Erik Schaffernicht

Erik Schaffernicht
  • 2012 – now: Postdoc in the MRO Lab at the AASS Research Center
  • 2006 – 2012: Researcher and PhD student in the Neuroinformatics and Cognitive Robotics Lab at Ilmenau University of Technology, Germany
  • 2006: Software developer for robotics with Metralabs, Germany
  • 2003 – 2004: Internship at the DaimlerChrysler research center in Ulm
  • 2000 – 2006: Diploma student at Ilmenau University of Technology in computer science

 

Research Interests

SmokeBot in the training facilities of the Dortmund firebrigade.

Apparently, I like to play with [robots close to] fire.

I am interested applications of machine learning techniques both in context of robotics and intelligent control. Currently my research revolves around robot with monitoring or exploration tasks in harsh environments, e.g. for occupational health monitoring in steel foundries, for the detection of gas leaks or for scouting disaster sites in the presence of heavy smoke. Previously, I have been working a lot with learning systems to control combustion processes in coal-fired power plants.

Our Husky operating in a foundry.

One a more theoretical side, I am interested in feature selection techniques, information-theoretic learning, reinforcement learning, sensor planning for mobile robots, spatio-temporal interpolation methods for environmental mapping and people tracking.

I am working as scientific manager in the SmokeBot H2020 project, enabling robots to operate in low visibility scenarios and have been the project leader of RAISE, developing a robot- assisted occupational health monitoring system for foundries.

 

Contact

Dr. Erik Schaffernicht

AASS Research Centre
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Room T1211
Phone +46 (0)19 30 32 27
erik.schaffernicht@oru.se

