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Peer Neubert

Dr.-Ing. Peer Neubert

Portrait: Dr.-Ing. Peer Neubert
Dr.-Ing. Peer Neubert
  • Phone:
    +49 371 531-38616
  • Email:
  • Address:
    Reichenhainer Straße 70, 09126 Chemnitz
  • Room:
    2/W125 (new: C25.125)

Recent event

We organized a free online tutorial on Vector Symbolic Architectures at the European Conference on Artificial Intelligence 2020 (ECAI). More information, slides, and code can be found on our tutorial website.

Research Interests

My research interests are in the fields of mobile robotics and artificial intelligence. I use computer vision and machine learning as tools within these fields. I have particular experience in the areas of place recognition in changing environments, hand crafted and deep-learned visual features, mobile robot navigation, biologically inspired perception and navigation approaches, as well as high-dimensional computing.

Details on my research can be found in the list of publications or here:

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Software

Of particular interest might be these open source software releases:
  • Superpixel benchmarks
  • Superpixel algorithms
  • Visual Place Recognition in Changing Environments Toolbox: ViPRICE
  • Minicolumn Networks for neurologically inspired place recognition and localization: MCN

Publications

Schubert, S., Neubert, P. & Protzel, P. (2020) Unsupervised Learning Methods for Visual Place Recognition in Discretely and Continuously Changing Environments. In Proc. of Intl. Conf. on Robotics and Automation (ICRA). DOI: 10.1109/ICRA40945.2020.9197044

Schlegel, K., Neubert, P. & Protzel, P. (2020) A comparison of Vector Symbolic Architectures. In arXiv:2001.11797

Schlegel, K., Neubert, P. & Protzel, P. (2020) Building a navigation system for a shopping assistant robot from off-the-shelf components. In Proc. of Towards Autonomous Robotic Systems Conference (TAROS). (to appear)

Yuan, F., Neubert, P. & Protzel, P. (2020) LocalSPED: A classification pipeline that can learn local features for place recognition using a small training set. In Proc. of Towards Autonomous Robotic Systems Conference (TAROS). (to appear)

Neubert, P., Schlegel, K., Schubert, S. & Protzel, P. (2020) Experiences and Open Questions on using Vector Symbolic Architectures for Mobile Robotics. In Workshop on Developments in Hyperdimensional Computing and Vector Symbolic Architectures. (to appear)

Sudharshan, V., Seidel, P., Ghamisi, P., Lorenz, S., Fuchs, M., Fareedh, J.S., Neubert, P., Schubert, S. & Gloaguen, R. (2020) Object detection routine for material streams combining RGB and hyperspectral reflectance databased on Guided Object Localization. IEEE Sensors Journal. DOI: 10.1109/JSEN.2020.2996757

Neubert, P., Schubert, S. & Protzel, P. (2019) An Introduction to Hyperdimensional Computing for Robotics. KI - Künstliche Intelligenz, Special Issue: Reintegrating Artificial Intelligence and Robotics, Vol. 33. DOI: 10.1007/s13218-019-00623-z

Neubert, P., Schubert, S. & Protzel, P. (2019) A neurologically inspired sequence processing model for mobile robot place recognition. In IEEE Robotics and Automation Letters (RA-L) and presentation at Intl. Conf. on Intelligent Robots and Systems (IROS). DOI: 10.1109/LRA.2019.2927096

Schubert, S., Neubert, P. & Protzel, P. (2019) Towards combining a neocortex model with entorhinal grid cells for mobile robot localization. In Proc. of European Conference on Mobile Robotics (ECMR). DOI: 10.1109/ECMR.2019.8870939

Schubert, S., Neubert, P., Pöschmann, J. & Protzel, P. (2019) Circular Convolutional Neural Networks for Panoramic Images and Laser Data. In Proc. of Intelligent Vehicles Symposium (IV). DOI: 10.1109/IVS.2019.8813862

Neubert, P., Ahmad, S. & Protzel, P. (2018) A Sequence-Based Neuronal Model for Mobile Robot Localization. In Proc. of German Conference on Artificial Intelligence (KI). DOI: 10.1007/978-3-030-00111-7_11

Neubert, P. & Protzel, P. (2018) Towards Hypervector Representations for Learning and Planning with Schemas. In Proc. of German Conference on Artificial Intelligence (KI)

Neubert, P., Schubert, S. & Protzel, P. (2017) Sampling-based Methods for Visual Navigation in 3D Maps by Synthesizing Depth Images. In Proc. of Intl. Conf. on Intelligent Robots and Systems (IROS). DOI: 10.1109/IROS.2017.8206067

Pöschmann, J., Neubert, P., Schubert, S. & Protzel, P. (2017) Synthesized semantic views for mobile robot localization. In Proc. of European Conf. on Mobile Robotics (ECMR). DOI: 10.1109/ECMR.2017.8098662

Schubert, S., Neubert, P. & Protzel, P. (2017) Towards camera based navigation in 3D maps by synthesizing depth images. In Proc. of Towards Autonomous Robotic Systems (TAROS). DOI: 10.1007/978-3-319-64107-2_49. Best Paper Award Winner

