People

Oliver Brock

Principal Investigator

Robotics

TU Berlin

 

Email:

Phone: +49 30 314 73111

 

Photo: SCIoI

← People Overview

Oliver Brock

Oliver Brock

Photo: SCIoI

Oliver Brock represents the synthetic discipline robotics. He has extensive experience in building real-world robotic systems, contributing also to related disciplines, including perception and machine learning. Within the fields of robotics, he is a leader in leveraging collaborations with analytical disciplines, in particular psychology and behavioral biology, to work towards an understanding of embodied intelligence.


Projects

Oliver Brock is member of:


6984777 Brock 1 apa 50 date desc year 19817 https://www.scienceofintelligence.de/wp-content/plugins/zotpress/
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Weber, L., Wienert, T., Splettstößer, M., Koenig, A., & Brock, O. (2026). Acoustic Sensing for Universal Jamming Grippers. IEEE International Conference on Robotics and Automation (ICRA). https://rbo.gitlab-pages.tu-berlin.de/papers/acoustic-jamming-icra26/
Mengers, V., & Brock, O. (2025). No Plan but Everything Under Control: Robustly Solving Sequential Tasks with Dynamically Composed Gradient Descent. 2025 IEEE International Conference on Robotics and Automation (ICRA), 90–96. https://doi.org/10.1109/ICRA55743.2025.11127552
Pfisterer, A., Li, X., Mengers, V., & Brock, O. (2025). A Helping (Human) Hand in Kinematic Structure Estimation. 2025 IEEE International Conference on Robotics and Automation (ICRA), 11918–11925. https://doi.org/10.1109/ICRA55743.2025.11127847
Mengers, V., Roth, N., Brock, O., Obermayer, K., & Rolfs, M. (2025). A robotics-inspired scanpath model reveals the importance of uncertainty and semantic object cues for gaze guidance in dynamic scenes. Journal of Vision, 25(2), 6. https://doi.org/10.1167/jov.25.2.6
Yordanova, M., & Hafner, V. V. (2025). Memory-Feedback Controllers for Lifelong Sensorimotor Learning in Humanoid Robots. In O. Brock & J. Krichmar (Eds.), From Animals to Animats 17 (pp. 275–286). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-71533-4_21
Karimian, M., Reeh, F., Daneshi, A., Brass, M., & Romanczuk, P. (2025). Behavioural Contagion in Human and Artificial Multi-agent Systems: A Computational Modeling Approach. In O. Brock & J. Krichmar (Eds.), From Animals to Animats 17 (pp. 145–156). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-71533-4_11
Zheng, Y., & Romanczuk, P. (2025). Bio-Inspired Agent-Based Model for Collective Shepherding. In O. Brock & J. Krichmar (Eds.), From Animals to Animats 17 (pp. 182–193). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-71533-4_14
Sevinchan, Y., Vollmoeller, C., Pacher, K., Bierbach, D., Arias-Rodriguez, L., Krause, J., & Romanczuk, P. (2025). Spatio-Temporal Dynamics of Social Contagion in Bio-inspired Interaction Networks. In O. Brock & J. Krichmar (Eds.), From Animals to Animats 17 (pp. 133–144). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-71533-4_10
Petković, U., Frenkel, J., Hellwich, O., & Lazarides, R. (2025). Nonverbal Immediacy Analysis in Education: A Multimodal Computational Model. In O. Brock & J. Krichmar (Eds.), From Animals to Animats 17 (pp. 326–338). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-71533-4_26
Zenkri, O., Bolenz, F., Pachur, T., & Brock, O. (2025). Extracting Principles of Exploration Strategies with a Complex Ecological Task. In O. Brock & J. Krichmar (Eds.), From Animals to Animats 17 (pp. 289–300). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-71533-4_22
Bartashevich, P., Knopf, L., & Romanczuk, P. (2025). Transient Milling Dynamics in Collective Motion with Visual Occlusions. In O. Brock & J. Krichmar (Eds.), From Animals to Animats 17 (pp. 157–168). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-71533-4_12
Battaje, A., Hanning, N., Brock, O., & Rolfs, M. (2025). Depth and Interaction Modulate Color Aftereffects in Virtual Reality [Poster]. European Conference on Visual Perception (ECVP).
