PhD Thesis - Safety and Robustness in Mobile Robot Motion Planning
- Robert-Bosch-Campus 1, 71272 Renningen, Germany
- Legal Entity: Robert Bosch GmbH
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- Learning- and optimization-based control. Mobile robots are deployed in constrained spaces with other vehicles and humans around. The common approach to achieving safety is to dedicate a separated safety control unit to intercept all control commands and alter these if deemed necessary; often using safety laser scanners on the robot. This approach is straightforward and practical for low-speed driving scenarios in sparsely occupied spaces where the monitored areas can be kept small through short braking distances. To be able move faster safely in dynamic environments it is necessary to increase reliance on environment understanding, in form of both semantics and interaction dynamics. This PhD research is about exploring ways to achieve this while keeping the decision-making scheme real-time implementable and to ultimately obtain a tighter integration between the motion planning and safety control.
- Develop strategies to achieve provably robustly safe mobile robotic systems, going beyond the performance achievable by using current industrial safety concepts.
- Design motion planning problem formulations that embed and exploit (uncertain) interactive models of the environment and autonomous dynamic agents in the surroundings.
- Develop efficient software and tools to achieve sufficiently fast computations of the proposed solutions to enable experimental validations.
- Be part of a research team and interact with our academic community. New ideas will be published at top-tier conferences in control and robotics.
- You have no industry project duties and your main aim is to perform academic research with excellence. Your algorithms will also have the opportunity to be tested on real systems, in various Bosch robotic products.
- Education: excellent master degree in system & control, applied mathematics, robotics, or a comparable subject
- Experience and Knowledge: proven programming skills (e.g., C++, Python), strong background in linear algebra, probability and statistics, and ideally in robust control, experience with motion planning and control topics using numerical optimization and search algorithms, proficiency in Modern C++, experience with run-time performance of optimization and/or planning algorithms
- Language: fluent in English
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You want to work remotly or part-time - we offer great opportunities for mobile working as well as different part-time models. Feel free to contact us.
Please submit all relevant documents (incl. curriculum vitae, motivation letter, transcript of records, certificates).
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Kevin Heiner (Human Resources)
+49 711 811 12223
Need further information about the job?
Niels van Duijkeren (Functional Department)
+49 711 811 59140