World's Best Scientists 2026 revealed!
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Computer Science
Germany
2025

D-Index & Metrics

Computer Science

D-Index
73
Citations
23596
World Ranking
1575
National Ranking
61

Research.com Recognitions

  • 2025 - Research.com Computer Science in Germany Leader Award
  • 2023 - Research.com Computer Science in Germany Leader Award
  • 2022 - Research.com Computer Science in Germany Leader Award

Overview

Michael Beetz is affiliated with the University of Bremen in Germany and has contributed substantially to fields within computer science and engineering. Their research spans a variety of specialized areas including artificial intelligence, control and systems engineering, computer vision and pattern recognition, industrial and manufacturing engineering, and social psychology.

Their work focuses on several main topics related to robotics and AI, including:

  • Robot Manipulation and Learning
  • AI-based Problem Solving and Planning
  • Reinforcement Learning in Robotics
  • Robotic Path Planning Algorithms
  • Logic, Reasoning, and Knowledge
  • Modular Robots and Swarm Intelligence
  • Robotics and Sensor-Based Localization

Their publication record includes papers in a range of journals and conference proceedings, with multiple contributions to both theoretical and applied aspects of robotics and AI. Frequent publication venues include:

  • arXiv (Cornell University)
  • Media (https://www.suub.uni-bremen.de/)
  • Robotics and Autonomous Systems
  • IEEE Robotics and Automation Letters
  • 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Notable recent papers by Michael Beetz include:

  • "SkillMaN - A skill-based robotic manipulation framework based on perception and reasoning" (2020, Robotics and Autonomous Systems)
  • "Foundations of the Socio-Physical Model of Activities (SOMA) for Autonomous Robotic Agents1" (2021, Frontiers in artificial intelligence and applications)
  • "Kineverse: A Symbolic Articulation Model Framework for Model-Agnostic Mobile Manipulation" (2022, IEEE Robotics and Automation Letters)
  • "The CRAM Cognitive Architecture for Robot Manipulation in Everyday Activities" (2023, arXiv (Cornell University))
  • "Heuristic-free Optimization of Force-Controlled Robot Search Strategies in Stochastic Environments" (2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))

Michael Beetz has also co-authored extensively with a set of frequent collaborators. These include:

  • Daniel Beßler
  • Mihai Pomarlan
  • Benjamin Alt
  • Darko Katić
  • Rainer Jäkel

In addition to journal and conference papers, Michael Beetz has published a book with Springer Nature titled Robotics for Intralogistics in Supermarkets and Retail Stores (2022).

Best Publications

  • Fast Point Feature Histograms (FPFH) for 3D registration

    Radu Bogdan Rusu;Nico Blodow;Michael Beetz

  • Towards 3D Point cloud based object maps for household environments

    Radu Bogdan Rusu;Zoltan Csaba Marton;Nico Blodow;Mihai Dolha

  • Aligning point cloud views using persistent feature histograms

    R.B. Rusu;N. Blodow;Z.C. Marton;M. Beetz

  • Probabilistic Algorithms and the Interactive Museum Tour-Guide Robot Minerva

    Sebastian Thrun;Michael Beetz;Maren Bennewitz;Wolfram Burgard

  • RoboEarth - A World Wide Web for Robots

    Markus Waibel;Michael Beetz;Raffaello D'Andrea;Rob Janssen

  • KnowRob: A knowledge processing infrastructure for cognition-enabled robots

    Moritz Tenorth;Michael Beetz

  • KNOWROB — knowledge processing for autonomous personal robots

    Moritz Tenorth;Michael Beetz

  • Real-time compression of point cloud streams

    Julius Kammerl;Nico Blodow;Radu Bogdan Rusu;Suat Gedikli

  • On fast surface reconstruction methods for large and noisy point clouds

    Zoltan Csaba Marton;Radu Bogdan Rusu;Michael Beetz

  • Robotic roommates making pancakes

    Michael Beetz;Ulrich Klank;Ingo Kresse;Alexis Maldonado

  • Learning informative point classes for the acquisition of object model maps

    R.B. Rusu;Z.C. Marton;N. Blodow;M. Beetz

  • The TUM Kitchen Data Set of everyday manipulation activities for motion tracking and action recognition

    Moritz Tenorth;Jan Bandouch;Michael Beetz

  • Persistent Point Feature Histograms for 3D Point Clouds

    Radu Bogdan Rusu;Zoltan Csaba Marton;Nico Blodow;Michael Beetz

  • CRAM — A Cognitive Robot Abstract Machine for everyday manipulation in human environments

    Michael Beetz;Lorenz Mosenlechner;Moritz Tenorth

  • Close-range scene segmentation and reconstruction of 3D point cloud maps for mobile manipulation in domestic environments

    Radu Bogdan Rusu;Nico Blodow;Zoltan Csaba Marton;Michael Beetz

  • ORO, a knowledge management platform for cognitive architectures in robotics

    Severin Lemaignan;Raquel Ros;Lorenz Mosenlechner;Rachid Alami

  • Know Rob 2.0 — A 2nd Generation Knowledge Processing Framework for Cognition-Enabled Robotic Agents

    Michael Beetz;Daniel Bessler;Andrei Haidu;Mihai Pomarlan

  • Representations for robot knowledge in the KnowRob framework

    Moritz Tenorth;Michael Beetz

  • Fast-Switching Vis–IR Electrochromic Covalent Organic Frameworks

    Derya Bessinger;Katharina Muggli;Michael Beetz;Florian Auras

  • Cooperative probabilistic state estimation for vision-based autonomous mobile robots

    T. Schmitt;R. Hanek;M. Beetz;S. Buck

  • Model-based and learned semantic object labeling in 3D point cloud maps of kitchen environments

    Radu Bogdan Rusu;Zoltan Csaba Marton;Nico Blodow;Andreas Holzbach

Frequent Co-Authors

Zoltan-Csaba Marton
Zoltan-Csaba Marton Agile Robots AG
Radu Bogdan Rusu
Radu Bogdan Rusu Fyusion, Inc
Freek Stulp
Freek Stulp German Aerospace Center
Gordon Cheng
Gordon Cheng Technical University of Munich
Armin B. Cremers
Armin B. Cremers University of Bonn
Joachim Hertzberg
Joachim Hertzberg Osnabrück University
Martin Buss
Martin Buss Technical University of Munich
Kei Okada
Kei Okada University of Tokyo
Drew McDermott
Drew McDermott Yale University
Rachid Alami
Rachid Alami Laboratory for Analysis and Architecture of Systems

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