Weber, L., Wienert, T., Splettstößer, M., Koenig, A., & Brock, O. (2025). Acoustic Sensing for Universal Jamming Grippers. Workshop on Acoustic Sensing and Representations for Robotics at the IEEE International Conference on Robotics and Automation (ICRA).
Mengers, V., Battaje, A., & Brock, O. (2025). AICON: A Representation for Adaptive Behavior. 1st German Robotics Conference (GRC).
Mengers, V., Koenig, A., Li, X., Sieler, A., Battaje, A., & Brock, O. (2025). Stop Merging, Start Separating: Why Merging Learning and Modeling Won’t Solve Manipulation but Separating the General From the Specific Will. International Conference on Robotics & Automation (ICRA) Workshop: Learning Meets Model-Based Methods for Contact-Rich Manipulation.
Brock, O. (2024). Intelligence as Computation. IOP Conference Series: Materials Science and Engineering, 1321(1), 012001. https://doi.org/10.1088/1757-899X/1321/1/012001
Mengers, V., Raoufi, M., Brock, O., Hamann, H., & Romanczuk, P. (2024). Leveraging uncertainty in collective opinion dynamics with heterogeneity. Scientific Reports, 14(1), 27314. https://doi.org/10.1038/s41598-024-78856-8
Battaje, A., Godinez, A., Hanning, N. M., Rolfs, M., & Brock, O. (2024). An Information Processing Pattern from Robotics Predicts Unknown Properties of the Human Visual System. bioRxiv. https://doi.org/10.1101/2024.06.20.599814
Baum, M., Rössler, T., Osuna-Mascaró, A. J., Auersperg, A., & Brock, O. (2024). Mechanical Problem Solving in Goffin’s Cockatoos—Towards Modeling Complex Behavior. Adaptive Behavior, 32(6), 551–562. https://doi.org/10.1177/10597123241270764
Li, X., Zenkri, O., Pfisterer, A., & Brock, O. (2024). A Biologically Inspired Design Principle for Building Robust Robotic Systems. arXiv. https://doi.org/10.48550/ARXIV.2408.10192
Li, X., Baum, M., & Brock, O. (2023). Augmentation Enables One-Shot Generalization in Learning from Demonstration for Contact-Rich Manipulation. 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 3656–3663. https://doi.org/10.1109/IROS55552.2023.10341625
Sieler, A., & Brock, O. (2023). Dexterous Soft Hands Linearize Feedback-Control for In-Hand Manipulation. 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 8757–8764. https://doi.org/10.1109/IROS55552.2023.10341438
Patidar, S., Sieler, A., & Brock, O. (2023). In-Hand Cube Reconfiguration: Simplified. 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 8751–8756. https://doi.org/10.1109/IROS55552.2023.10341521
Baum, M., Froessl, A., Battaje, A., & Brock, O. (2023). Estimating the Motion of Drawers From Sound. 2023 IEEE International Conference on Robotics and Automation (ICRA), 697–703. https://doi.org/10.1109/ICRA48891.2023.10161399
Mengers, V., Battaje, A., Baum, M., & Brock, O. (2023). Combining Motion and Appearance for Robust Probabilistic Object Segmentation in Real Time. 2023 IEEE International Conference on Robotics and Automation (ICRA), 683–689. https://doi.org/10.1109/ICRA48891.2023.10160908
Stahl, K., Graziadei, A., Dau, T., Brock, O., & Rappsilber, J. (2023). Protein structure prediction with in-cell photo-crosslinking mass spectrometry and deep learning. Nature Biotechnology, 41(12), 1810–1819. https://doi.org/10.1038/s41587-023-01704-z
Battaje, A., Brock, O., & Rolfs, M. (2023). An interactive motion perception tool for kindergarteners (and vision scientists). I-Perception, 14(2), 20416695231159182. https://doi.org/10.1177/20416695231159182
Wall, V., Zöller, G., & Brock, O. (2023). Passive and active acoustic sensing for soft pneumatic actuators. The International Journal of Robotics Research, 42(3), 108–122. https://doi.org/10.1177/02783649231168954
Godinez, A., Battaje, A., Brock, O., & Rolfs, M. (2023). Probing perceptual mechanism of shape-contingent color after-images via interconnected recursive filters. In Journal of Vision [Poster]. Vision Science Society Annual Meeting (VSS). https://doi.org/10.1167/jov.23.9.4885
