IP Library › Granted Patent US 12,194,639
Granted Patent B2
US 12,194,639 · App. 17/909,801 · Granted Jan 14, 2025

Digital representations of robot operational environment, useful in motion planning for robots

Inventors: Aakash Murugan (Boston, MA); Jenni Lam (Boston, MA); Venkat K. Gopalakrishnan (Lexington, MA)
Assignee: REALTIME ROBOTICS, INC.
B25J9/1666B25J9/161B25J9/1697
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Quick Facts
Patent No.
US 12,194,639
App. No.
17/909,801
Filed
Sep 7, 2022
Granted
Jan 14, 2025
Kind
B2
Art Unit
3657
USPC
700/245
Abstract

An oversized representation of at least a portion of a robot is filtered (e.g., voxels are set as unoccupied for any objects that reside completely within the oversized representation) from a representation of an operational environment, which provides a digital model of the operational environment which can, for example, be used for motion planning for the robot. The oversized representation exceeds a physical dimension of at least a portion (e.g. appendage) of the robot, to advantageously account for cables and other features that are attached to, and extending beyond, the outer dimensions of the robot. The specific dimensions of the oversized representation can be based on a variety of factors, for example a geometry of the cable, orientation or position of the robot appendage, orientation or position of the cable with respect to the robot appendage, velocity of the appendage, slack in the cable, etc., which may be modeled.

Claims (80)

1. A system, comprising:

at least one processor; at least one nontransitory processor-readable medium communicatively coupled to the at least one processor and which stores processor-executable instructions which, when executed by the at least processor, cause the at least one processor to:

identify one or more elements in a digital representation of a three-dimensional operational environment, the one or more elements that represent one or more physical objects that reside in the three-dimensional operational environment;

determine which, whether any, of the physical objects represented in the digital representation of the three-dimensional operational environment reside completely within a three-dimensional representation of an oversized volume that encompasses at least an appendage of a first robot, at least one portion of the oversized volume which extends beyond a corresponding peripheral dimension of at least the appendage of the first robot to encompass one or more cables physically coupled to the appendage of the first robot;

for at least one of the physical objects that are-is determined to reside completely within the three-dimensional representation of the oversized volume, set one or more occupancy values in the digital representation of the three-dimensional operational environment to represent a volume corresponding to the respective physical object as unoccupied to provide a filtered representation of the three-dimensional operational environment in which the oversized volume encompassing at least the robotic appendage of the first robot and at least one of the one or more cables is not indicated as being an obstacle;

perform motion planning for the first robot using the filtered representation of the three-dimensional operational environment; and

provide an output to position and orient robots in a multi-robot environment and that causes the robot to perform tasks.

2. The system of claim 1 wherein the instructions, when executed by the at least one processor, cause the at least one processor further to:

generate the three-dimensional representation of the oversized volume that encompasses at least the appendage of the first robot and the at least one portion of the oversized volume which extends beyond the corresponding peripheral dimension of the appendage of the first robot to encompass one or more cables physically coupled to the appendage of the first robot.

3. The system of claim 2 wherein to generate the three-dimensional representation of an oversized volume, the instructions, when executed by the at least one processor, cause the at least one processor to:

modify a three-dimensional representation of the appendage of the first robot to increase at least one dimension thereof along a one portion of the appendage, the portion of the appendage along which the at least one of the one or more cables extends along.

4. The system of claim 2 wherein to generate the three-dimensional representation of an oversized volume, the instructions, when executed by the at least one processor, cause the at least one processor to:

generate the three-dimensional representation of an oversized volume based at least on a location of the at least one of the one or more cables relative to at least a part of the appendage of the first robot with respect to gravity.

5. The system of claim 2 wherein to generate the three-dimensional representation of an oversized volume, the instructions, when executed by the at least one processor, cause the at least one processor to:

generate the three-dimensional representation of an oversized volume based at least on an orientation of at least a part of the appendage of the first robot with respect to gravity and an amount of slack in at least one of the one or more cables.

6. The system of claim 2 wherein to generate the three-dimensional representation of an oversized volume, the instructions, when executed by the at least one processor, cause the at least one processor to:

generate a bounding box representation based on a set of dimensions of the appendage of the first robot and based on a set of border buffer specifications.

