Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Changliu Liu"'
Publikováno v:
IEEE Control Systems Letters. 7:1213-1218
Model mismatches prevail in real-world applications. Ensuring safety for systems with uncertain dynamic models is critical. However, existing robust safe controllers may not be realizable when control limits exist. And existing methods use loose over
Publikováno v:
IEEE Robotics and Automation Letters. 7:10248-10255
Planning under social interactions with other agents is an essential problem for autonomous driving. As the actions of the autonomous vehicle in the interactions affect and are also affected by other agents, autonomous vehicles need to efficiently in
This paper studies real-time collaborative robot (cobot) handling, where the cobot maneuvers an object under human dynamic gesture commands. Enabling dynamic gesture commands is useful when the human needs to avoid direct contact with the robot or th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d28db30951e810cd3025ef5ba02ae308
http://arxiv.org/abs/2304.06175
http://arxiv.org/abs/2304.06175
Autor:
Hongyi Chen, Changliu Liu
This study proposes a safe and sample-efficient reinforcement learning (RL) framework to address two major challenges in developing applicable RL algorithms: satisfying safety constraints and efficiently learning with limited samples. To guarantee sa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fde60f6f75b0a322136c5fb606d7e9f5
http://arxiv.org/abs/2303.14265
http://arxiv.org/abs/2303.14265
Publikováno v:
IFAC-PapersOnLine. 55:167-174
Publikováno v:
IEEE Control Systems Letters. 6:3439-3444
Tolerance estimation problems are prevailing in engineering applications. For example, in modern robotics, it remains challenging to efficiently estimate joint tolerance, \ie the maximal allowable deviation from a reference robot state such that safe
Autor:
Ruixuan Liu, Changliu Liu
Publikováno v:
ACC
Human motion prediction, especially arm prediction, is critical to facilitate safe and efficient human-robot collaboration (HRC). This letter proposes a novel human motion prediction framework that combines a recurrent neural network (RNN) and invers
Publikováno v:
IFAC-PapersOnLine. 54:346-353
Autor:
Changliu Liu, Abulikemu Abuduweili
Publikováno v:
International Journal of Adaptive Control and Signal Processing. 35:314-341
Publikováno v:
IEEE Robotics and Automation Letters. 5:2602-2609
Human-robot collaboration (HRC) is becoming increasingly important as the paradigm of manufacturing is shifting from mass production to mass customization. The introduction of HRC can significantly improve the flexibility and intelligence of automati