general machine learning applications.

Besides refined mathematical/physical modeling we put special emphasis on developing robust, efficient and ready to use implementations of our solutions.

Partners: Zurich Soft Robotics GmbH  I  Varian Medical Systems Imaging Laboratory GmbH  I  Haute école de travail social et de la santé  I  dynamic devices AG / ddrobotec  I  Zurich UAS Racing

Contact: info@iamp.ch

As a leading national institution for applied science and development in robotics & mechatronics, the Institute of Mechatronic Systems (IMS) specialises in innovative projects at the interface between mechanics, electronics and information technology (IT). The knowhow of more than 60 staff with backgrounds in various related fields, as well as a modern research infrastructure, allows us to be your flexible and efficient partner for the successful completion of your R&D projects.

In the robotics context we have the following labs:

• Robotics & Automation
• Biomedical Engineering
• System Engineering
• Industry 4.0 / 5.0
• MINDLab: AI in human-robot cooperation

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