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CAUSE-Cognitive Autonomous Subsurface Exploration

Working Group:WG Optimization and Optimal Control
Leadership: Prof. Dr. Christof Büskens ((0421) 218-63861, E-Mail: bueskens@math.uni-bremen.de )
Dr.-Ing. Mitja Echim ((0421) 218-63865, E-Mail: mitja.echim@uni-bremen.de)
Processor: Christian Meerpohl ((0421) 218-59891, E-Mail: cmeerpohl@math.uni-bremen.de)
Dr.-Ing. Stephanie Chen
Matthias Rick ((0421) 218-64356, E-Mail: mrick@math.uni-bremen.de)
Eva Dierkes ((0421) 218-64357, E-Mail: eva.dierkes@uni-bremen.de)
Project partner: AG Kognitive Neuroinformatik, Universität Bremen
DLR, Raumfahrtmanagement, Bonn
Time period: 01.04.2015 - 30.09.2018
Bild des Projekts CAUSE-Cognitive Autonomous Subsurface Exploration
The current state of research allows the assumption that the icy moons of our solar system could harbour life. Astrobiologically interesting candidates are, in addition to the polar caps of Mars, the Jupiter moon Europa and also Saturn's moon Enceladus, since they each have rich ice and water deposits. A future mission to Enceladus could be to send a fully autonomous space system including an autonomous melting probe navigating in the ice to take samples from an ice crevasse at the South Pole. An essential prerequisite for the space capability of the system is autonomous navigation and control. For this purpose, procedures are required which, on the basis of fused sensor data as well as with the help of previous and background knowledge, make decisions about the behavior of a complete system and execute the decisions made under criteria of optimality.
Testroboter für CAUSE
Within the framework of CAUSE, the Optimization and Optimal Control working group deals with the automatic identification of dynamic systems on the basis of merged measurement data, optimal trajectory planning, and the automatic design of model-based and adaptive control concepts. The concepts to be developed should not be limited to exploration projects, but should also be used in other application scenarios. Thus, the system is not only to be used on a melting probe, but the general transferability of the methods to be developed to different robot systems is a main focus of the investigations.
Bundesministerium für Wirtschaft und Energie


  1. C. Meerpohl, M. Rick, C. Büskens.
    Free-space Polygon Creation based on Occupancy Grid Maps for Trajectory Optimization Methods.
    10th IFAC Symposium on Intelligent Autonomous Vehicles (IAV 2019), 03.07.-05.07.2019.

    DOI: 10.1016/j.ifacol.2019.08.107

  2. C. Meerpohl, K. Flaßkamp, C. Büskens.
    Optimization Strategies for Real-Time Control of an Autonomous Melting Probe.
    2018 American Control Conference (ACC), 2018, Milwaukee, WI, USA.

    DOI: 10.23919/ACC.2018.8430877

  3. J. Clemens, C. Meerpohl, V. Schwarting, M. Rick, K. Schill, C. Büskens.
    Autonomous In-Ice Exploration of the Saturnian Moon Enceladus.
    69th International Astronautical Congress (IAC), 01.10.-05.10.2018, Bremen, Germany.