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Publications: Area Z and Joint Publications

This section lists publications by the CML consortium from the integration activities and publications that are not related to one specific research subproject.

  • Chen, J., Zhang, D., Engel, A. K., Gong, Q., & Maye, A. (2017). Application of a single-flicker online SSVEP BCI for spatial navigation. PloS one, 12(5), e0178385. DOI: https://doi.org/10.1371/journal.pone.0178385
  • Zheng, W., Liu, Y., Liu, C. H., Chen, Y. H., Cui, Q., & Fu, X. (2019). The Influence of Event Valence and Emotional States on the Metaphorical Comprehension of Time. Frontiers in psychology, 10, 410.
  • Ni, L., Liu, Y., & Yu, W. (2019). The dominant role of functional action representation in object recognition. Experimental brain research, 237(2), 363-375.
  • 吴迪, 顾晶金, 李明, 张淼, 张明, 赵科, & 傅小兰. (2019). 动作的主动控制感与因果关系的主动控制感: 主动动作时间压缩效应的产生机制. 心理科学进展, 27(5), 804-810.
  • 於文苑, 刘烨*, 傅小兰, 龚江涛, 徐迎庆*. (2019). 触觉二维图像识别的认知机制.心理科学进展,27(04):611-622.
  • Liang, J., Chen, Y. H., Yan, W. J., Qu, F., & Fu, X. (2018). Effects of task-irrelevant emotional information on deception. Cognition and Emotion, 32(6), 1265-1274.
  • Zhang, Z., Chen, T., Meng, H., Liu, G., & Fu, X. (2018). SMEConvnet: A convolutional neural network for spotting spontaneous facial micro-expression from long videos. IEEE Access, 6, 71143-71151.
  • Cui, Q., Zhao, K., Chen, Y. H., Zheng, W., & Fu, X. (2018). Opposing subjective temporal experiences in response to unpredictable and predictable fear-relevant stimuli. Frontiers in psychology, 9, 360.
  • Gong, M., Xuan, Y., Smart, L. J., & Olzak, L. A. (2018). The extraction of natural scene gist in visual crowding. Scientific reports, 8(1), 14073
  • Zheng, W., Liu, Y., & Fu, X. (2018). The Temporal-Spatial Metaphorical Expression Difference in Spatial Schema Design. In International Conference on Human-Computer Interaction, 225-234. Springer, Cham.
  • Yu, W., Liu, Y., & Fu, X. (2018, July). The Effect of Static and Dynamic Gesture Presentation on the Recognition of Two Manipulation Gestures. In International Conference on Human-Computer Interaction,. 366-379. Springer, Cham.
  • 郑玮琦, 刘烨, & 傅小兰. (2018). 感觉鄄运动系统参与隐喻理解的认知神经机制. 生物化学与生物物理进展, 45(3), 325-335.
  • 於文苑, 刘烨, & 傅小兰. (2018). 可操作物体识别过程中的两种操作动作表征. 心理科学进展, 26(2), 229-240.
  • 崔倩, 赵科, & 傅小兰. (2018). 情绪调节时间知觉的作用方式及认知神经机制. 生物化学与生物物理进展, 45(4), 409-421.
  • 龚江涛, 於文苑, 曲同, 刘烨, 傅小兰, & 徐迎庆. (2018). 影响触觉图像识别因素的量化分析. 计算机辅助设计与图形学学报, (08), 1438-1445.
  • Peng, M., Wang, C., Chen, T., Liu, G., & Fu, X. (2017). Dual temporal scale convolutional neural network for micro-expression recognition. Frontiers in psychology, 8, 1745.
  • Qu, F., Yan, W. J., Chen, Y. H., Li, K., Zhang, H., & Fu, X. (2017). “You Should Have Seen the Look on Your Face…”: Self-awareness of Facial Expressions. Frontiers in psychology, 8, 832.

Project Z3: Integration

Publications of the current project

  • J. Scholz, C. Weber, M.B. Hafez and S. Wermter (2021). Improving Model-Based Reinforcement Learning with Internal State Representations through Self-Supervision, Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), Virtual event, pp. 1–8, 2021.
