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pro vyhledávání: '"Seel A"'
Autor:
Bank, Dennis, Ehlers, Simon F. G., Kortmann, Karl-Philipp, Zeller, Tobias, Cujic, Patrick, Seel, Thomas
Refrigerated truck trailers are currently mainly operated with environmentally harmful diesel units; an alternative is to operate the refrigeration unit with electrical energy. However, this requires a battery, the size of which can be reduced by usi
Externí odkaz:
http://arxiv.org/abs/2409.10414
Intelligent real-world systems critically depend on expressive information about their system state and changing operation conditions, e.g., due to variation in temperature, location, wear, or aging. To provide this information, online inference and
Externí odkaz:
http://arxiv.org/abs/2409.09331
Stem cell therapy is a promising approach to treat heart insufficiency and benefits from automated myocardial injection which requires highly precise motion of a robotic manipulator that is equipped with a syringe. This work investigates whether suff
Externí odkaz:
http://arxiv.org/abs/2409.06361
In this paper, we extend the Recurrent Inertial Graph-based Estimator (RING), a novel neural-network-based solution for Inertial Motion Tracking (IMT), to generalize across a large range of sampling rates, and we demonstrate that it can overcome four
Externí odkaz:
http://arxiv.org/abs/2409.02502
Parallel robots (PR) offer potential for human-robot collaboration (HRC) due to their lower moving masses and higher speeds. However, the parallel leg chains increase the risks of collision and clamping. In this work, these hazards are described by k
Externí odkaz:
http://arxiv.org/abs/2408.15831
Physics-informed neural networks (PINNs) are trained using physical equations and can also incorporate unmodeled effects by learning from data. PINNs for control (PINCs) of dynamical systems are gaining interest due to their prediction speed compared
Externí odkaz:
http://arxiv.org/abs/2408.14951
Many application domains, e.g., in medicine and manufacturing, can greatly benefit from pneumatic Soft Robots (SRs). However, the accurate control of SRs has remained a significant challenge to date, mainly due to their nonlinear dynamics and viscoel
Externí odkaz:
http://arxiv.org/abs/2408.03754
Advanced driver assistance systems are critically dependent on reliable and accurate information regarding a vehicles' driving state. For estimation of unknown quantities, model-based and learning-based methods exist, but both suffer from individual
Externí odkaz:
http://arxiv.org/abs/2406.14028
Autor:
Habich, Tim-Lukas, Haack, Jonas, Belhadj, Mehdi, Lehmann, Dustin, Seel, Thomas, Schappler, Moritz
Soft-robot designs are manifold, but only a few are publicly available. Often, these are only briefly described in their publications. This complicates reproduction, and hinders the reproducibility and comparability of research results. If the design
Externí odkaz:
http://arxiv.org/abs/2404.10734
Publikováno v:
Control Engineering Practice, Volume 145, April 2024, 105879
This work proposes Autonomous Iterative Motion Learning (AI-MOLE), a method that enables systems with unknown, nonlinear dynamics to autonomously learn to solve reference tracking tasks. The method iteratively applies an input trajectory to the unkno
Externí odkaz:
http://arxiv.org/abs/2404.06179