CRAM
A framework for cognitive robot abstract architectures to perform high-level tasks.
A framework for cognitive robot abstract architectures to perform high-level tasks.
PyCRAM is a toolbox for designing, implementing and deploying software on autonomous robots. The framework provides various tools and libraries for aiding in robot software development as well as geometric reasoning and fast simulation mechanisms to develop cognition-enabled control programs that achieve high levels of robot autonomy.
A knowledge-processing system for autonomous robots that integrates symbolic and geometric reasoning.
An open-source platform for task planning, execution, and monitoring in robotic systems.
A powerful framework for motion planning and control in high-dimensional robotic spaces.
Joint Probability Trees (short JPTs) are a formalism for learning of and reasoning about joint probability distributions, which is tractable for practical applications.
The Probalistic Model package contains fast and flexible implementations for various probabilistic models. This package provides a clean, unifying and well documented API to probabilistic models. Just like sklearn does for classical machine learning models.
The package is designed to provide a simple and flexible way to generate events that are suitable for probabilistic reasoning in a python.
Perception as inner realistic world construction that anticipates and explains the world state as well as observations in an explainable manner, with reasonable computational resources. NaivPhys4RP is a white-box and causal generative model of perception
Huerkamp, Malte, Dhanabalachandran, Kaviya, Pomarlan, Mihai, Stelter, Simon and Beetz, Michael, "A Modular Framework for Knowledge-Based Servoing: Plugging Symbolic Theories into Robotic Controllers", In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1, pp. 886–897, 2025.
Beetz, Michael, Huerkamp, Malte, Picklum, Mareike, Zhang, Jianwei and Lakemeyer, Gerhard, "AI-Powered and Cognition-Enabled Robotics: Advancing Autonomy and Human-Robot Collaboration", In 1st German Robotics Conference (GRC), 2025.
Beetz, Michael, Huerkamp, Malte, Hassouna, Vanessa, Kümpel, Michaela, Zhan, Yanxiang, Niedzwiecki, Arthur, Gandyra, Max, Hawkin, Alina, Nguyen, Giang and Picklum, Mareike, "Virtual Research Building: Accelerating Collaborative Robotics Research and Innovation", In 1st German Robotics Conference (GRC), 2025.
Kenghagho Kenfack, Franklin, Weibel, Jean-Baptiste, Aloui, Saifeddine, Prada, Miguel, Neumann, Michael, Dubois, Clémence, Raveendran, Nirmal, Grossard, Mathieu, Remazeilles, Anthony, Vincze, Markus and Beetz, Michael, "RobAuditor — A Methodology for Scalable and Context-Adaptive Task Execution Verification in Safety-Critical Robotic Processes", In , vol. , no. , pp. Submitted, 2025.
Kümpel, Michaela, "Enhancing Cognitive Robotics with Actionable Knowledge Graphs: A Framework for Context-Aware Reasoning", In 1st German Robotics Conference (GRC), 2025.
Kümpel, Michaela and Dech, Jonas, "Semantic Digital Twins for Omni-Channel Localisation", In Proceedings of the 11th IFAC MIM Conference on Manufacturing Modelling, Management and Control, 2025.
Maldonado, Jaime, Huerkamp, Malte, Krumme, Jonas, Zetzsche, Christoph and Beetz, Michael, "Robot Pouring: Modeling and Sim-to-Real Evaluation Using Causal Discovery", In Proceedings of the European Robotics Forum 2025 (Accepted for publication), 2025.
Mania, Patrick, Neumann, Michael, Kenghagho Kenfack, Franklin and Beetz, Michael, "Towards Autonomous Verification: Integrating Cognitive AI and Semantic Digital Twins in Medical Robotics", In 2025 International Conference on Robotics and Automation (ICRA), 2025. Accepted for publication
Beetz, Michael, Niedzwiecki, Arthur and Picklum, Mareike, "Semantic Verification through Mental Simulation of Generated Control Sequences for Autonomous Cognitive Household Robots", In 1st German Robotics Conference (GRC), 2025.
Pekarek-Rosin, Theresa, Hassouna, Vanessa, Sun, Xiaowen, Krohm, Luca, Kordt, Henri-Leon, Beetz, Michael and Wermter, Stefan, "A Framework for Adapting Human-Robot Interaction to Diverse User Groups", In Social Robotics, vol. , no. , pp. 24–38, 2025.
