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Extract from the Register of European Patents

EP About this file: EP3515671

EP3515671 - ROBOTIC GRASPING PREDICTION USING NEURAL NETWORKS AND GEOMETRY AWARE OBJECT REPRESENTATION [Right-click to bookmark this link]
StatusNo opposition filed within time limit
Status updated on  19.03.2021
Database last updated on 18.03.2026
FormerThe patent has been granted
Status updated on  10.04.2020
FormerGrant of patent is intended
Status updated on  21.11.2019
FormerRequest for examination was made
Status updated on  28.06.2019
FormerThe international publication has been made
Status updated on  31.12.2018
Formerunknown
Status updated on  25.07.2018
Most recent event   Tooltip15.07.2022Lapse of the patent in a contracting state
New state(s): MK		published on 17.08.2022  [2022/33]
Applicant(s)For all designated states
Google LLC
1600 Amphitheatre Parkway
Mountain View, CA 94043 / US
[2019/31]
Inventor(s)01 / DAVIDSON, James
1600 Amphitheatre Parkway
Mountain View, California 94043 / US
02 / YAN, Xinchen
1600 Amphitheatre Parkway
Mountain View, California 94043 / US
03 / BAI, Yunfei
1600 Amphitheatre Parkway
Mountain View, California 94043 / US
04 / LEE, Honglak
1600 Amphitheatre Parkway
Mountain View, California 94043 / US
05 / GUPTA, Abhinav
1600 Amphitheatre Parkway
Mountain View, California 94043 / US
06 / KHANSARI ZADEH, Seyed Mohammad
1600 Amphitheatre Parkway
Mountain View, California 94043 / US
07 / PATHAK, Arkanath
1600 Amphitheatre Parkway
Mountain View, California 94043 / US
08 / HSU, Jasmine
1600 Amphitheatre Parkway
Mountain View, California 94043 / US
 [2019/31]
Representative(s)Anderson, Oliver Ben, et al
Venner Shipley LLP
200 Aldersgate
London EC1A 4HD / GB
[2019/31]
Application number, filing date18740382.918.06.2018
[2019/31]
WO2018US38082
Priority number, dateUS201762522059P19.06.2017         Original published format: US 201762522059 P
[2019/31]
Filing languageEN
Procedural languageEN
PublicationType: A1 Application with search report
No.:WO2018236753
Date:27.12.2018
Language:EN
[2018/52]
Type: A1 Application with search report 
No.:EP3515671
Date:31.07.2019
Language:EN
The application published by WIPO in one of the EPO official languages on 27.12.2018 takes the place of the publication of the European patent application.
[2019/31]
Type: B1 Patent specification 
No.:EP3515671
Date:13.05.2020
Language:EN
[2020/20]
Search report(s)International search report - published on:EP27.12.2018
ClassificationIPC:B25J9/16
[2019/31]
CPC:
B25J9/1612 (EP,CN,US); B25J9/1697 (EP,CN,US); B25J9/161 (CN,US);
B25J9/1669 (EP,CN,US); B25J9/1694 (CN); G05B2219/39473 (EP);
G05B2219/39484 (EP); G05B2219/39536 (EP) (-)
Designated contracting statesAL,   AT,   BE,   BG,   CH,   CY,   CZ,   DE,   DK,   EE,   ES,   FI,   FR,   GB,   GR,   HR,   HU,   IE,   IS,   IT,   LI,   LT,   LU,   LV,   MC,   MK,   MT,   NL,   NO,   PL,   PT,   RO,   RS,   SE,   SI,   SK,   SM,   TR [2019/31]
Extension statesBANot yet paid
MENot yet paid
Validation statesKHNot yet paid
MANot yet paid
MDNot yet paid