  • M.B. Hafez and S. Wermter (2021). Behavior Self-Organization Supports Task Inference for Continual Robot Learning, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, Czech Republic, pp. 6716–6723, 2021.
  • M.B. Hafez, C. Weber, M. Kerzel and S. Wermter (2020). Improving Robot Dual- System Motor Learning with Intrinsically Motivated Meta-Control and Latent-Space Experience Imagination, Robotics and Autonomous Systems, vol. 133, pp. 103630, 2020.
  • Korn, C., Redzepovic, S., Gläscher, J., Kerzel, M., Barros, P., Heinrich, S., & Wermter, S. (2021). Cross-modal emotion recognition: How similar are patterns between DNNs and human fMRI data? Proceedings of the ICLR2021 Workshop on How Can Findings About The Brain Improve AI Systems? (Brain2AI@ICLR2021), Number 18 - May 2021.
  • Özdemir, O., Kerzel, M., & Wermter, S. (2021). Embodied Language Learning with Paired Variational Autoencoders. In 2021 IEEE International Conference on Development and Learning (ICDL) (pp. 1-6). IEEE.
  • Li, M., Weber, C., Kerzel, M., Lee, J. H., Zeng, Z., Liu, Z., & Wermter, S. (2021). Robotic Occlusion Reasoning for Efficient Object Existence Prediction. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • Duczek, N., Kerzel, M., & Wermter, S. (2021). Continual Learning from Synthetic Data for a Humanoid Exercise Robot. Frontiers in Neurorobotics. submitted.
  • Logacjov, A., Kerzel, M., & Wermter, S. (2021). Learning Then, Learning Now, and Every Second in Between: Lifelong Learning With a Simulated Humanoid Robot. Frontiers in Neurorobotics, 15.
  • Jirak, D., Biertimpel, D., Kerzel, M., & Wermter, S. (2021). Solving visual object ambiguities when pointing: an unsupervised learning approach. Neural Computing and Applications, 33(7), 2297-2319.
  • Mir, G., Kerzel, M., Strahl, E., & Wermter, S. (2021). A Humanoid Robot Learning Audiovisual Classification By Active Exploration. In 2021 IEEE International Conference on Development and Learning (ICDL) (pp. 1-6). IEEE.
  • Daniel Ahlers, Florens Wasserfall, Norman Hendrich, Arne Büngener, Jan-Tarek Butt, Jianwei Zhang (2021). Automated In-Situ Placing of Metal Components Into 3D Printed FFF Objects, IEEE Transactions on Mechatronics (TMECH), and IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM-2021), 2021. DOI: 10.1109/TMECH.2021.3078409
  • Máximo A. Roa, Mehmet Dogar, Jordi Pages, Carlos Vivas, Antonio Morales, Nikolaus Correll, Michael Görner, Jan Rosell, Sergi Foix, Raphael Memmesheimer, and Francesco Ferro (2021). Mobile Manipulation Hackathon: Moving Into Real-World Applications, IEEE Robotics & Automation Magazine, March 2021, p. 2-14. DOI: 10.1109/MRA.2021.3061951
  • Norman Hendrich, Florens Wasserfall and Jianwei Zhang (2020). 3D Printed Low-Cost Force-Torque Sensors, IEEE Access, 2020. doi: https://doi.org/10.1109/ACCESS.2020.3007565
  • Ronja Güldenring, Michael Görner, Norman Hendrich, Niels Jul Jacobsen, Jianwei Zhang (2020). Learning Local Planners for Human-aware Navigation in Indoor Environment, International Conference on Intelligent Robots and Systems (IROS) 2020, Las, Vegas, USA.
  • Lin Cong, Michael Görner, Philipp Ruppel, Hongzhuo Liang, Norman Hendrich, Jianwei Zhang (2020). Self-Adapting Recurrent Models for Object Pushing from Learning in Simulation, International Conference on Intelligent Robots and Systems (IROS) 2020, Las Vegas, USA.