Alt, Benjamin, Kienle, Claudius, Katic, Darko, Jäkel, Rainer and Beetz, Michael, "Shadow Program Inversion with Differentiable Planning: A Framework for Unified Robot Program Parameter and Trajectory Optimization", In 2025 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Atlanta, USA, 2025.
Hassouna, Vanessa, Huerkamp, Malte and Beetz, Michael, "Task-Critical Motion Patterns in Task Planning and Motion Control for Household Manipulation Tasks", In ICRA40 – 40th Anniversary of the IEEE International Conference on Robotics and Automation, 2024. In press.
Kenghagho, Franklin Kenfack, Neumann, Michael, Mania, Patrick and Beetz, Michael, "Perception through Cognitive Emulation: 'A Second Iteration of NaivPhys4RP for Learningless and Safe Recognition and 6D-Pose Estimation of (Transparent) Objects'", In 2024 IEEE International Conference on Robotics and Automation (ICRA), pp. 7679–7685, 2024.
Kümpel, Michaela, Vyas, Abhijit, Hassouna, Vanessa and Beetz, Michael, "Task Learning Using Actionable Knowledge Graphs", In ICRA40 – 40th Anniversary of the IEEE International Conference on Robotics and Automation, 2024.
Kümpel, Michaela, Töberg, Jan-Phillip, Hassouna, Vanessa, Cimiano, Phillip and Beetz, Michael, "Towards a Knowledge Engineering Methodology for Flexible Robot Manipulation in Everyday Tasks", In Actionable Knowledge Representation and Reasoning for Robots (AKR³) at European Semantic Web Conference (ESWC), 2024.
Mania, Patrick, Stelter, Simon, Kazhoyan, Gayane and Beetz, Michael, "An Open and Flexible Robot Perception Framework for Mobile Manipulation Tasks", In 2024 International Conference on Robotics and Automation (ICRA), 2024.
Nguyen, Giang, Beßler, Daniel, Stelter, Simon, Pomarlan, Mihai and Beetz, Michael, "Translating Universal Scene Descriptions into Knowledge Graphs for Robotic Environment", In 2024 IEEE International Conference on Robotics and Automation (ICRA), pp. 9389–9395, 2024.
Niedzwiecki, Arthur, Jongebloed, Sönke, Zhan, Yanxiang, Kümpel, Michaela, Syrbe, Jan, Beetz, Michael, "Cloud-based Digital Twin for Cognitive Robotics", In IEEE Global Engineering Education Conference (EDUCON), pp. 1–5, 2024,
Syrbe, Jan, Rümenapp, Tim, Wenzl, Paul, Kümpel, Michaela, Beetz, Michael, Niedzwiecki, Arthur, "Interactive E-Learning Environment for Cognitive Robotics", In IEEE Global Engineering Education Conference (EDUCON), pp. 01–09, 2024.
Alt, Benjamin, Dvorak, Julia, Katic, Darko, Jäkel, Rainer, Beetz, Michael and Lanza, Gisela, "BANSAI: Towards Bridging the AI Adoption Gap in Industrial Robotics with Neurosymbolic Programming", In Procedia CIRP, Elsevier B.V., vol. 130, Póvoa de Varzim, Portugal, pp. 532–537, 2024.
Alt, Benjamin, Zahn, Johannes, Kienle, Claudius, Dvorak, Julia, May, Marvin, Katic, Darko, Jäkel, Rainer, Kopp, Tobias, Beetz, Michael and Lanza, Gisela, "Human-AI Interaction in Industrial Robotics: Design and Empirical Evaluation of a User Interface for Explainable AI-Based Robot Program Optimization", In Procedia CIRP, Elsevier B.V., vol. 130, Póvoa de Varzim, Portugal, pp. 591–596, 2024.
Alt, Benjamin, Stöckl, Florian, Müller, Silvan, Braun, Christopher, Raible, Julian, Alhasan, Saad, Rettig, Oliver, Ringle, Lukas, Katic, Darko, Jäkel, Rainer, Beetz, Michael, Strand, Marcus and Huber, Marco F., "RoboGrind: Intuitive and Interactive Surface Treatment with Industrial Robots", In 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Yokohama, Japan, pp. 1–8, 2024.