Publications

Journal Articles

[1] S. Gugliermo, D. C. Dominguez, M. Iannotta, T. Stoyanov and E. Schaffernicht. Evaluating behavior trees. Robotics and Autonomous Systems, 178, 2024 [ BibTeX | DiVA  ]
[2] N. P. Winkler, O. Kotlyar, E. Schaffernicht, H. Matsukura, H. Ishida, P. P. Neumann and A. J. Lilienthal. Super-resolution for Gas Distribution Mapping. Sensors and actuators. B, Chemical, 419, 2024 [ BibTeX | DiVA  ]
[3] S. Gugliermo, E. Schaffernicht, C. Koniaris and F. Pecora. Learning Behavior Trees From Planning Experts Using Decision Tree and Logic Factorization. IEEE Robotics and Automation Letters, 8(6):3534-3541, 2023 [ BibTeX | DiVA  ]
[4] T. P. Kucner, M. Magnusson, S. Mghames, L. Palmieri, F. Verdoja, C. S. Swaminathan, T. Krajnik, E. Schaffernicht, N. Bellotto, M. Hanheide and A. J. Lilienthal. Survey of maps of dynamics for mobile robots. The international journal of robotics research, 42(11):977-1006, 2023 [ BibTeX | DiVA  ]
[5] E. Gutiérrez Maestro, T. R. d. Almeida, E. Schaffernicht and O. Martinez Mozos. Wearable-Based Intelligent Emotion Monitoring in Older Adults during Daily Life Activities. Applied Sciences, 13(9), 2023 [ BibTeX | DiVA  ]
[6] D. C. Dominguez, M. Iannotta, J. A. Stork, E. Schaffernicht and T. Stoyanov. A Stack-of-Tasks Approach Combined With Behavior Trees : A New Framework for Robot Control. IEEE Robotics and Automation Letters, 7(4):12110-12117, 2022 [ BibTeX | DiVA  ]
[7] H. Fan, E. Schaffernicht and A. Lilienthal. Ensemble Learning-Based Approach for Gas Detection Using an Electronic Nose in Robotic Applications. Frontiers in Chemistry, 10, 2022 [ BibTeX | DiVA  | PDF ]
[8] M. Schindler, J. H. Doderer, A. L. Simon, E. Schaffernicht, A. J. Lilienthal and K. Schäfer. Small number enumeration processes of deaf or hard-of-hearing students : A study using eye tracking and artificial intelligence. Frontiers in Psychology, 13, 2022 [ BibTeX | DiVA  ]
[9] M. A. Arain, V. Hernandez Bennetts, E. Schaffernicht and A. Lilienthal. Sniffing out fugitive methane emissions : autonomous remote gas inspection with a mobile robot. The international journal of robotics research, 40(4-5):782-814, 2021 [ BibTeX | DiVA  ]
[10] Y. Xing, T. A. Vincent, H. Fan, E. Schaffernicht, V. Hernandez Bennetts, A. J. Lilienthal, M. Cole and J. W. Gardner. FireNose on Mobile Robot in Harsh Environments. IEEE Sensors Journal, 19(24):12418-12431, 2019 [ BibTeX | DiVA  ]
[11] H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. J. Lilienthal. Towards Gas Discrimination and Mapping in Emergency Response Scenarios Using a Mobile Robot with an Electronic Nose. Sensors, 19(3), 2019 [ BibTeX | DiVA  | PDF ]
[12] H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. Lilienthal. A cluster analysis approach based on exploiting density peaks for gas discrimination with electronic noses in open environments. Sensors and actuators. B, Chemical, 259:183-203, 2018 [ BibTeX | DiVA  | PDF ]
[13] H. Banaee, E. Schaffernicht and A. Loutfi. Data-Driven Conceptual Spaces : Creating Semantic Representations for Linguistic Descriptions of Numerical Data. The journal of artificial intelligence research, 63:691-742, 2018 [ BibTeX | DiVA  | PDF ]