  • Philipp Ruppel, Michael Görner, Norman Hendrich, Jianwei Zhang (2020). Detection and Reconstruction of Transparent Objects with Infrared Projection-based RGB-D Cameras, International Conference on Cognitive Systems and Information Processing (ICCSIP) 2020, Springer Communications in Computer and Information Science, vol 1397. DOI: 10.1007/978-981-16-2336-3_53
  • Fu, D., Weber, C., Yang, G., Kerzel, M., Nan, W., Barros, P., Wu, H., Liu, W. & Wermter, S. (2020). What can computational models learn from human selective attention? A review from an audiovisual unimodal and crossmodal perspective. Frontiers in integrative neuroscience, 14, 10.
  • Heinrich, S., Yao, Y., Hinz, T., Liu, Z., Hummel, T., Kerzel, M., Weber, C., & Wermter, S. (2020). Crossmodal language grounding in an embodied neurocognitive model. Frontiers in Neurorobotics, 14.
  • Kerzel, M., & Wermter, S. (2020). Towards a data generation framework for affective shared perception and Social cue learning using virtual avatars. Workshop on Affective Shared Perception, ICDL 2020.
  • Kerzel, M., Pekarek-Rosin, T., Strahl, E., Heinrich, S., & Wermter, S. (2020). Teaching Nico how to grasp: an empirical study on crossmodal social interaction as a key factor for robots learning from humans. Frontiers in Neurorobotics, 14, 28.
  • Hafez, M. B., Weber, C., Kerzel, M., & Wermter, S. (2020). Improving robot dual-system motor learning with intrinsically motivated meta-control and latent-space experience imagination. Robotics and Autonomous Systems, 133, 103630.
  • Beik-Mohammadi, H., Kerzel, M., Pleintinger, B., Hulin, T., Reisich, P., Schmidt, A., Pereira, A., Wertmer, S., & Lii, N. Y. (2020). Model mediated teleoperation with a hand-arm exoskeleton in long time delays using reinforcement learning. In 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)713-720. IEEE.
  • Kerzel, M., Spisak, J., Strahl, E., & Wermter, S. (2020). Neuro-Genetic Visuomotor Architecture for Robotic Grasping. In International Conference on Artificial Neural Networks (ICANN-2020) pp. 533-545. Springer, Cham.
  • Kerzel, M., Abawi, F., Eppe, M., & Wermter, S. (2020). Enhancing a Neurocognitive Shared Visuomotor Model for Object Identification, Localization, and Grasping With Learning From Auxiliary Tasks. IEEE Transactions on Cognitive and Developmental Systems.

Publications of the phase-1 project

  • Beik-Mohammadi, H., Ali Zamani, M., Kerzel, M., Wermter, M. (2019). Mixed-Reality Deep Reinforcement Learning for a Reach-to-grasp Task. Artificial Neural Networks and Machine Learning (ICANN 2019).
  • Hafez B., Weber, C., Kerzel, M., Wermter, M. (2019). Efficient Intrinsically Motivated Robotic Grasping with Learning-Adaptive Imagination in Latent Space. Proceedings of the Ninth Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL-EpiRob), pages 240-246.
  • Kerzel, M., Eppe, M., Heinrich, S., Abawi, F., Wermter, S. (2019). Neurocognitive Shared Visuomotor Network for End-to-end Learning of Object Identification, Localization and Grasping on a Humanoid. 2019 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), pages 19-24.
  • Hafez, B., Weber, C., Kerzel, M., Wermter, S. (2019). Curious Meta-Controller: Adaptive Alternation between Model-Based and Model-Free Control in Deep Reinforcement Learning. Proceedings of the International Joint Conference on Neural Networks (IJCNN).
  • Kerzel, M., Strahl, E., Gaede, C., Gasanov, E., Wermter, S. (2019). Neuro-Robotic Haptic Object Classification by Active Exploration on a Novel Dataset. Proceedings of the International Joint Conference on Neural Networks (IJCNN 2019).
  • Heinrich, S., Springstübe, P., Knöppler, T., Kerzel, M., Wermter, S. (2019). Continuous convolutional object tracking in developmental robot scenarios. Neurocomputing, Volume 342, pages 137-144. doi:10.1016/j.neucom.2018.10.086 (open access).
