MSc C. Manss

PhD student
Signal Processing Systems (SPS), Department of Microelectronics

Expertise: Swarm communication

Themes: XG - Next Generation Sensing and Communication


Christoph Manss is a part-time PhD student with Geert Leus, working at the German Aerospace Center Institute of Communications and Navigation.

Robotic exploration aims at reconstructing (or understanding) an unknown physical process autonomously and as efficiently as possible. In many situations, however, the exploration domain is either vast and a full coverage of it is time consuming for one agent. Another issue is the robustness of the exploration mission, where a single robot represents a single point of failure. This is the reason why this project focuses on multi-agent exploration systems, called swarms. The multi-agent systems coordinate their actions by cooperatively collecting measurements and jointly processing the acquired data, thus they split the computational complexity of the estimation, and risk of whole system failure, among individual agents.


  1. Consensus Based Distributed Sparse Bayesian Learning by Fast Marginal Likelihood Maximization
    C. Manss; D. Shutin; G. Leus;
    IEEE Signal Processing Letters,
    Volume 27, pp. 2119-2123, 2020. DOI: 10.1109/LSP.2020.3039481

  2. Coordination Methods for Entropy-Based Multi-Agent Exploration Under Sparsity Constraints
    C. Manss; D. Shutin; A. Viseras; G. Leus;
    In Proc. of IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),
    Le Gosier, Guadeloupe, pp. 490--494, December 2019. DOI: 10.1109/CAMSAP45676.2019.9022453

  3. Distributed splitting-over-features Sparse Bayesian Learning with Alternating Direction Method of Multipliers
    C. Manss; D. Shutin; G. Leus;
    In 2018 IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP),
    Calgary (Canada), IEEE, pp. 3654-3658, April 2018. ISSN: 2379-190X. DOI: 10.1109/ICASSP.2018.8462229

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Last updated: 10 Mar 2023