[14] D. R. Canelhas, E. Schaffernicht, T. Stoyanov, A. Lilienthal and A. J. Davison. Compressed Voxel-Based Mapping Using Unsupervised Learning. Robotics, 6(3), 2017 [ BibTeX | DiVA  ]
[15] T. P. Kucner, M. Magnusson, E. Schaffernicht, V. M. Hernandez Bennetts and A. J. Lilienthal. Enabling Flow Awareness for Mobile Robots in Partially Observable Environments. IEEE Robotics and Automation Letters, 2(2):1093-1100, 2017 [ BibTeX | DiVA  | PDF ]
[16] V. Hernandez Bennetts, T. P. Kucner, E. Schaffernicht, P. P. Neumann, H. Fan and A. J. Lilienthal. Probabilistic Air Flow Modelling Using Turbulent and Laminar Characteristics for Ground and Aerial Robots. IEEE Robotics and Automation Letters, 2(2):1117-1123, 2017 [ BibTeX | DiVA  ]
[17] Y. Zhang, M. Gulliksson, V. Hernandez Bennetts and E. Schaffernicht. Reconstructing gas distribution maps via an adaptive sparse regularization algorithm. Inverse Problems in Science and Engineering, 24(7):1186-1204, 2016 [ BibTeX | DiVA  ]
[18] M. A. Arain, M. Trincavelli, M. Cirillo, E. Schaffernicht and A. J. Lilienthal. Global coverage measurement planning strategies for mobile robots equipped with a remote gas sensor. Sensors, 15(3):6845-6871, 2015 [ BibTeX | DiVA  | PDF ]
[19] R. Mojtahedzadeh, A. Bouguerra, E. Schaffernicht and A. J. Lilienthal. Support relation analysis and decision making for safe robotic manipulation tasks. Robotics and Autonomous Systems, 71(SI):99-117, 2015 [ BibTeX | DiVA  ]
[20] E. Schaffernicht, M. Trincavelli and A. J. Lilienthal. Bayesian Spatial Event Distribution Grid Maps for Modeling the Spatial Distribution of Gas Detection Events. Sensor Letters, 12(6-7):1142-1146, 2014 [ BibTeX | DiVA  ]
[21] V. Hernandez Bennetts, E. Schaffernicht, V. Pomadera Sese, A. J. Lilienthal, S. Marco and M. Trincavelli. Combining Non Selective Gas Sensors on a Mobile Robot for Identification and Mapping of Multiple Chemical Compounds. Sensors, 14(9):17331-17352, 2014 [ BibTeX | DiVA  ]
[22] V. Hernandez Bennetts, M. Trincavelli, A. J. Lilienthal and E. Schaffernicht. Online parameter selection for gas distribution mapping. Sensor Letters, 12(6-7):1147-1151, 2014 [ BibTeX | DiVA  ]
[23] S. Pashami, A. J. Lilienthal, E. Schaffernicht and M. Trincavelli. rTREFEX: Reweighting norms for detecting changes in the response of MOX gas sensors. Sensor Letters, 12(6/7):1123-1127, 2014 [ BibTeX | DiVA  ]
[24] S. Pashami, A. J. Lilienthal, E. Schaffernicht and M. Trincavelli. TREFEX : trend estimation and change detection in the response of mox gas sensors. Sensors, 13(6):7323-7344, 2013 [ BibTeX | DiVA  | PDF ]
[25] J. Funkquist, V. Stephan, E. Schaffernicht, C. Rosner and M. Berg. SOFCOM -- Self-Optimising Strategy for Control of the Combustion Process. VGB PowerTech Journal (VGB), 3:48-54, 2011 [ BibTeX ]
[26] C. Rosner, H. Roepell, F. Wintrich, V. Stephan and E. Schaffernicht. Wirkungsgradverbesserung an steinkohlebefeuerten Dampferzeugern mittels lernfaehiger, videogestuetzter Lufverteilungsoptimierung. VGB PowerTech Journal (VGB), 12:94-99, 2008 [ BibTeX ]
[27] C. Martin, E. Schaffernicht, A. Scheidig and H. M. Gross. Multi-Modal Sensor Fusion Using a Probabilistic Aggregation Scheme for People Detection and Tracking. Robotics and Autonomous Systems (RAS), 54(9):721-728, 2006 [ BibTeX ]

