Study/final thesis: Dynamic Obstacle Prediction for Autonomous Outdoor Navigation

Job description

Call for applications for the field of study, such as : Automation technology, electrical engineering, computer science, cybernetics, mechanical engineering, mathematics, mechatronics, control engineering, software design, software engineering, technical computer science, or similar. In the research group Navigation Mobile Robots, we develop autonomous, mobile robots for a variety of outdoor applications, such as agriculture, forestry and logistics. The focus is on the development of autonomous outdoor navigation solutions as well as the hardware of the robots. Be part of change Autonomous navigation in dynamic environments and higher speeds create challenges to typical mobile robots. To ensure safe and efficient path planning the robot must predict the future movement of dynamic obstacles and integrate that into its world understanding. This includes classifying the obstacle into typical dynamic obstacles like pedestrians, bikes, and vehicles based on LiDAR and/or camera data, predicting a realistic and/or conservative movement corridor and integrate this information efficiently into ROS2 costmaps. An important integration requirement lies in the compatibility with the ROS2 Nav2 Stack, which is widely used in the state of art of mobile robotics navigation What you contribute Valid enrollment at a German university or college Background in Computer Science, Software Engineering, Mechanical Engineering, Mechatronics or similar Programming knowledge and experience Experience with ROS is a plus Analytical mindset Enthusiasm for mobile robotics Fluent in English or German First, you will select a suitable state-of-the-art detection and classification approach based on LiDAR and/or camera data. But your focus lies on the prediction and map integration part of the pipeline. Therefore, you will investigate different types of predictions like intent prediction, reachability approaches or Bayesian filtering and develop a robust prediction algorithm. These dynamic predictions must then be integrated into a map representation to be included and used in the path planning of the robot. An important integration requirement lies in the compatibility with the ROS2 Nav2 Stack, which is widely used in the state of art of mobile robotics navigation. You will implement your solution inside our ROS2, C++ navigation stack and validate it both in simulation and in real-world scenarios with our mobile CURT robots. What we offer Cutting-edge technology in the field of outdoor mobile robotics Hands on with our robots in Stuttgart Take on responsibility and freedom to implement your own ideas Work with the best students in their discipline We value and promote the diversity of our employees' skills and therefore welcome all applications – regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Our tasks are diverse and adaptable – for applicants with disabilities, we work together to find solutions that best promote their abilities. With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future. Ready for a change? Then apply now and make a difference! Once we have received your online application, you will receive an automatic confirmation of receipt. We will then get back to you as soon as possible and let you know what happens next. Mrs. Lisa Schäfer Recruiting +49 711 970-3681 Fraunhofer Institute for Manufacturing Engineering and Automation IPA Requisition Number: 85217 Application Deadline: