Prof. Bradley J. Nelson

Multi-Scale Robotics Lab

Forschung Das Multi-Scale Robotics Lab verfolgt ein dynamisches Forschungsprogramm, welches einen starken Robotik-Fokus auf mehrere aufkommende Gebiete im Bereich der Wissenschaft und Technologie legt. Einer der Hauptkomponenten der Forschungstätigkeiten des MSRL ist die Erschaffung von Intelligenten Maschinen, welche im Mikro- und Nanobereich operieren. MSRL entwickelt die Instrumente und Prozesse, welche für die Fabrikation und die Montage von Robotern im Mikrobereich und für mikroskopisch kleine Roboter-Komponenten im Nanobereich notwendig sind. Viele dieser Systeme werden zur Erforschung in biologischen Bereichen eingesetzt, zum Beispiel zur robotergestützten Erforschung von molekularen Strukturen, Zell-Systemen und komplexen Verhaltensweisen von Organismen. Dies ist ein aufkommendes Gebiet, welches unser Institut als BioMicroRobotik bezeichnet.



Prof. Roland Y. Siegwart

Autonomous Systems Lab

Autonomous Systems Lab In the Autonomous System Lab our research interest is in Mechatronics, namely in the design and control of systems operating in uncertain and highly dynamical environments. Our major goal is to find new ways to deal with uncertainties and to enable the design of highly interactive and adaptive systems. This is driven by the vision that machines are getting closer and closer to human beings, as it can be experienced for autonomous robots, and in some cases they will even merge with them.



Prof. Robert Riener

Sensory-Motor Systems Lab

Forschung We investigate the sensory-motor actions in and interactions between humans and machines. Human sensors (receptors) record the physical state of the human body and the surrounding environment. Sensory information is perceived by the human central nervous system. Human cognition is required to interpret the perceived information and generate a motor reaction. Similarly, in machines technical sensors detect the state of the machine and its environment. Sensor data is processed in order to drive actuators and displays. Human and machine can interact with each other via their sensory and motor channels.
The research of the Sensory-Motor Systems Lab focuses on the study of human sensory-motor control, the design of novel mechatronic machines, and the investigation and optimisation of human-machine interaction. Main application area is the field of rehabilitation. Further applications are within sports, fitness and medical education.



Prof. Roger Gassert

Rehabilitation Engineering Lab

Rehabilitation Engineering Lab The emerging field of neuroscience robotics promises novel insights into the neural mechanisms of human sensorimotor control and their reorganization with age or after focal brain injury, and can thus be beneficial to the diagnosis, assessment and retraining of motor function. In our Lab we use a combined approach of robotics, psychophysics and cognitive neuroscience to develop and clinically evaluate diagnostic, therapeutic and assistive tools in order to promote recovery, independence and social integration of the physically disabled. We are especially interested in hand function, and how haptic feedback can benefit motor learning, rehabilitation therapy, and human-machine interaction.



Prof. Fumiya Iida

Bio-Inspired Robotics Laboratory

Bio-Inspired Robotics Laboratory The research interests of the Bio-Inspired Robotics Lab lie at the intersection of robotics and biology. Through abstraction of the design principles of biological systems, we develop core competences which are the design and control of dynamic mechatronics systems, bionic sensor technologies, and computational optimization techniques. Our main goals are to contribute to a deeper understanding of adaptivity and autonomy of animals through the investigation of dynamic robots, and to engineer novel robotic applications which are more adaptive, resilient, and energy efficient.



Prof. Jonas Buchli

Agile & Dexterous Robotics Lab

Agile & Dexterous Robotics Lab ADRL's research focuses on achieving robust, dynamic, agile and autonomous robotic control in unstructured environments by means of model based control, force and impedance control, and applied machine learning, with applications to mobile manipulation, grasping, legged locomotion, prosthetics, field robotics, and bio-inspired robotics.