Book Chapters

[1] H. Ishida, A. J. Lilienthal, H. Matsukura, V. Hernandez Bennetts and E. Schaffernicht. Using Chemical Sensors as 'Noses' for Mobile Robots. In Essentials of Machine Olfaction and Taste, pages 219-246, 2016 [ BibTeX | DiVA  ]

Refereed Conference and Workshop Articles

[1] N. P. Winkler, P. P. Neumann, E. Schaffernicht and A. J. Lilienthal. Gas Distribution Mapping With Radius-Based, Bi-directional Graph Neural Networks (RABI-GNN). In 2024 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) 2024 [ BibTeX | DiVA  ]
[2] H. Fan, E. Schaffernicht and A. J. Lilienthal. Identification of Gas Mixtures with Few Labels Using Graph Convolutional Networks. In 2024 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) 2024 [ BibTeX | DiVA  ]
[3] S. Gugliermo, E. Schaffernicht, C. Koniaris and A. Saffiotti. Extracting Planning Domains from Execution Traces : a Progress Report. 2023 [ BibTeX | DiVA  | PDF ]
[4] N. P. Winkler, P. P. Neumann, E. Schaffernicht, A. Lilienthal, M. Poikkimäki, A. Kangas and A. Säämänen. Gather Dust and Get Dusted : Long-Term Drift and Cleaning of Sharp GP2Y1010AU0F Dust Sensor in a Steel Factory. 2022 [ BibTeX | DiVA  | PDF ]
[5] M. Iannotta, D. C. Dominguez, J. A. Stork, E. Schaffernicht and T. Stoyanov. Heterogeneous Full-body Control of a Mobile Manipulator with Behavior Trees. In IROS 2022 Workshop on Mobile Manipulation and Embodied Intelligence (MOMA): Challenges and  Opportunities 2022 [ BibTeX | DiVA  | PDF ]
[6] N. P. Winkler, O. Kotlyar, E. Schaffernicht, H. Fan, H. Matsukura, H. Ishida, P. P. Neumann and A. Lilienthal. Learning From the Past : Sequential Deep Learning for Gas Distribution Mapping. In ROBOT2022 : Fifth Iberian Robotics Conference: Advances in Robotics, Volume 2, 590(590):178-188, 2022 [ BibTeX | DiVA  ]
[7] N. P. Winkler, H. Matsukura, P. P. Neumann, E. Schaffernicht, H. Ishida and A. J. Lilienthal. Super-Resolution for Gas Distribution Mapping : Convolutional Encoder-Decoder Network. In 2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) 2022 [ BibTeX | DiVA  ]
[8] H. Fan, D. Jonsson, E. Schaffernicht and A. Lilienthal. Towards Gas Identification in Unknown Mixtures Using an Electronic Nose with One-Class Learning. In 2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) : Proceedings 2022 [ BibTeX | DiVA  ]
[9] F. Rietz, E. Schaffernicht, T. Stoyanov and J. A. Stork. Towards Task-Prioritized Policy Composition. 2022 [ BibTeX | DiVA  ]
[10] N. P. Winkler, P. P. Neumann, H. Kohlhoff, J. Erdmann, E. Schaffernicht and A. Lilienthal. Development of a Low-Cost Sensing Node with Active Ventilation Fan for Air Pollution Monitoring. In SMSI 2021 Proceedings, pages 260-261, 2021 [ BibTeX | DiVA  | PDF ]
[11] N. P. Winkler, P. P. Neumann, E. Schaffernicht and A. Lilienthal. Using Redundancy in a Sensor Network to Compensate Sensor Failures. In 2021 IEEE SENSORS 2021 [ BibTeX | DiVA  ]
[12] N. P. Winkler, P. P. Neumann, E. Schaffernicht and A. J. Lilienthal. Using Redundancy in a Sensor Network to Compensate Sensor Failures. In 2021 IEEE SENSORS 2021 [ BibTeX | DiVA  ]
[13] N. P. Winkler, P. P. Neumann, A. Säämänen, E. Schaffernicht and A. J. Lilienthal. High-quality meets low-cost : Approaches for hybrid-mobility sensor networks. In MATERIALS TODAY-PROCEEDINGS, 32:250-253, 2020 [ BibTeX | DiVA  ]
[14] M. Schindler, E. Schaffernicht and A. Lilienthal. Identifying student strategies through eye tracking and unsupervised learning : The case of quantity recognition. In Interim Proceedings of the 44th Conference of the International Group for the Psychology of Mathematics Education. Khon Kaen, Thailand: PME, pages 518-527, 2020 [ BibTeX | DiVA  | PDF ]
[15] M. Schindler, E. Schaffernicht and A. J. Lilienthal. Differences in Quantity Recognition Between Students with and without Mathematical Difficulties Analyzed Through Eye : Analysis Through Eye-Tracking and AI. In Proceedings of the 43rd Conference of the International Group for the Psychology of Mathematics Education, 3:281-288, 2019 [ BibTeX | DiVA  | PDF ]
[16] H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. J. Lilienthal. Semi-supervised Gas Detection Using an Ensemble of One-class Classifiers. In 18th ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) 2019 [ BibTeX | DiVA  | PDF ]
[17] J. Lundell, R. Krug, E. Schaffernicht, T. Stoyanov and V. Kyrki. Safe-To-Explore State Spaces : Ensuring Safe Exploration in Policy Search with Hierarchical Task Optimization. In IEEE-RAS Conference on Humanoid Robots, pages 132-138, 2018 [ BibTeX | DiVA  ]