Battaje, A., & Brock, O. (2022). One Object at a Time: Accurate and Robust Structure From Motion for Robots. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 3598–3603. https://doi.org/10.1109/IROS47612.2022.9981953
Wall, V., & Brock, O. (2022). A Virtual 2D Tactile Array for Soft Actuators Using Acoustic Sensing. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 10029–10034. https://doi.org/10.1109/IROS47612.2022.9981225
Pannen, T. J., Puhlmann, S., & Brock, O. (2022). A Low-Cost, Easy-to-Manufacture, Flexible, Multi-Taxel Tactile Sensor and its Application to In-Hand Object Recognition. 2022 International Conference on Robotics and Automation (ICRA), 10939–10944. https://doi.org/10.1109/ICRA46639.2022.9811761
Baum, M., & Brock, O. (2022). “The World Is Its Own Best Model”: Robust Real-World Manipulation Through Online Behavior Selection. 2022 International Conference on Robotics and Automation (ICRA), 1499–1505. https://doi.org/10.1109/ICRA46639.2022.9811845
Puhlmann, S., Harris, J., & Brock, O. (2022). RBO Hand 3 : A Platform for Soft Dexterous Manipulation. IEEE Transactions on Robotics, 38(6), 3434–3449. https://doi.org/10.1109/TRO.2022.3156806
Li, X., & Brock, O. (2022). Learning From Demonstration Based on Environmental Constraints. IEEE Robotics and Automation Letters, 7(4), 10938–10945. https://doi.org/10.1109/LRA.2022.3196096
Baum, M., Schattenhofer, L., Rössler, T., Osuna-Mascaró, A., Auersperg, A., Kacelnik, A., & Brock, O. (2022). Yoking-Based Identification of Learning Behavior in Artificial and Biological Agents. In L. Cañamero, P. Gaussier, M. Wilson, S. Boucenna, & N. Cuperlier (Eds.), From Animals to Animats 16 (Vol. 13499, pp. 67–78). Springer International Publishing. https://doi.org/10.1007/978-3-031-16770-6_6
Bhatt*, A., Sieler*, A., Puhlmann, S., & Brock, O. (2021, July 12). Surprisingly Robust In-Hand Manipulation: An Empirical Study. Robotics: Science and Systems XVII. Robotics: Science and Systems 2021. https://doi.org/10.15607/RSS.2021.XVII.089
Pall, E., & Brock, O. (2021). Analysis of Open-Loop Grasping From Piles. 2021 IEEE International Conference on Robotics and Automation (ICRA), 2591–2597. https://doi.org/10.1109/ICRA48506.2021.9561065
Baum, M., & Brock, O. (2021). Achieving Robustness in a Drawer Manipulation Task by using High-level Feedback instead of Planning. Proceedings of the DGR Days, 29–29.
Roy, N., Posner, I., Barfoot, T., Beaudoin, P., Bengio, Y., Bohg, J., Brock, O., Depatie, I., Fox, D., Koditschek, D., Lozano-Perez, T., Mansinghka, V., Pal, C., Richards, B., Sadigh, D., Schaal, S., Sukhatme, G., Therien, D., Toussaint, M., & Van de Panne, M. (2021). From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence. arXiv. https://doi.org/10.48550/ARXIV.2110.15245
Battaje, A., & Brock, O. (2021). Interconnected Recursive Filters in Artificial and Biological Vision. Proceedings of the DGR Days, 32–32.
Zoller, G., Wall, V., & Brock, O. (2020). Active Acoustic Contact Sensing for Soft Pneumatic Actuators. 2020 IEEE International Conference on Robotics and Automation (ICRA), 7966–7972. https://doi.org/10.1109/ICRA40945.2020.9196916
Morik, M., Rastogi, D., Jonschkowski, R., & Brock, O. (2019). State Representation Learning with Robotic Priors for Partially Observable Environments. 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 6693–6699. https://doi.org/10.1109/IROS40897.2019.8967938
Wall, V., & Brock, O. (2019). Multi-Task Sensorization of Soft Actuators Using Prior Knowledge. 2019 International Conference on Robotics and Automation (ICRA), 9416–9421. https://doi.org/10.1109/ICRA.2019.8793697

Werner Heisenberg Medaille (2024)

Perraudin, L., Brock, O., Coelho Mollo, D., Mareis, C., Müller, M., Nestler, A., Puhlmann, S., Schäffner, W., Steinhardt, S. 2021. »Wenn Materie lebendig wird«. Experimentallabor für Wissenschaftskommunikation »CollActive Materials«. Berlin University Alliance, project funding for 2022-2024.
https://www.collactive-materials.de/

Research

An overview of our scientific work

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