Robotics Research Lab

Unimog U5023


The Unimog U5023 is a Mercedes Benz Special Trucks vehicle with a high level terrain mobility and a lot of possible applications. In the EFRE-supported lead project of the Commercial Vehicle Cluster Nutzfahrzeuge GmbH "Autonomer Fahrbetrieb von Nutzfahrzeugen im Off-Road-Bereich am Beispiel des Unimogs" the Unimog represents a demonstration vehicle of the technical development of robust and secure navigation solutions of commercial vehicles in rough and unstructured terrain.

The Unimog is characterized by extreme off-road capability and a lot of envelopes like differential lock, central tire inflation system, high number of gears, frame torsion, centreline torsion and portal axle. The vehicle is very attractive for applied research because it is possible to drive through rough terrain that were not included in the previous research programs.

Compared to on-road applications, this off-road navigation is currently an unsolved research problem with high technical obstacles. Nevertheless, the legal regulations for the autonomous commercial vehicles in unstructured terrain are at a lower level, which is why those concepts are easier to commercialize.

The main theme of the research in combination with the Unimog is the progress of robust perception systems, which are providing the detection and evaluation of tracks and passages and statistically and dynamic obstacles. On top of that there are biological motivated methods for localisation and general quality assessment of the sensor system.

Especially in unstructured environment a robot system is often influenced and disturbed by noisy and faulty sensor measurements. In consideration of dynamically changing of the sensor data quality on navigation, it is possible to react to alternating environmental influence. Therefore a path planning can avoid dangerous areas like holes, obstacles, sliding away or tilting.

As part of the project, the U5023 was technically converted with a new steering and braking system to navigate the robot completely autonomic. The sensor system monitors the whole vehicle environment. That's why certain trajectory in unstructured terrain can be calculated. Furthermore, a complex simulation of the Unimog was built, which includes all the envelopes and characteristics of the vehicle. On account of this, it is possible to simulate risky manoeuvres in heavy terrain before testing it in real life.




Sort by: Author, Year, Title

  • Advanced Scene Aware Navigation for the Heavy Duty Off-Road Vehicle Unimog.
    Patrick Wolf, Axel Vierling, Thorsten Ropertz and Karsten Berns
    Proceedings of the 9th International Conference on Advanced Concepts in Mechanical Engineering (ACME2020), (2020)
  • Autonome Off-Road Navigation von Nutzfahrzeugen. Erfahrungsbericht und Testergebnisse des CVC-Leitprojekts zum autonomen Fahrbetrieb von Nutzfahrzeugen im Off-Road-Bereich.
    Karsten Berns, Patrick Wolf and Steffen Hemer
    CVC News, Vol. 1, S. 4 - 10. (2020)
  • Autonomous Off-Road Navigation using Near-Feature-Based World Knowledge Incorporation on the Example of Forest Path Detection.
    Patrick Wolf, Axel Vierling, Thorsten Ropertz, Simon Velden, Carlos Guzman and Karsten Berns
    Preprint submitted to Robotics and Autonomous Systems, (2020)
  • Behavior-Based Control for Safe and Robust Navigation of an Unimog in Off-Road Environments.
    Patrick Wolf, Thorsten Ropertz, Karsten Berns, Martin Thul, Peter Wetzel and Achim Vogt
    Commercial Vehicle Technology 2018. Proceedings of the 5th Commercial Vehicle Technology Symposium – CVT 2018, S. 63 - 76. (2018)
  • Behavior-Based Low-Level Control for (semi-) Autonomous Vehicles in Rough Terrain.
    Thorsten Ropertz, Patrick Wolf and Karsten Berns
    Proceedings of ISR 2018, S. 386 - 393. (2018)
  • Local Behavior-Based Navigation in Rough Off-Road Scenarios based on Vehicle Kinematics.
    Patrick Wolf, Thorsten Ropertz, Moritz Oswald and Karsten Berns
    2018 IEEE International Conference on Robotics and Automation (ICRA), S. 719 - 724. (2018)
  • Modelling and Simulation of Behaviour-Based Differential and Slippage Control for Unimog.
    Ganesh Sundaram
  • Multi Feature Maps for Autonomous Off-Road Navigation in Rough Environments.
    Simon Velden
  • Ontologies for Situation-Aware, Autonomous Navigation in Challenging Off-Road Environments.
    Philipp Feldmann
  • Autonomie in unwegsamem Gelände. Aktuelle Zwischenergebnisse des CVC-Leitprojekts zum autonomen Fahrbetrieb von Nutzfahrzeugen im Off-Road Bereich.
    Karsten Berns and Patrick Wolf
    CVC News, Vol. 2, S. 8 - 11. (2017)
  • Behavior-Based Gear Control for Rough Off-Road Environments.
    Simon Velden
  • Behavior-Based Navigation for Stuck Vehicles in Rough Off-Road Environments.
    Matthias Kremer
  • Geländerekonstruktion basierend auf 3D-Punktwolken.
    Hannes Endres
  • Navigation in Unstructured Environments for the Cross Country Vehicle "Unimog".
    Moritz Oswald


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