[18] T. Wiedemann, D. Shutin, V. Hernandez Bennetts, E. Schaffernicht and A. Lilienthal. Bayesian Gas Source Localization and Exploration with a Multi-Robot System Using Partial Differential Equation Based Modeling. In 2017 ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN 2017) : Proceedings, pages 122-124, 2017 [ BibTeX | DiVA  ]
[19] M. Vuka, E. Schaffernicht, M. Schmuker, V. Hernandez Bennetts, F. Amigoni and A. J. Lilienthal. Exploration and Localization of a Gas Source with MOX Gas Sensorson a Mobile Robot : A Gaussian Regression Bout Amplitude Approach. In 2017 ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN 2017) : Proceedings, pages 164-166, 2017 [ BibTeX | DiVA  ]
[20] H. Fan, M. A. Arain, V. Hernandez Bennetts, E. Schaffernicht and A. J. Lilienthal. Improving Gas Dispersal Simulation For Mobile Robot Olfaction : Using Robot-Created Occupancy Maps And Remote Gas Sensors In The Simulation Loop. In 2017 ISOCS/IEEE International Symposium on Olfaction andElectronic Nose (ISOEN 2017) Proceedings 2017 [ BibTeX | DiVA  ]
[21] M. A. Arain, H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. J. Lilienthal. Improving Gas Tomography With Mobile Robots : An Evaluation of Sensing Geometries in Complex Environments. In 2017 ISOCS/IEEE International Symposium on Olfaction andElectronic Nose (ISOEN 2017) Proceedings 2017 [ BibTeX | DiVA  ]
[22] Y. Xing, T. A. Vincent, M. Cole, J. W. Gardner, H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. Lilienthal. Mobile robot multi-sensor unit for unsupervised gas discrimination in uncontrolled environments. In IEEE SENSORS 2017 : Conference Proceedings, pages 1691-1693, 2017 [ BibTeX | DiVA  | PDF ]
[23] E. Schaffernicht, V. Hernandez Bennetts and A. Lilienthal. Mobile robots for learning spatio-temporal interpolation models in sensor networks - The Echo State map approach : The Echo State map approach. In 2017 IEEE International Conference on Robotics and Automation (ICRA), pages 2659-2665, 2017 [ BibTeX | DiVA  | PDF ]
[24] R. Mosberger, E. Schaffernicht, H. Andreasson and A. J. Lilienthal. Inferring human body posture information from reflective patterns of protective work garments. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4131-4136, 2016 [ BibTeX | DiVA  | PDF ]
[25] T. Kucner, M. Magnusson, E. Schaffernicht, V. Hernandez Bennetts and A. Lilienthal. Tell me about dynamics! : Mapping velocity fields from sparse samples with Semi-Wrapped Gaussian Mixture Models. In Robotics : Science and Systems Conference (RSS 2016) 2016 [ BibTeX | DiVA  | PDF ]
[26] M. A. Arain, E. Schaffernicht, V. Hernandez Bennetts and A. J. Lilienthal. The Right Direction to Smell : Efficient Sensor Planning Strategies for Robot Assisted Gas Tomography. In 2016 IEEE International Conference on Robotics and Automation (ICRA), pages 4275-4281, 2016 [ BibTeX | DiVA  | PDF ]
[27] V. Hernandez Bennetts, E. Schaffernicht, A. J. Lilienthal, H. Fan, T. P. Kucner, L. Andersson and A. Johansson. Towards occupational health improvement in foundries through dense dust and pollution monitoring using a complementary approach with mobile and stationary sensing nodes. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 131-136, 2016 [ BibTeX | DiVA  ]
[28] H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. J. Lilienthal. Unsupervised gas discrimination in uncontrolled environments by exploiting density peaks. In 2016 IEEE SENSORS 2016 [ BibTeX | DiVA  ]
[29] A. Khaliq, S. Pashami, E. Schaffernicht, A. J. Lilienthal and V. Hernandez Bennetts. Bringing Artificial Olfaction and Mobile Robotics Closer Together : An Integrated 3D Gas Dispersion Simulator in ROS. In Proceedings of the 16th International Symposium on Olfaction and Electronic Noses 2015 [ BibTeX | DiVA  ]
[30] M. A. Arain, M. Cirillo, V. Hernandez Bennetts, E. Schaffernicht, M. Trincavelli and A. J. Lilienthal. Efficient Measurement Planning for Remote Gas Sensing with Mobile Robots. In 2015 IEEE International Conference on Robotics and Automation (ICRA), pages 3428-3434, 2015 [ BibTeX | DiVA  | PDF ]
[31] V. Hernandez Bennetts, A. J. Lilienthal, E. Schaffernicht, S. Ferrari and J. Albertson. Integrated Simulation of Gas Dispersion and Mobile Sensing Systems. In Workshop on Realistic, Rapid and Repeatable Robot Simulation 2015 [ BibTeX | DiVA  ]
[32] V. Hernandez Bennetts, E. Schaffernicht, V. Pomadera Sese, A. J. Lilienthal and M. Trincavelli. A Novel Approach for Gas Discrimination in Natural Environments with Open Sampling Systems. In Proceedings of the IEEE Sensors Conference 2014 2014 [ BibTeX | DiVA  ]