7. The system of claim 2 wherein to generate the three-dimensional representation of an oversized volume, the instructions, when executed by the at least one processor, cause the at least one processor to:

generate the three-dimensional representation of an oversized volume based at least on a geometry of the at least one of the one or more cables.

8. The system of claim 7 wherein to generate the three-dimensional representation of an oversized volume, the instructions, when executed by the at least one processor, cause the at least one processor to:

generate the three-dimensional representation of an oversized volume based at least on a velocity of at least a part of the appendage of the first robot.

9. The system of claim 1 wherein to identify one or more elements in the digital representation of the three-dimensional operational environment, the instructions, when executed by the at least one processor, cause the at least one processor to:

identify one or more groups of voxels in the digital representation of the three-dimensional operational environment that are contiguous and that each have a respective occupancy value that represents an occupied occupancy condition, and

wherein to determine which, if any, of the physical objects represented in the digital representation of the three-dimensional operational environment reside completely within a three-dimensional representation of an oversized volume the instructions, when executed by the at least one processor, cause the at least one processor to:

determine for each of the one or more groups of voxels in the digital representation of the three-dimensional operational environment that have been identified as representing a physical object whether the group of voxels straddle a boundary of the three-dimensional representation of the oversized volume.

10. The system of claim 1 wherein to identify one or more elements in the digital representation of the three-dimensional operational environment, the instructions, when executed by the at least one processor, cause the at least one processor to:

identify one or more groups of voxels in the digital representation of the three-dimensional operational environment that are contiguous and that each have a respective occupancy value that represents an occupied occupancy condition, and

wherein to set one or more occupancy values in the digital representation of the three-dimensional operational environment to represent a volume corresponding to the respective physical object as unoccupied the instructions, when executed by the at least one processor, cause the at least one processor to:

for each voxel in the digital representation of the three-dimensional operational environment that corresponds to any of the objects that reside completely within the three-dimensional representation of the oversized volume as represented in the digital representation of the three-dimensional operational environment, set a respective occupancy value of the respective voxel as representative of being unoccupied.

11. The system of claim 1 wherein, when executed by the at least one processor, the instructions cause the at least one processor to:

during a pre-run time period,

repeatedly move at least a portion of the first robot having the at least one of the one or more cables;

capture data that represents a volume occupied by the at least one of the one or more cables during each movement of the portion of the first robot; and

generating a digital model of at least the at least one of the one or more cables.

12. The system of claim 1 wherein, when executed by the at least one processor, the instructions cause the at least one processor to:

determine which, if any, of the physical objects represented in the digital representation of the three-dimensional operational environment reside completely within a three-dimensional representation of an oversized volume that encompasses at least an appendage of a second robot, at least one portion of the oversized volume which extends beyond a corresponding peripheral dimension of at least the appendage of the second robot to encompass one or more cables physically coupled to the appendage of the second robot; and

for any of the physical objects that are determined to reside completely within the three-dimensional representation of the oversized volume, set one or more occupancy values in the digital representation of the three-dimensional operational environment to represent a volume corresponding to the respective physical object as unoccupied to provide a filtered representation of the three-dimensional operational environment in which the oversized volume encompassing at least the robotic appendage of the second robot and the at least one of the one or more cables is not indicated as being an obstacle.

13. A method of operation of a system, the system comprising at least one processor, and at least one nontransitory processor-readable medium communicatively coupled to the at least one processor and which stores processor-executable instructions, the method comprising:

identifying one or more elements in a digital representation of a three-dimensional operational environment, the one or more elements which represent one or more physical objects that reside in the three-dimensional operational environment;

determining whether any, of the physical objects represented in the digital representation of the three-dimensional operational environment reside completely within a three-dimensional representation of an oversized volume that encompasses at least an appendage of a first robot, at least one portion of the oversized volume which extends beyond a corresponding peripheral dimension of at least the appendage of the first robot to encompass one or more cables physically coupled to the appendage of the first robot;

for at least one of the physical objects that a-is determined to reside completely within the three-dimensional representation of the oversized volume, setting one or more occupancy values in the digital representation of the three-dimensional operational environment to represent a volume corresponding to the respective physical object as unoccupied to provide a filtered representation of the three-dimensional operational environment in which the oversized volume encompassing at least the robotic appendage of the first robot and the-at least one of the one or more cables is not indicated as being an obstacle;

performing motion planning for the first robot using the filtered representation of the three-dimensional operational environment; and

providing output to position and orient robots in a multi-robot environment and that causes the robot to perform tasks.

