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Bosch Center for Artificial Intelligence

Our Research Field

Dynamic Multi-Agent Planning

What Motivates Us

Coordinating large groups of autonomous mobile systems is increasingly important as the number of deployed systems grows. More than mere coordination, we are interested into optimizing goal achievement of multi-agent systems in a safe manner while enabling operators to specify goals and requirements directly and unambiguously. Complexity increases when a complete fleet of autonomous systems is deployed with goals specified independent of the robot executing the underlying tasks. Ensuring coordination in an inherently uncertain and stochastic environment is even more demanding.

Our Approach

Multi-robot planning with complex temporal logic constraints enables the design of fleet management systems that are scalable and respect domain-specific requirements. Furthermore, transferring recent advances in reinforcement learning to this domain allows to synthesize control policies that work robustly even under uncertainty.

Application

Autonomous multi-agent systems are becoming increasingly relevant for industrial environments, in particular for intralogistics. Leveraging artificial intelligence, our research team builds the foundation for dynamic planning and scheduling of robotic fleets in an industrial environment while incorporating complex requirements and constraints.

Read more

  • Bosch BCAI - Publication - ICRA

    Schillinger et al.

    "Multi-Objective Search for Optimal Multi-Robot Planning with Finite LTL Specifications..."
    • Authors: Philipp Schillinger, Mathias Bürger, and Dimos V. Dimarogonas
    • Published in ICRA in 2017
  • Bosch BCAI - Publication - DARS

    Schillinger et al.

    "Decomposition of Finite LTL Specifications for Efficient Multi-Agent Planning"
    • Authors: Philipp Schillinger, Mathias Bürger, and Dimos V. Dimarogonas
    • Published in DARS in 2016

Research Application

Bosch BCAI - Correct-by-Construction Action Planning for Autonomous Systems

Correct-by-Construction Action Planning for Autonomous Systems

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