(Master’s Thesis / Internship, w/m/x) Terrain-Aware Motion Planning for Wheel Wear Reduction in Planetary Rovers
Understanding wheel wear is crucial for long-duration planetary missions, where abrasive terrain and sharp steering maneuvers can significantly reduce rover lifetime. NASA’s surface mission experience (see [Lessons Learned – Mobility System](https://llis.nasa.gov/lesson/22401), point 5) highlights how in-place steering and high-curvature motions accelerate wheel degradation. Building on these insights, the Institute of Robotics and Mechatronics aims to develop motion-planning algorithms that reduce harmful steering actions on our autonomous LRU rover.
The goal of this position is to investigate how curvature-based cost functions, as proxies for steering-induced wheel wear, can be effectively integrated into the motion planning stack of a planetary rover. This work starts from an existing sampling-based planning framework and analyzes its limitations in terms of computational performance, robustness, and solution quality. Based on this, improved formulations and planning strategies will be developed, with particular attention to efficient planning under realistic runtime constraints.
Your tasks will include:
- analyzing and benchmarking an existing sampling-based motion planning framework
- studying planning strategies with respect to terrain-awareness and curvature-based objectives with a focus on integrating [learning-based](https://byangw.github.io/projects/icra2021/) methods into the existing framework
- investigating how terrain-awareness and curvature-based objectives can be integrated at different stages of the planning stack
- improving computational performance through algorithmic and implementation-level optimizations
The successful candidate will have:
- the chance to work on a cutting-edge mobile robot for planetary exploration
- an opportunity to learn from experienced roboticists in a professional environment
- the potential to grow and apply your skills and knowledge
What we expect from you:
- currently enrolled in a Master's degree in robotics, computer science, or a related field
- knowledge of fundamental concepts in autonomous systems/ robotics (planning, control, state-estimation, mapping)
- proficiency in Python and/or C++, basics of linux and git
- professional working proficiency in English and/or German
- experience in working with mobile robotics/ROS is a plus
What we offer:
DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.
Further information:
- When applying for a position, please indicate your current education and GPA, experience in relevant projects and/or classes, and the time frame you would be interested in.
- internships need to count towards your studies progress (i.e. you receive credits for it)
- earliest starting date: roughly 3 months after application
- Duration of contract: 6+ months
Kontakt
Office (AUF)