14. The method of claim 13 further comprising:

generating the three-dimensional representation of the oversized volume that encompasses at least the appendage of the first robot and at least one portion of the oversized volume which extends beyond the corresponding peripheral dimension of the appendage of the first robot to encompass one or more cables physically coupled to the appendage of the first robot.

15. The method of claim 14 wherein generating the three-dimensional representation of an oversized volume includes:

modifying a three-dimensional representation of the appendage of the first robot to increase at least one dimension thereof along a one portion of the appendage, the portion of the appendage along which the at least one of the one or more cables extends along.

16. The method of claim 14 wherein generating the three-dimensional representation of an oversized volume includes:

generating the three-dimensional representation of an oversized volume based at least on a location of the at least one of the one or more cables relative to at least a part of the appendage of the first robot with respect to gravity.

17. The method of claim 14 wherein generating the three-dimensional representation of an oversized volume includes:

generating the three-dimensional representation of an oversized volume based at least on an orientation of at least a part of the appendage of the first robot with respect to gravity and an amount of slack in the at least one of the one or more cables.

18. The method of claim 14 wherein generating the three-dimensional representation of an oversized volume includes:

generating a bounding box representation based on a set of dimensions of the appendage of the first robot and based on a set of border buffer specifications.

19. The method of claim 14 wherein generating the three-dimensional representation of an oversized volume includes:

generating the three-dimensional representation of an oversized volume based at least on a geometry of the at least one of the one or more cables.

20. The method of claim 19 wherein generating the three-dimensional representation of an oversized volume includes:

generating the three-dimensional representation of an oversized volume based at least on a velocity of at least a part of the appendage of the first robot.

21. The method of claim 13 wherein identifying one or more elements in the digital representation of the three-dimensional operational environment includes:

identifying one or more groups of voxels in the digital representation of the three-dimensional operational environment that are contiguous and that each have a respective occupancy value that represents an occupied occupancy condition, and

wherein determining which, if any, of the physical objects represented in the digital representation of the three-dimensional operational environment reside completely within a three-dimensional representation of an oversized volume includes:

determining for each of the one or more groups of voxels in the digital representation of the three-dimensional operational environment that have been identified as representing a physical object whether the group of voxels straddle a boundary of the three-dimensional representation of the oversized volume.

22. The method of claim 13 wherein identifying one or more elements in the digital representation of the three-dimensional operational environment includes:

identifying one or more groups of voxels in the digital representation of the three-dimensional operational environment that are contiguous and that each have a respective occupancy value that represents an occupied occupancy condition, and

wherein setting one or more occupancy values in the digital representation of the three-dimensional operational environment to represent a volume corresponding to the respective physical object as unoccupied includes:

for each voxel in the digital representation of the three-dimensional operational environment that corresponds to any of the objects that reside completely within the three-dimensional representation of the oversized volume as represented in the digital representation of the three-dimensional operational environment, setting a respective occupancy value of the respective voxel as representative of being unoccupied.

23. The method of claim 13 , further comprising:

during a pre-run time period,

repeatedly causing at least a portion of the first robot having the at least one of the one or more cables to move;

capturing data that represents a volume occupied by the at least one of the one or more cables during each movement of the portion of the first robot; and

generating a digital model of at least the at least one of the one or more cables.

24. The method of claim 13 , further comprising:

determining which, if any, of the physical objects represented in the digital representation of the three-dimensional operational environment reside completely within a three-dimensional representation of an oversized volume that encompasses at least an appendage of a second robot, at least one portion of the oversized volume which extends beyond a corresponding peripheral dimension of at least the appendage of the second robot to encompass one or more cables physically coupled to the appendage of the second robot; and

for any of the physical objects that are determined to reside completely within the three-dimensional representation of the oversized volume, setting one or more occupancy values in the digital representation of the three-dimensional operational environment to represent a volume corresponding to the respective physical object as unoccupied to provide a filtered representation of the three-dimensional operational environment in which the oversized volume encompassing at least the robotic appendage of the second robot and the at least one of the one or more cables is not indicated as being an obstacle.

