Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Chonhyon Park"'
Publikováno v:
The International Journal of Robotics Research. 38:23-39
We present a motion planning algorithm to compute collision-free and smooth trajectories for high-degree-of-freedom (high-DOF) robots interacting with humans in a shared workspace. Our approach uses offline learning of human actions along with tempor
Publikováno v:
Springer Proceedings in Advanced Robotics ISBN: 9783030430887
WAFR
WAFR
We present a novel approach to performing probabilistic collision detection between a high-DOF robot and imperfect obstacle representations in dynamic, uncertain environments. These uncertainties are modeled using Gaussian distributions. We present a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9e4c5c930ca42421f2099b2f3952252e
https://doi.org/10.1007/978-3-030-43089-4_38
https://doi.org/10.1007/978-3-030-43089-4_38
Publikováno v:
IEEE Transactions on Automation Science and Engineering. 15:980-991
We present a novel approach to perform probabilistic collision detection between a high-DOF robot and imperfect obstacle representations in dynamic and uncertain environments. Our formulation is designed for high-DOF robot trajectory planning in dyna
Publikováno v:
IEEE Transactions on Robotics. 33:359-371
We present a rapidly exploring-random-tree-based parallel motion planning algorithm that uses the maximal Poisson-disk sampling scheme. Our approach exploits the free-disk property of the maximal Poisson-disk samples to generate nodes and perform tre
Autor:
Douglas W. Arner, Chonhyon Park, Anton N. Didenko, E Pashoska, Ross P. Buckley, Bo Zhao, Dirk Andreas Zetzsche
This report offers an analytical framework that allows for more systemic assessments of distributed ledger technology (DLT) and its applications. It examines the evolution and typology of the emergent technology, its existing and projected applicatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::818cb6bf619fe577b3e13ca25bf6020c
https://doi.org/10.22617/tcs190205-2
https://doi.org/10.22617/tcs190205-2
Publikováno v:
Proceedings of the International Conference on Automated Planning and Scheduling. 26:518-526
We present a new algorithm to compute a collision-free trajectory for a robot manipulator to pour liquid from one container to the other. Our formulation uses a physical fluid model to predicate its highly deformable motion. We present simulation gui
Autor:
Nicolas Mansard, Chonhyon Park, Julien Pettré, Steve Tonneau, Dinesh Manocha, Andrea Del Prete
Publikováno v:
IEEE Transactions on Robotics
IEEE Transactions on Robotics, 2018, 34 (3), pp.586-601. ⟨10.1109/TRO.2018.2819658⟩
IEEE Transactions on Robotics, Institute of Electrical and Electronics Engineers (IEEE), 2018, pp.1-16. 〈10.1109/TRO.2018.2819658〉
IEEE Transactions on Robotics, IEEE, 2018, 34 (3), pp.586-601. ⟨10.1109/TRO.2018.2819658⟩
IEEE Transactions on Robotics, 2018, 34 (3), pp.586-601. ⟨10.1109/TRO.2018.2819658⟩
IEEE Transactions on Robotics, Institute of Electrical and Electronics Engineers (IEEE), 2018, pp.1-16. 〈10.1109/TRO.2018.2819658〉
IEEE Transactions on Robotics, IEEE, 2018, 34 (3), pp.586-601. ⟨10.1109/TRO.2018.2819658⟩
International audience; We present a framework capable of producing contact plans describing complex multiped motions (including humanoid): standing up, climbing stairs using a handrail, crossing rubble and getting out of a car. Our framework answers
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d638d72d36dde108ebe1cfefe1da3fb
https://hal.science/hal-01267345v3/file/root.pdf
https://hal.science/hal-01267345v3/file/root.pdf
Publikováno v:
Robotics: Science and Systems
We present a motion planning algorithm to compute collision-free and smooth trajectories for robots cooperating with humans in a shared workspace. Our approach uses offline learning of human actions and their temporal coherence to predict the human a
Publikováno v:
ICRA
We present new algorithms to perform fast probabilistic collision queries between convex as well as non-convex objects. Our approach is applicable to general shapes, where one or more objects are represented using Gaussian probability distributions.
Publikováno v:
IROS
We present an algorithmic framework for the early classification of human intentions, and use it to accurately predict future human motions when planning the path of a robot in an environment that is shared with humans. During an off-line learning ph