Lecturer

Dr.-Ing. Patrick Wolf

Content

1. Introduction to Robotic Systems for Use in Highly Unstructured Environments (2h)

2. Hardware Aspects, Interfaces, Safety (1h)

3. Sensing and Measurement Principles for Environment Detection of Autonomous Off-Road Robots, Measurement Errors and Effects (3h)

• Laser
• Camera
• Radar

4. Building Robust and Secure Perception Systems for Autonomous Off-Road Driving (2h)

• Essential Properties and Requirements for Perception
• Perception Errors

5. Algorithms for Off-Road Driving (4h)

• Bottom-Up Perception (Quality Assessment, SLAM, Localization)
• Top-Down Perception (Maps, Ontologies)
• Dynamic Interaction Between Top-Down and Bottom-Up Perception
• Navigation

6. Architectures (1h)

• Machine Learning/End-to-End Learning
• Subsumption
• Behavior Trees
• Integrated Behavior-Based Control

7. Safety, Risk Management (1h)

Requirement

None

Intended learning achievements

Upon successful completion of the module, students will be able to,

• Understand and communicate problems and challenges for autonomous off-road driving,
• design and build reliable autonomous off-road systems,
• explain relevant environmental characteristics for perception algorithms,
• identify typical off-road error causes and situations, assess the potential consequences of perception errors, and develop strategies to avoid errors,
• apply algorithms for autonomous off-road driving,
• Understand the properties of perception architectures and analyze their influence on perception performance,
• Take measures to safeguard perception and autonomy software against errors.

Examination achievement

• Form of examination: written exam (Klausur) (60-90 Min.)
• Examination Frequency: each semester

Literature

• K. Berns and E. Puttkamer, "Autonomous Land Vehicles," Vieweg+Teubner Verlag | Springer Fachmedien Wiesbaden GmbH, Wiesbaden, 2009.
• S. Thrun, W. Burgard, and D. Fox, "Probabilistic Robotics," MIT Press, 2005.
• P. Wolf, "Cognitive Processing in Behavior-Based Perception of Autonomous Off-Road Vehicles," Verlag Dr. Hut, München, 2022.