Krajník, T., Cristóforis, P., Kusumam, K., Neubert, P. & Duckett, T. (2016) Image features for visual teach-and-repeat navigation in changing environments. In Robotics and Autonomous Systems. DOI: 10.1016/j.robot.2016.11.011

Neubert, P., Schubert, S. & Protzel, P. (2016) Learning Vector Symbolic Architectures for Reactive Robot Behaviours. In Proc. of Intl. Conf. on Intelligent Robots and Systems (IROS) Workshop on Machine Learning Methods for High-Level Cognitive Capabilities in Robotics

Schubert, S., Lange, S., Neubert, P. & Protzel, P. (2016) Map Enhancement with Track-Loss Data in Visual SLAM. In Proc. of Intl. Conf. on Intelligent Robots and Systems (IROS) Workshop on State Estimation and Terrain Perception for All Terrain Mobile Robots

Neubert, P. & Protzel, P. (2016) Beyond Holistic Descriptors, Keypoints and Fixed Patches: Multiscale Superpixel Grids for Place Recognition in Changing Environments. In IEEE Robotics and Automation Letters and presentation at Intl. Conf. on Robotics and Automation (ICRA)

Schubert, S., Neubert, P. & Protzel, P. (2016) How to Build and Customize a High-Resolution 3D Laserscanner Using Off-the-shelf Components. In Proc. of Towards Autonomous Robotic Systems (TAROS). DOI: 10.1007/978-3-319-40379-3_33. Best Paper Award Winner


Neubert, P. & Protzel, P. (2015) Local Region Detector + CNN based Landmarks for Practical Place Recognition in Changing Environments. In Proc of. European Conf. on Mobile Robotics (ECMR)

Neubert, P. & Protzel, P. (2015) Benchmarking Superpixel Descriptors. In Proc. of European Signal Processing Conference (EUSIPCO)

Neubert, P., Schubert, S. & Protzel, P. (2015) Exploiting intra Database Similarities for Selection of Place Recognition Candidates in Changing Environments. In Proc. of. Computer Vision and Pattern Recognition (CVPR) Workshop on Visual Place Recognition in Changing Environments

Neubert, P., Sünderhauf, N. & Protzel, P. (2015) Superpixel-based appearance change prediction for long-term navigation across seasons. Robotics and Autonomous Systems, Vol. 69:15-27. DOI: 10.1016/j.robot.2014.08.005

Neubert, P. & Protzel, P. (2014) Compact Watershed and Preemptive SLIC: On improving trade-offs of superpixel segmentation algorithms. In Proc. of Intl. Conf. on Pattern Recognition (ICPR)

Sünderhauf, N., Neubert, P., Truschzinski, M., Wunschel, D., Pöschmann, J., Lange, S. & Protzel, P. (2014) Phobos and Deimos on Mars — Two Autonomous Robots for the DLR SpaceBot Cup. In Proc. of Intl. Symposium on Artificial Intelligence, Robotics and Automation in Space (iSAIRAS)

Neubert, P. & Protzel, P. (2013) Evaluating Superpixels in Video: Metrics Beyond Figure-Ground Segmentation.. In Proc. of British Machine Vision Conference (BMVC)

Neubert, P., Sünderhauf, N. & Protzel, P. (2013) Appearance Change Prediction for Long-Term Navigation Across Seasons. In Proc. of European Conference on Mobile Robotics (ECMR)

Sünderhauf, N., Neubert, P. & Protzel, P. (2013) Predicting the Change -- A Step Towards Life-Long Operation in Everyday Environments. In Proc. of Robotics: Science and Systems (RSS) Robotics Challenges and Vision Workshop. RCV 2013 3rd Best Paper Award Winner

Sünderhauf, N., Neubert, P. & Protzel, P. (2013) Are We There Yet? Challenging SeqSLAM on a 3000 km Journey Across All Four Seasons. In Proc. of Workshop on Long-Term Autonomy at Int. Conf. on Rob. a. Autom. (ICRA)

Neubert, P. & Protzel, P. (2012) Superpixel Benchmark and Comparison. In Proc. of Forum Bildverarbeitung

Neubert, P., Sünderhauf, N. & Protzel, P. (2012) From Saliency Based Image Features Towards Semantic Mapping. In Proc. of 7th German Conference on Robotics, pages 1-6

Lange, S., Sünderhauf, N., Neubert, P., Drews, S. & Protzel, P. (2011) Autonomous Corridor Flight of a UAV Using a Low-Cost and Light-Weight RGB-D Camera. In Advances in Autonomous Mini Robots - Proceedings of the 6-th AMiRE Symposium, pages 183-192. ISBN: 978-3-642-27481-7. DOI: 10.1007/978-3-642-27482-4_19

Sünderhauf, N., Neubert, P. & Protzel, P. (2010) The Causal Update Filter -- A Novel Biologically Inspired Filter Paradigm for Appearance Based SLAM. In Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS). DOI: 10.1109/IROS.2010.5653221

Peer, N., Vidal-Calleja, T., Lacroi, S. & Protzel, P. (2008) A Fast Visual Line Segment Tracker. In Proc. of 13th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

Neubert, P., Sünderhauf, N. & Protzel, P. (2007) FastSLAM using SURF Features: An Efficient Implementation and Practical Experiences. In Proceedings of the International Conference on Intelligent and Autonomous Vehicles, IAV07