25. A system, comprising:

at least one processor;

at least one nontransitory processor-readable medium communicatively coupled to the at least one processor and which stores processor-executable instructions which, when executed by the at least processor, cause the at least one processor to:

identify one or more elements in a digital representation of a three-dimensional operational environment, the one or more elements which represent one or more physical objects that reside in the three-dimensional operational environment;

determine whether any, of the physical objects represented in the digital representation of the three-dimensional operational environment reside completely within a three-dimensional representation of an oversized volume that encompasses at least an appendage of a first robot, at least one portion of the oversized volume which extends beyond a corresponding peripheral dimension of at least the appendage of the first robot to encompass one or more structures physically coupled to the appendage of the first robot; and

for at least one of the physical objects that is determined to reside completely within the three-dimensional representation of the oversized volume, set one or more occupancy values in the digital representation of the three-dimensional operational environment to represent a volume corresponding to the respective physical object as unoccupied to provide a filtered representation of the three-dimensional operational environment in which the oversized volume encompassing at least the robotic appendage of the first robot and the at least one structure is not indicated as being an obstacle.

26. The system of claim 25 wherein the one or more structures is a cable.

Assignments (2)
SECURITY INTEREST Recorded Oct 22, 2025
From: REALTIME ROBOTICS, INC.
To: FIRST-CITIZENS BANK & TRUST COMPANY
Reel/Frame 074155/0025 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 19, 2024
From: MURUGAN, AAKASH; LAM, JENNI; GOPALAKRISHNAN, VENKAT K.
To: REALTIME ROBOTICS, INC.
Reel/Frame 069322/0387 →
Continuity (2)
Provisional Application 62991487 · Mar 18, 2020
Related Publication 20240208060A1 · Jun 27, 2024
References Cited (400)
US 4163183A · Dunne et al. · 1979 [cited by applicant]
US 4300198A · Davini · 1981 [cited by applicant]
US 4763276A · Perreirra et al. · 1988 [cited by applicant]
US 4862373A · Meng · 1989 [cited by applicant]
US 4890241A · Hoffman et al. · 1989 [cited by applicant]
US 4949277A · Trovato et al. · 1990 [cited by applicant]
US 5177563A · Everett et al. · 1993 [cited by applicant]
US 5297238A · Wang et al. · 1994 [cited by applicant]
US 5347459A · Greenspan et al. · 1994 [cited by applicant]
US 5544282A · Chen et al. · 1996 [cited by applicant]
US 5727132A · Arimatsu et al. · 1998 [cited by applicant]
US 6004016A · Spector · 1999 [cited by applicant]
US 6049756A · Libby · 2000 [cited by applicant]
US 6089742A · Warmerdam et al. · 2000 [cited by applicant]
US 6259988B1 · Galkowski et al. · 2001 [cited by applicant]
US 6345213B1 · Graeser et al. · 2002 [cited by applicant]
US 6470301B1 · Barral · 2002 [cited by applicant]
US 6493607B1 · Bourne et al. · 2002 [cited by applicant]
US 6526372B1 · Orschel et al. · 2003 [cited by applicant]
US 6526373B1 · Barral · 2003 [cited by applicant]
US 6529852B2 · Knoll et al. · 2003 [cited by applicant]
US 6539294B1 · Kageyama · 2003 [cited by applicant]
US 6629037B1 · Nyland · 2003 [cited by applicant]
US 6671582B1 · Hanley · 2003 [cited by applicant]
US 6836702B1 · Brogaardh et al. · 2004 [cited by applicant]
US 6907133B2 · Gotoh · 2005 [cited by applicant]
US 6944584B1 · Tenney et al. · 2005 [cited by applicant]
