Master Thesis: Design and Implementation of a Model-Predictive Local Planner for Mobile Outdoor Robots

vor 2 Wochen


Stuttgart, Baden-Württemberg, Deutschland Fraunhofer-Gesellschaft Vollzeit
Job Overview

As a Master Thesis student at Fraunhofer-Gesellschaft, you will have the opportunity to work on a cutting-edge project that focuses on the design and implementation of a model-predictive local planner for mobile outdoor robots. Your task will be to develop a motion planner that can find optimal collision-free trajectories on uneven outdoor terrain and send the appropriate velocity commands to the robot base.

Key Responsibilities
  • Design and implement a model-predictive local planner for mobile outdoor robots
  • Develop a motion planner that can find optimal collision-free trajectories on uneven outdoor terrain
  • Implement a system that can send velocity commands to the robot base
  • Work with ROS in C++ and have access to a simulation environment and our outdoor robot CURTmini for regular testing and evaluation
Requirements
  • Background in Computer Science, Software Engineering, Electrical Engineering, Mechatronics, or similar
  • Profound knowledge of C++
  • Experience with ROS
  • Experience in Model Predictive Control
  • Enthusiasm for mobile robotics
  • Fluent in English or German
What We Offer
  • Cutting-edge technology in the field of outdoor mobile robotics
  • Hands-on experience with our robots on our own test fields in Stuttgart
  • Take on responsibility and freedom to implement your own ideas
  • Work with the best students in their discipline
  • Familiar atmosphere including Cake Friday
Company Overview

Fraunhofer-Gesellschaft is a leading organization in the field of research and development, with a focus on key technologies and the application of research results in industry and economy. We value diversity and welcome applications from all qualified candidates, regardless of age, gender, nationality, ethnic and social origin, religion, worldview, disability, or sexual orientation and identity.


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