TNNot yet paid
TitleGerman:ROBOTISCHE GREIFVORHERSAGE UNTER VERWENDUNG NEURONALER NETZWERKE UND GEOMETRIEBEWUSSTER OBJEKTDARSTELLUNG[2019/31]
English:ROBOTIC GRASPING PREDICTION USING NEURAL NETWORKS AND GEOMETRY AWARE OBJECT REPRESENTATION[2019/31]
French:PRÉDICTION DE SAISIE ROBOTIQUE AU MOYEN DE RÉSEAUX NEURONAUX ET D'UNE REPRÉSENTATION D'OBJET SENSIBLE À LA GÉOMÉTRIE[2019/31]
Entry into regional phase26.04.2019National basic fee paid 
26.04.2019Designation fee(s) paid 
26.04.2019Examination fee paid 
Examination procedure26.04.2019Amendment by applicant (claims and/or description)
26.04.2019Examination requested  [2019/31]
26.04.2019Date on which the examining division has become responsible
22.11.2019Communication of intention to grant the patent
31.03.2020Fee for grant paid
31.03.2020Fee for publishing/printing paid
31.03.2020Receipt of the translation of the claim(s)
Divisional application(s)EP20167061.9  / EP3693138
Opposition(s)16.02.2021No opposition filed within time limit [2021/16]
Opt-out from the exclusive  Tooltip
competence of the Unified
Patent Court		 See the Register of the Unified Patent Court for opt-out data
Responsibility for the accuracy, completeness or quality of the data displayed under the link provided lies entirely with the Unified Patent Court.
Lapses during opposition  TooltipHU18.06.2018
AL13.05.2020
AT13.05.2020
CY13.05.2020
CZ13.05.2020
DK13.05.2020
EE13.05.2020
ES13.05.2020
FI13.05.2020
HR13.05.2020
IT13.05.2020
LT13.05.2020
LV13.05.2020
MC13.05.2020
MK13.05.2020
MT13.05.2020
NL13.05.2020
PL13.05.2020
RO13.05.2020
RS13.05.2020
SE13.05.2020
SI13.05.2020
SK13.05.2020
SM13.05.2020
TR13.05.2020
IE18.06.2020
LU18.06.2020
BE30.06.2020
BG13.08.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
[2022/33]
Former [2022/27]HU18.06.2018
AL13.05.2020
AT13.05.2020
CY13.05.2020
CZ13.05.2020
DK13.05.2020
EE13.05.2020
ES13.05.2020
FI13.05.2020
HR13.05.2020
IT13.05.2020
LT13.05.2020
LV13.05.2020
MC13.05.2020
MT13.05.2020
NL13.05.2020
PL13.05.2020
RO13.05.2020
RS13.05.2020
SE13.05.2020
SI13.05.2020
SK13.05.2020
SM13.05.2020
TR13.05.2020
IE18.06.2020
LU18.06.2020
BE30.06.2020
BG13.08.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2021/24]AL13.05.2020
AT13.05.2020
CZ13.05.2020
DK13.05.2020
EE13.05.2020
ES13.05.2020
FI13.05.2020
HR13.05.2020
IT13.05.2020
LT13.05.2020
LV13.05.2020
MC13.05.2020
NL13.05.2020
PL13.05.2020
RO13.05.2020
RS13.05.2020
SE13.05.2020
SI13.05.2020
SK13.05.2020
SM13.05.2020
IE18.06.2020
LU18.06.2020
BE30.06.2020
BG13.08.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2021/20]AL13.05.2020
AT13.05.2020
CZ13.05.2020
DK13.05.2020
EE13.05.2020
ES13.05.2020
FI13.05.2020
HR13.05.2020
IT13.05.2020
LT13.05.2020
LV13.05.2020
MC13.05.2020
NL13.05.2020
PL13.05.2020
RO13.05.2020
RS13.05.2020
SE13.05.2020
SK13.05.2020
SM13.05.2020
IE18.06.2020
LU18.06.2020
BG13.08.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2021/15]AL13.05.2020
AT13.05.2020
CZ13.05.2020
DK13.05.2020
EE13.05.2020
ES13.05.2020
FI13.05.2020
HR13.05.2020
IT13.05.2020
LT13.05.2020
LV13.05.2020
MC13.05.2020
NL13.05.2020