US 7493231B2 · Graf · 2009 [cited by applicant]
US 7577498B2 · Jennings et al. · 2009 [cited by applicant]
US 7609020B2 · Kniss et al. · 2009 [cited by applicant]
US 7715946B2 · Watanabe et al. · 2010 [cited by applicant]
US 7865277B1 · Larson et al. · 2011 [cited by applicant]
US 7904202B2 · Hoppe · 2011 [cited by applicant]
US 7940023B2 · Kniss et al. · 2011 [cited by applicant]
US 8082064B2 · Kay · 2011 [cited by applicant]
US 8103085B1 · Zadeh · 2012 [cited by applicant]
US 8111904B2 · Wallack et al. · 2012 [cited by applicant]
US 8162584B2 · Michael et al. · 2012 [cited by applicant]
US 8315738B2 · Chang et al. · 2012 [cited by applicant]
US 8571706B2 · Zhang et al. · 2013 [cited by applicant]
US 8666548B2 · Lim · 2014 [cited by applicant]
US 8825207B2 · Kim et al. · 2014 [cited by applicant]
US 8825208B1 · Benson · 2014 [cited by applicant]
US 8855812B2 · Kapoor · 2014 [cited by applicant]
US 8880216B2 · Izumi et al. · 2014 [cited by applicant]
US 8972057B1 · Freeman et al. · 2015 [cited by applicant]
US 8989897B2 · De Smet · 2015 [cited by applicant]
US 9061421B2 · Trompeter · 2015 [cited by applicant]
US 9092698B2 · Buehler et al. · 2015 [cited by applicant]
US 9102055B1 · Konolige et al. · 2015 [cited by applicant]
US 9227322B2 · Graca et al. · 2016 [cited by applicant]
US 9280899B2 · Biess et al. · 2016 [cited by applicant]
US 9327397B1 · Williams et al. · 2016 [cited by applicant]
US 9333044B2 · Olson · 2016 [cited by applicant]
US 9434072B2 · Buehler et al. · 2016 [cited by applicant]
US 9539058B2 · Tsekos et al. · 2017 [cited by applicant]
US 9632502B1 · Levinson et al. · 2017 [cited by applicant]
US 9645577B1 · Frazzoli et al. · 2017 [cited by applicant]
US 9659236B2 · Barker et al. · 2017 [cited by applicant]
US 9687982B1 · Jules et al. · 2017 [cited by applicant]
US 9687983B1 · Prats · 2017 [cited by applicant]
US 9701015B2 · Buehler et al. · 2017 [cited by applicant]
US 9707682B1 · Konolige et al. · 2017 [cited by applicant]
US 9731724B2 · Yoon · 2017 [cited by applicant]
US 9981382B1 · Strauss et al. · 2018 [cited by applicant]
US 9981383B1 · Nagarajan · 2018 [cited by applicant]
US 10035266B1 · Kroeger · 2018 [cited by applicant]
US 10099372B2 · Vu et al. · 2018 [cited by applicant]
US 10124488B2 · Lee et al. · 2018 [cited by applicant]
US 10131053B1 · Sampedro et al. · 2018 [cited by applicant]
US 10300605B2 · Sato · 2019 [cited by applicant]
US 10303180B1 · Prats · 2019 [cited by applicant]
US 10430641B2 · Gao · 2019 [cited by applicant]
US 10671081B1 · Prats · 2020 [cited by applicant]
US 10688664B2 · Kovacs · 2020 [cited by applicant]
US 10705528B2 · Wierzynski et al. · 2020 [cited by applicant]
US 10723024B2 · Konidaris et al. · 2020 [cited by applicant]
US 10782694B2 · Zhang et al. · 2020 [cited by applicant]
US 10792114B2 · Hashimoto et al. · 2020 [cited by applicant]
US 10959795B2 · Hashimoto et al. · 2021 [cited by applicant]
US 11314254B2 · Macias et al. · 2022 [cited by applicant]
US 11358337B2 · Czinger et al. · 2022 [cited by applicant]
US 11407117B1 · Hickman · 2022 [cited by examiner]
US 11623494B1 · Arnicar et al. · 2023 [cited by applicant]
US 11751948B2 · Gregerson et al. · 2023 [cited by applicant]
US 20020013675A1 · Knoll et al. · 2002 [cited by applicant]
US 20020074964A1 · Quaschner et al. · 2002 [cited by applicant]
US 20030155881A1 · Hamann et al. · 2003 [cited by applicant]
US 20040249509A1 · Rogers et al. · 2004 [cited by applicant]
US 20050071048A1 · Watanabe et al. · 2005 [cited by applicant]
US 20050216181A1 · Estkowski et al. · 2005 [cited by applicant]
US 20060235610A1 · Ariyur et al. · 2006 [cited by applicant]
