Fast Kinodynamic Planning on the Constraint Manifold With Deep Neural Networks-Reference-Cited by-同舟云学术

Fast Kinodynamic Planning on the Constraint Manifold With Deep Neural Networks

Author:

Kicki Piotr¹^ORCID,Liu Puze²^ORCID,Tateo Davide²^ORCID,Bou-Ammar Haitham³^ORCID,Walas Krzysztof¹^ORCID,Skrzypczyński Piotr¹^ORCID,Peters Jan²^ORCID

Affiliation:

1. Institute of Robotics and Machine Intelligence, Poznan University of Technology, Poznan, Poland

2. Department of Computer Science, Technische Universität Darmstadt, Darmstadt, Germany

3. Huawei R&D London, Cambridge, U.K.

Funder

TAILOR

Horizon 2020

REMODEL

CSTT

Huawei Tech R&D

China Scholarship Council

German Federal Ministry of Education and Research

collaborative KIARA

Narodowa Agencja Wymiany Akademickiej

STER

Poznan University

PUT

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

Reference68 articles.

2. Policy search for motor primitives in robotics;Kober;Adv. Neural Inf. Process. Syst.,2008

5. High acceleration reinforcement learning for real-world juggling with binary rewards;Ploeger,2021

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