KIT Career ServiceAbschlussarbeiten am KIT

Optimizing Lifelong Multi-Agent Pathfinding Using Reinforcement and Imitation Learning

Forschungsthema/Bereich
Mobile Agents and Robotic Systems
Typ der Abschlussarbeit
Master
Startzeitpunkt
01.11.2025
Bewerbungsschluss
30.04.2026
Dauer der Arbeit
6 Monate

Beschreibung

Field:
Mobile robotics is one of the fastest-growing and most dynam-ic areas in intralogistics. As fleet sizes rapidly increase, the challenge shifts from single-robot navigation to large-scale, cooperative fleet coordination. Efficient and adaptive management of these fleets is essential to ensure high system throughput, reliability, and productivi-ty. At the IFL, we are at the forefront of this development, actively contributing to the industry standard VDA 5050, which defines com-munication between mobile robots and fleet management systems.

Problem Statement:
Traditional Lifelong Multi-Agent Pathfinding (LMAPF) algorithms rely on fixed heuristics and lack adaptability to dynamic, real-world environments. In practice, robot fleets must op-erate continuously under uncertainty, delays, and changing task de-mands—conditions where static methods quickly reach their limits. This thesis explores learning-based approaches such as Reinforce-ment Learning, Imitation Learning, or hybrid methods to enable scal-able and adaptive coordination. The goal is to develop policies that learn cooperative behaviors, reduce congestion and deadlocks, and improve overall system throughput and robustness.

Voraussetzung

Voraussetzungen an Studierende
  • Experience with Python or a similar programming language.
  • Familiarity with machine learning frameworks such as PyTorch or TensorFlow is an advantage.
  • Knowledge of graph theory and pathfinding algorithms is a plus.
  • Problem-solving mindset and an independent working style.

Studiengangsbereiche
  • Ingenieurwissenschaften
    Informatik
    Maschinenbau
    Mechatronik & Informationstechnik
    Mechanical Engineering
  • Wirtschafts- und Rechtswissenschaften
    Wirtschaftsinformatik
    Wirtschaftsingenieurwesen


Betreuung

Titel, Vorname, Name
M. Sc. Marvin Rüdt
Organisationseinheit
Institute for Material Handling and Logistics (IFL)
E-Mail Adresse
marvin.ruedt@kit.edu
Link zur eigenen Homepage/Personenseite
Website

Bewerbung per E-Mail

Bewerbungsunterlagen
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  • Lebenslauf
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E-Mail Adresse für die Bewerbung
Senden Sie die oben genannten Bewerbungsunterlagen bitte per Mail an marvin.ruedt@kit.edu


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