Master Thesis Execution-Aware Multi-Robot Planning

In modern factories teams of mobile robots are used to transport materials efficiently and autonomously. To operate at scale these robots require coordinated planning of their movements while avoiding conflicts and delays.

• During your thesis you will investigate how such multi-robot plans can remain efficient when execution deviates from the original schedule (e.g. due to delays or blocked paths). Instead of recomputing plans from scratch the goal is to adapt them locally during execution.
• You will develop methods to represent robot actions and their interactions and design algorithms that incrementally repair ongoing plans while ensuring safety and consistency.
• Your approaches will be implemented in a simulation framework and evaluated on representative industrial scenarios focusing on robustness efficiency and solution quality.
• Finally you will work closely with a research team and contribute to bridging algorithmic planning methods with real-world robotic systems.

Qualifications :

• Education: Master studies in the field of Computer Science Robotics AI or comparable with good grades
• Experience and Knowledge: strong programming skills in C and Python; basic familiarity with Git and software development workflows; good understanding of mobile robotics path/motion planning and multi-agent systems; familiarity with algorithm design and performance evaluation; experience with simulation tools or robotics frameworks is a plus
• Personality and Working Practice: you excel at systematically analyzing complex problems and developing innovative solutions through a research-oriented approach
• Work Routine: your on-site presence is required
• Enthusiasm: interest in robotics intelligent systems and real-world industrial applications; motivation to contribute to research with both academic and applied relevance
• Languages: fluent in English

Additional Information :

Start: according to prior agreement
Duration: 6 months

Requirement for this thesis is the enrollment at university. Please attach your CV transcript of records examination regulations and if indicated a valid work and residence permit.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.

Need further information about the job
Chuanlong Zang (Functional Department)
 23557

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Remote Work :

No

Employment Type :

Full-time