  • Hafez, B., Weber, C., Kerzel, M., Wermter, S. (2019). Deep Intrinsically Motivated Continuous Actor-Critic for Efficient Robotic Visuomotor Skill Learning. Paladyn. Journal of Behavioral Robotics, Volume 10, Number 1, pages 14-29. doi:10.1515/pjbr-2019-0005 (open access).
  • Philipp Ruppel, Norman Hendrich, Jianwei Zhang (2019). Low-cost multi-view pose tracking using active markers, IEEE ICPS/MFI 2019, pp. 261-268, Taipei, Taiwan.
  • Niklas Fiedler, Marc Bestmann, Jianwei Zhang (2019). Position Estimation on Image-Based Heat Map Input using Particle Filters in Cartesian Space, IEEE ICPS/MFI 2019, pp. 269-274, Taipei, Taiwan.
  • Xinqiang Pan, Yao Shuai, Chuangui Wu, Lu Zhang, Hongliang Guo, Hong Cheng, Yun Peng, Shijun Qiao, Wenbo Luo, Tao Wang, Xiangyu Sun, Huizhong Zeng, Jianwei Zhang, Wanli Zhang, Xin Ou, Nan Du, Heidemarie Schmidt (2019). Ar+ ions irradiation induced memristive behavior and neuromorphic computing in monolithic LiNbO3 thin films, Applied Surface Science 484, p. 751–758 (2019), doi: 0.1016/j.apsusc.2019.04.114
  • Xinqiang Pan, Yao Shuai, Chuangui Wu, Wenbo Luo, Xiangyu Sun, Huizhong Zeng, Hongliang Guo, Ye Yuan, Shengqiang Zhou, Roman Böttger, Hong Cheng, Jianwei Zhang, Wanli Zhang, Heidemarie Schmidt (2019). Compliance-current-modulated resistive switching with multi-level resistance states in single-crystalline LiNbO3 thin film. Solid State Ionics, 334, p. 1-4, 2019. doi: 10.1016/j.ssi.2019.01.026
  • Lu, S., Qi, X., Hu, Y., Li, B., & Zhang, J. (2019). Deployment Dynamics of Large Space Antenna and Supporting Arms. IEEE Access.
  • Sun, Y., Jiang, Z., Qi, X., Hu, Y., Li, B., & Zhang, J. (2019). Model-based spinal deformation compensation in robot-assisted decompressive laminectomy. Mechatronics, 59, 115-126.
  • Siqueira H., Sutherland, A., Barros, P., Kerzel, M., Magg, S., Wermter, S. (2018). Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue. IEEE-RAS International Conference on Humanoid Robots (Humanoids), 433-440.
  • Heinrich, S., Kerzel, M., Strahl, E., Wermter, S. (2018). Embodied Multi-modal Interaction in Language learning: the EMIL data collection. Proceedings of the ICDL-EpiRob Workshop on Active Vision, Attention, and Learning (ICDL-Epirob 2018 AVAL).
  • Beik-Mohammadi, H., Kerzel, M., Görner, M., Zamani, M. A., Eppe, M., and Wermter, S. (2018). Neural end-to-end learning of reach for grasp ability with a 6-DOF robot arm. IROS 2018 Workshop on Machine Learning in Robot Motion Planning.
  • Eppe, M., Kerzel, M., Strahl, E., and Wermter, S. (2018). Deep neural object analysis by interactive auditory exploration with a humanoid robot. IEEE/RSJ International Conference on Intelligent Robots and Systems.
  • Griffiths, S., Alpay, T., Sutherland, A., Kerzel, M., Eppe, M., Strahl, E., and Wermter, S. (2018). Exercise with social robots: Companion or coach? Sebastian Schneider, Sascha Griffiths, C. A. C. G. S. W. B. W., editor, Proceedings of Workshop on Personal Robots for Exercising and Coaching at the HRI 2018 (HRI2018), New York, NY, USA. ACM.
  • Hafez, B., Kerzel, M., Weber, C., and Wermter, S. (2018). Slowness-based neural visuomotor control with an intrinsically motivated continuous actor-critic. Proceedings of the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), pages 509–514.
