I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Socially Aware Hybrid Robot Navigation via Deep Reinforceme..:
, In:
2023 42nd Chinese Control Conference (CCC)
,
Feng, Zhen
;
Gao, Ming
;
Xue, Bingxin
.. - p. 3697-3701 , 2023
Link:
https://doi.org/10.23919/CCC58697.2023.10240813
RT T1
2023 42nd Chinese Control Conference (CCC)
: T1
Socially Aware Hybrid Robot Navigation via Deep Reinforcement Learning
UL https://suche.suub.uni-bremen.de/peid=ieee-10240813&Exemplar=1&LAN=DE A1 Feng, Zhen A1 Gao, Ming A1 Xue, Bingxin A1 Wang, Chaoqun A1 Zhou, Fengyu YR 2023 SN 1934-1768 K1 Deep learning K1 Navigation K1 Dynamics K1 Human-robot interaction K1 Reinforcement learning K1 Feature extraction K1 Generators K1 Social robotics K1 Dynamic window approach K1 Deep reinforcement learning SP 3697 OP 3701 LK http://dx.doi.org/https://doi.org/10.23919/CCC58697.2023.10240813 DO https://doi.org/10.23919/CCC58697.2023.10240813 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)