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Emperical Interference

Haptic Intelligence

Modern Magnetic Systems

Perceiving Systems

Physical Intelligence

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Social Foundations of Computation

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Autonomous Vision

Autonomous Learning

Bioinspired Autonomous Miniature Robots

Dynamic Locomotion

Embodied Vision

Human Aspects of Machine Learning

Intelligent Control Systems

Learning and Dynamical Systems

Locomotion in Biorobotic and Somatic Systems

Micro, Nano, and Molecular Systems

Movement Generation and Control

Neural Capture and Synthesis

Physics for Inference and Optimization

Organizational Leadership and Diversity

Probabilistic Learning Group

Topics

Robot Learning

Conference Paper

2022

Autonomous Learning

Robotics

AI

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Embodied Vision Article Visual-Inertial Odometry with Online Calibration of Velocity-Control Based Kinematic Motion Models Li, H., Stueckler, J. IEEE Robotics and Automation Letters, 7(3):6415-6422, July 2022, Accepted for oral presentation at IEEE ICRA 2023 (Published) preprint DOI URL BibTeX
Embodied Vision Article Weakly Supervised Learning of Multi-Object 3D Scene Decompositions Using Deep Shape Priors Elich, C., Oswald, M. R., Pollefeys, M., Stueckler, J. Computer Vision and Image Understanding (CVIU), 220, July 2022 (Published) Link Preprint DOI URL BibTeX
Embodied Vision Conference Paper Event-based Non-Rigid Reconstruction from Contours Xue, Y., Li, H., Leutenegger, S., Stueckler, J. In Proceedings of the British Machine Vision Conference (BMVC), 2022 (Published) preprint video URL BibTeX
Embodied Vision Conference Paper Learning Temporally Extended Skills in Continuous Domains as Symbolic Actions for Planning Achterhold, J., Krimmel, M., Stueckler, J. In Proceedings of the 6th Conference on Robot Learning (CoRL), 205:225-236 , Proceedings of Machine Learning Research , 6th Annual Conference on Robot Learning (CoRL 2022) , 2022 (Published) preprint project website URL BibTeX
Embodied Vision Technical Report Observability Analysis of Visual-Inertial Odometry with Online Calibration of Velocity-Control Based Kinematic Motion Models Li, H., Stueckler, J. abs/2204.06651, CoRR/arxiv, 2022 (Published) URL BibTeX