  • Hafez, B., Weber, C., Kerzel, M., and Wermter, S. (2018). Deep intrinsically motivated continuous actor-critic for efficient robotic visuomotor skill learning. arXiv:1810.11388 (Accepted in Paladyn, Journal of Behavioral Robotics).
  • Josifovski, J., Kerzel, M., Pregizer, C., Posniak, L., and Wermter, S. (2018). Object detection and pose estimation based on convolutional neural networks trained with synthetic data. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, pages 6269–6276.
  • Kerzel, M., Beik-Mohammadi, H., Zamani, M. A., and Wermter, S. (2018). Accelerating deep continuous reinforcement learning through task simplification. International Joint Conference on Neural Networks (IJCNN), pages 139–144.
  • Ng, H. G., Kerzel, M., Mehnert, J., May, A., and Wermter, S. (2018). Classification of mri migraine medical data using 3d convolutional neural network. International Conference on Artificial Neural Networks - ICANN 2018, pages 300–309. Springer.
  • Strahl, E., Kerzel, M., Eppe, M., Griffiths, S., and Wermter, S. (2018). Hear the egg demonstrating robotic interactive auditory perception. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2018.
  • Zamani, M. A., Beik-Mohammadi, H., Kerzel, M., Magg, S., and Wermter, S. (2018). Learning spatial representation for safe human-robot collaboration in joint manual tasks. ICRA workshop on the WORKplace is better with intelligent, collaborative, robot MATEs (WORKMATE) .
  • Fiedler, N., Bestmann, M., and Hendrich, N. (2018). ImageTagger: An Open Source Online Platform for Collaborative Image Labeling, RoboCup Symposium 2018, Montreal, Canada.
  • Speck, D., Bestmann, M., and Barros, P. (2018). Towards Real-Time Ball Localization using CNNs. RoboCup Symposium 2018, Montreal, Canada.
  • Li, S., Liang, H., and Zhang, J. (2018). Path Planning for Wheeled Mobile Service Robots based on Improved Genetic Algorithm", Shanghai International Symposium on Human-Centered Robotics (HCR), 251-254, 2018.
  • Kerzel, M., Wermter, S. (2017). Learning of neurobotic visuomotor abilities based on interactions with the environment, Proceedings of the DGR Days 2017, T. Asfour and M. Beetz, Eds., pages 14-15.
  • Parisi, G.I., Barros, M., Kerzel, M., Wu, H., Yang, G., Li, Z., Liu, X., Wermter S. (2017). A computational model of crossmodal processing for conflict resolution. Proceedings of the 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics., pages 33-38.
  • Kerzel, M., Wermter S. (2017). Neural end-to-end self-learning of visuomotor skills by environment interaction. Artificial Nueral Networks and Machine Learning, ICANN-2017. Lecture Notes in Computer Science, vol. 10613, Springer. pages 27-34.
  • Kerzel, M., Strahl, E., Magg, S., Navarro-Guerrero, N., Heinrich, S., Wertmer S. (2017). NICO - neuro-inspired companion: A developmental humanoid robot platform for multimodal interaction. Proceedings IEEE International Symposium on Robot and Human Interactive Communication (ROMAN-2017). pages 113-120.
  • Kerzel, M., Ali, M.M.M., Ng, H.G., Wermter S. (2017). Haptic material classification with a multi-channel neural neetwork. International Joint Conference on Neural networks, IJCNN-2017, Anchorage, Alaska. IEEE, pages 439-446.
  • Eppe, M., Kerzel, M., Griffiths, S., Ng, H.G., Wermter S. (2017). Combining deep learning for visuomotor coordination with object identification to realize a high-level interface for robot object-picking. IEEE-RAS International Conference on Humanoid Robots (Humanoids-2017), pages 612-617.
  • Kerzel, M., Ng, H.G., Griffiths, S., Wermter S. (2017). Effect of a humanoids active role during learning with embodied dialogue systems. Workshop Towards Intelligent Social Robots, IEEE International Symposium on Robot and Human Interactive Communication (ROMAN-2017).
  • Li Q., Liu G., Tang J., Zhang J. (2016). A simple 2D straight-leg passive dynamic walking model without foot-scuffing problem. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 5155-5161.