Zobrazeno 1 - 10
of 25 740
pro vyhledávání: '"Safe learning"'
Autor:
Liu, Puze, Günster, Jonas, Funk, Niklas, Gröger, Simon, Chen, Dong, Bou-Ammar, Haitham, Jankowski, Julius, Marić, Ante, Calinon, Sylvain, Orsula, Andrej, Olivares-Mendez, Miguel, Zhou, Hongyi, Lioutikov, Rudolf, Neumann, Gerhard, Zhalehmehrabi, Amarildo Likmeta Amirhossein, Bonenfant, Thomas, Restelli, Marcello, Tateo, Davide, Liu, Ziyuan, Peters, Jan
Machine learning methods have a groundbreaking impact in many application domains, but their application on real robotic platforms is still limited. Despite the many challenges associated with combining machine learning technology with robotics, robo
Externí odkaz:
http://arxiv.org/abs/2411.05718
Autor:
Hirt, Sebastian, Höhl, Andreas, Pohlodek, Johannes, Schaeffer, Joachim, Pfefferkorn, Maik, Braatz, Richard D., Findeisen, Rolf
Model predictive control (MPC) is a powerful tool for controlling complex nonlinear systems under constraints, but often struggles with model uncertainties and the design of suitable cost functions. To address these challenges, we discuss an approach
Externí odkaz:
http://arxiv.org/abs/2410.04982
Autor:
Pua, Xun, Khadiv, Majid
Safe learning of locomotion skills is still an open problem. Indeed, the intrinsically unstable nature of the open-loop dynamics of locomotion systems renders naive learning from scratch prone to catastrophic failures in the real world. In this work,
Externí odkaz:
http://arxiv.org/abs/2407.11673
We present a hierarchical architecture to improve the efficiency of event-triggered control (ETC) in reducing resource consumption. This paper considers event-triggered systems generally as an impulsive control system in which the objective is to min
Externí odkaz:
http://arxiv.org/abs/2409.09812
Powerful domain-independent planners have been developed to solve various types of planning problems. These planners often require a model of the acting agent's actions, given in some planning domain description language. Manually designing such an a
Externí odkaz:
http://arxiv.org/abs/2403.15251
Legged robots navigating cluttered environments must be jointly agile for efficient task execution and safe to avoid collisions with obstacles or humans. Existing studies either develop conservative controllers (< 1.0 m/s) to ensure safety, or focus
Externí odkaz:
http://arxiv.org/abs/2401.17583
Autor:
Zagorowska, Marta, König, Christopher, Yu, Hanlin, Balta, Efe C., Rupenyan, Alisa, Lygeros, John
Optimization-based controller tuning is challenging because it requires formulating optimization problems explicitly as functions of controller parameters. Safe learning algorithms overcome the challenge by creating surrogate models from measured dat
Externí odkaz:
http://arxiv.org/abs/2310.17431
Publikováno v:
African Journal of Health Professions Education. Jun2024, Vol. 16 Issue 2, p2-6. 5p.
This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the