PL13.05.2020
RO13.05.2020
RS13.05.2020
SE13.05.2020
SK13.05.2020
SM13.05.2020
LU18.06.2020
BG13.08.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2021/14]AL13.05.2020
AT13.05.2020
CZ13.05.2020
DK13.05.2020
EE13.05.2020
ES13.05.2020
FI13.05.2020
HR13.05.2020
IT13.05.2020
LT13.05.2020
LV13.05.2020
MC13.05.2020
NL13.05.2020
PL13.05.2020
RO13.05.2020
RS13.05.2020
SE13.05.2020
SK13.05.2020
SM13.05.2020
BG13.08.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2021/10]AL13.05.2020
AT13.05.2020
CZ13.05.2020
DK13.05.2020
EE13.05.2020
ES13.05.2020
FI13.05.2020
HR13.05.2020
IT13.05.2020
LT13.05.2020
LV13.05.2020
NL13.05.2020
PL13.05.2020
RO13.05.2020
RS13.05.2020
SE13.05.2020
SK13.05.2020
SM13.05.2020
BG13.08.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2021/09]AL13.05.2020
AT13.05.2020
CZ13.05.2020
DK13.05.2020
EE13.05.2020
ES13.05.2020
FI13.05.2020
HR13.05.2020
IT13.05.2020
LT13.05.2020
LV13.05.2020
NL13.05.2020
RO13.05.2020
RS13.05.2020
SE13.05.2020
SM13.05.2020
BG13.08.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2021/08]AL13.05.2020
DK13.05.2020
ES13.05.2020
FI13.05.2020
HR13.05.2020
LT13.05.2020
LV13.05.2020
NL13.05.2020
RO13.05.2020
RS13.05.2020
SE13.05.2020
SM13.05.2020
BG13.08.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2021/04]AL13.05.2020
FI13.05.2020
HR13.05.2020
LT13.05.2020
LV13.05.2020
NL13.05.2020
RS13.05.2020
SE13.05.2020
BG13.08.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2021/01]FI13.05.2020
HR13.05.2020
LT13.05.2020
LV13.05.2020
RS13.05.2020
SE13.05.2020
BG13.08.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2020/51]FI13.05.2020
HR13.05.2020
LT13.05.2020
LV13.05.2020
RS13.05.2020
SE13.05.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2020/50]FI13.05.2020
HR13.05.2020
LT13.05.2020
LV13.05.2020
SE13.05.2020
NO13.08.2020
GR14.08.2020
IS13.09.2020
PT14.09.2020
Former [2020/48]FI13.05.2020
LT13.05.2020
SE13.05.2020
NO13.08.2020
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PT14.09.2020
Former [2020/47]LT13.05.2020
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IS13.09.2020
Former [2020/46]IS13.09.2020
Cited inInternational search[A]   I. LENZ ET AL: "Deep learning for detecting robotic grasps", INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH., vol. 34, no. 4-5, 16 March 2015 (2015-03-16), US, pages 705 - 724, XP055288225, ISSN: 0278-3649, DOI: 10.1177/0278364914549607 [A] 1-22 * page 705 - page 724 *

DOI:   http://dx.doi.org/10.1177/0278364914549607
 [A]   SULABH KUMRA ET AL: "Robotic grasp detection using deep convolutional neural networks", ARXIV:1611.08036V3 [CS.RO], 24 February 2017 (2017-02-24), pages 1 - 8, XP055503622 [A] 1-22 * the whole document *
 [A]   JOSEPH REDMON ET AL: "Real-time grasp detection using convolutional neural networks", 2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 1 May 2015 (2015-05-01), pages 1316 - 1322, XP055288285, ISBN: 978-1-4799-6923-4, DOI: 10.1109/ICRA.2015.7139361 [A] 1-22 * the whole document *

DOI:   http://dx.doi.org/10.1109/ICRA.2015.7139361
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