Cooperative Systems

Cooperative Control Systems

Vision

How will automation interact with humans in the future?

How to create synergies between humans and machines in the context of Industry 4.0?

The research group Cooperative Systems develops a framework for modeling and control of interactions between humans and machines. The individual strengths of human and machine are combined to achieve high performance systems, ready to meet future challenges of automatization. The fields of applications are e.g. Advanced Driver Assistance Systems, Robotics, Medical Technologies and Aerospace Engineering.

Cooperative Control Loop

Cooperative Control Loop

Modeling and Identification

The modeling of cooperative systems forms the basis of automation design for cooperative scenarios. In this context, uncertainties in perception and action need to be considered. Furthermore, semantics enable a strategic description of the interaction. Moreover, the identification of human behavior is essential in automation design.

Control Synthesis

Automation design in a cooperative scenario needs to be capable of a dynamic allocation of authority. Furthermore, it requires the ability to negotiate a common goal with the human. One approach to control cooperative systems is based on game theory and Model Predictive Control (MPC). In order to achieve real-time control, motion primitives are examined.

 

Experiments

Motion Tracking is used in various scenarios to measure human motion and validate identification methods.

An Advanced Driving Simulator with haptic feedback human machine interfaces was developed at the IRS. It is used to validate cooperative control methods in the context of advanced driver assistance systems.

A newly developed Ball-on-Plate experiment will be used to apply cooperative identification and control methods in a highly dynamical scenario.

Staff

Balint Varga

Head of Research Group

Research Interest:
Cooperative control of mobile machinery

   

Christian Braun

Research Associate

Research Interest:
Shared control of heterogenous robot swarms

Julian Schneider

Research Associate

Research Interest:
Multi level connection for the consistent design of cooperative human-machine systems

Philipp Karg

Research Associate

Research Interest:
Modeling and Identification in Cooperative Human-Machine Scenarios

Sean Kille

Research Associate

Research Interest:
 

Esther Bischoff

Research Associate

Research Interest:

   

Student Assistants

Hongdong Zhao

Software development and experimental implementation in the field of multi-robot manufacturing system

   

Recent job offers for student assistants can be found here.

Publications


2024
2023
2022
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2013