[33] R. Mojtahedzadeh, A. Bouguerra, E. Schaffernicht and A. J. Lilienthal. Probabilistic Relational Scene Representation and Decision Making Under Incomplete Information for Robotic Manipulation Tasks. In Robotics and Automation (ICRA), 2014 IEEE International Conference on, pages 5685-5690, 2014 [ BibTeX | DiVA  ]
[34] V. H. Bennetts, E. Schaffernicht, T. Stoyanov, A. J. Lilienthal and M. Trincavelli. Robot Assisted Gas Tomography - Localizing Methane Leaks in Outdoor Environments. In 2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), pages 6362-6367, 2014 [ BibTeX | DiVA  ]
[35] V. Hernandez Bennetts, E. Schaffernicht, T. Stoyanov, A. J. Lilienthal and M. Trincavelli. Robot assisted gas tomography : an alternative approach for the detection of fugitive methane emissions. In Workshop on Robot Monitoring 2014 [ BibTeX | DiVA  ]
[36] R. Kaltenhaeuser, E. Schaffernicht, F. F. Steege and H. M. Gross. Evolutionary computation based system decomposition with neural networks. In ESANN 2013 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligenceand Machine Learning, pages 191-196, 2013 [ BibTeX | DiVA  ]
[37] A. J. Lilienthal, M. Trincavelli and E. Schaffernicht. It's always smelly around here! Modeling the Spatial Distribution of Gas Detection Events with BASED Grid Maps. In Proceedings of the 15th International Symposium on Olfaction and Electronic Nose (ISOEN 2013) 2013 [ BibTeX | DiVA  ]
[38] V. Hernandez Bennetts, M. Trincavelli, A. J. Lilienthal, V. Pomadera Sese and E. Schaffernicht. Online parameter selection for gas distribution mapping. In Proceedings of the ISOEN conference 2013 2013 [ BibTeX | DiVA  ]
[39] E. Schaffernicht and H. M. Gross. Weighted Mutual Information for Feature Selection. In Int. Conf. on Artificial Neural Networks (ICANN), 6792(2):181-188, 2011 [ BibTeX ]
[40] F. F. Steege, A. Hartmann, E. Schaffernicht and H. M. Gross. Reinforcement Learning Based Neural Controllers for Dynamic Processes without Exploration. In Int. Conf. on Artificial Neural Networks (ICANN), 6353(2):222-227, 2010 [ BibTeX ]
[41] E. Schaffernicht, R. Kaltenhaeuser, S. S. Verma and H. M. Gross. On Estimating Mutual Information for Feature Selection. In Int. Conf. on Artificial Neural Networks (ICANN), 6352(1):362-367, 2010 [ BibTeX ]
[42] C. Vollmer, E. Schaffernicht and H. M. Gross. Exploring Continuous Action Spaces with Diffusion Trees for Reinforcement Learning. In Int. Conf. on Artificial Neural Networks (ICANN), 6353(2):190-199, 2010 [ BibTeX ]
[43] E. Schaffernicht, C. Moeller, K. Debes and H. M. Gross. Forward Feature Selection Using Residual Mutual Information. In Europ. Symp. on Artificial Neural Networks, Computational Intelligence and Learning (ESANN), pages 583-588, 2009 [ BibTeX ]
[44] E. Schaffernicht, V. Stephan and H. M. Gross. Adaptive Feature Transformation for Image Data from Non-Stationary Processes. In Int. Conf. on Artificial Neural Networks (ICANN), 5769(2):735-744, 2009 [ BibTeX ]
[45] E. Schaffernicht, V. Stephan, K. Debes and H. M. Gross. Machine Learning Techniques for Selforganizing Combustion Control. In German Conf. on Artificial Intelligence (KI), 5803:395-402, 2009 [ BibTeX ]
[46] S. Mueller, S. Hellbach, E. Schaffernicht, A. Ober, A. Scheidig and H. M. Gross. Whom to Talk to? Estimating User Interest from Movement Trajectories. In IEEE Int. Symp. on Robot and Human Interactive Communication (RO-MAN), pages 532-538, 2008 [ BibTeX ]
[47] S. Mueller, E. Schaffernicht, A. Scheidig, H. J. Boehme and H. M. Gross. Are You Still Following Me?. In Europ. Conf. on Mobile Robots (ECMR), pages 211-216, 2007 [ BibTeX ]
[48] E. Schaffernicht, V. Stephan and H. M. Gross. An Efficient Search Strategy for Feature Selection Using Chow-Liu Trees. In Int. Conf. on Artificial Neural Networks (ICANN), 4669(2):190-199, 2007 [ BibTeX ]
[49] C. Martin, E. Schaffernicht, A. Scheidig and H. M. Gross. Sensor Fusion Using a Probabilistic Aggregation Scheme for People Detection and Tracking. In Europ. Conf. on Mobile Robots (ECMR), pages 176-181, 2005 [ BibTeX ]
[50] E. Schaffernicht, C. Martin, A. Scheidig and H. M. Gross. A Probabilistic Multimodal Sensor Aggregation Scheme Applied for a Mobile Robot. In German Conf. on Artificial Intelligence (KI), 3698:320-334, 2005 [ BibTeX ]

Theses

[1] E. Schaffernicht. Lernbeiträge im Rahmen einer kognitiven Architektur zur intelligenten Prozessführung. Ilmenau University of Technology, Germany, Doctoral Thesis, 2012 [ BibTeX | PDF ]
[2] E. Schaffernicht. Teilautonomer Serviceroboter für den interaktiven Outdoor-Einsatz auf bevölkertem Campusgelände. Ilmenau University of Technology, Germany, Diploma Thesis, 2006 [ BibTeX ]

Find the complete BibTeX record here.

 
clear