US 20060241813A1 · Babu et al. · 2006 [cited by applicant]
US 20060247852A1 · Kortge et al. · 2006 [cited by applicant]
US 20070106422A1 · Jennings et al. · 2007 [cited by applicant]
US 20070112700A1 · Den et al. · 2007 [cited by applicant]
US 20070239315A1 · Sato et al. · 2007 [cited by applicant]
US 20080012517A1 · Kniss et al. · 2008 [cited by applicant]
US 20080125893A1 · Tilove et al. · 2008 [cited by applicant]
US 20080186312A1 · Ahn et al. · 2008 [cited by applicant]
US 20080234864A1 · Sugiura et al. · 2008 [cited by applicant]
US 20090055024A1 · Kay · 2009 [cited by applicant]
US 20090192710A1 · Eidehall et al. · 2009 [cited by applicant]
US 20090234499A1 · Nielsen et al. · 2009 [cited by applicant]
US 20090295323A1 · Papiernik et al. · 2009 [cited by applicant]
US 20090326711A1 · Chang et al. · 2009 [cited by applicant]
US 20090326876A1 · Miller · 2009 [cited by applicant]
US 20100145516A1 · Cedoz et al. · 2010 [cited by applicant]
US 20100235033A1 · Yamamoto et al. · 2010 [cited by applicant]
US 20110036188A1 · Fujioka et al. · 2011 [cited by applicant]
US 20110066282A1 · Bosscher et al. · 2011 [cited by applicant]
US 20110153080A1 · Shapiro et al. · 2011 [cited by applicant]
US 20110222995A1 · Irie et al. · 2011 [cited by applicant]
US 20110264111A1 · Nowlin et al. · 2011 [cited by applicant]
US 20120010772A1 · Pack et al. · 2012 [cited by applicant]
US 20120053728A1 · Theodorus et al. · 2012 [cited by applicant]
US 20120083964A1 · Montemerlo et al. · 2012 [cited by applicant]
US 20120215351A1 · Mcgee et al. · 2012 [cited by applicant]
US 20120297733A1 · Pierson et al. · 2012 [cited by applicant]
US 20120323357A1 · Izumi et al. · 2012 [cited by applicant]
US 20130076866A1 · Drinkard et al. · 2013 [cited by applicant]
US 20130325244A1 · Wang et al. · 2013 [cited by applicant]
US 20130346348A1 · Buehler et al. · 2013 [cited by applicant]
US 20140012419A1 · Nakajima · 2014 [cited by applicant]
US 20140025201A1 · Ryu et al. · 2014 [cited by applicant]
US 20140025203A1 · Inazumi · 2014 [cited by applicant]
US 20140058406A1 · Tsekos · 2014 [cited by applicant]
US 20140067121A1 · Brooks et al. · 2014 [cited by applicant]
US 20140079524A1 · Shimono et al. · 2014 [cited by applicant]
US 20140121833A1 · Lee et al. · 2014 [cited by applicant]
US 20140121837A1 · Hashiguchi et al. · 2014 [cited by applicant]
US 20140147240A1 · Noda et al. · 2014 [cited by applicant]
US 20140156068A1 · Graca et al. · 2014 [cited by applicant]
US 20140249741A1 · Levien et al. · 2014 [cited by applicant]
US 20140251702A1 · Berger et al. · 2014 [cited by applicant]
US 20140277718A1 · Izhikevich et al. · 2014 [cited by applicant]
US 20140305227A1 · Johns · 2014 [cited by applicant]
US 20140309916A1 · Bushnell · 2014 [cited by applicant]
US 20140368504A1 · Chen et al. · 2014 [cited by applicant]
US 20150005785A1 · Olson · 2015 [cited by applicant]
US 20150037131A1 · Girtman et al. · 2015 [cited by applicant]
US 20150051783A1 · Tamir et al. · 2015 [cited by applicant]
US 20150134111A1 · Nakajima · 2015 [cited by applicant]
US 20150217455A1 · Kikkeri et al. · 2015 [cited by applicant]
US 20150261899A1 · Atohira et al. · 2015 [cited by applicant]
US 20150266182A1 · Strandberg · 2015 [cited by applicant]
US 20160001775A1 · Wilhelm et al. · 2016 [cited by applicant]
US 20160008078A1 · Azizian et al. · 2016 [cited by applicant]
US 20160016312A1 · Lawrence et al. · 2016 [cited by applicant]
US 20160059412A1 · Oleynik · 2016 [cited by examiner]
US 20160107313A1 · Hoffmann et al. · 2016 [cited by applicant]
US 20160112694A1 · Nishi et al. · 2016 [cited by applicant]
US 20160121486A1 · Lipinski et al. · 2016 [cited by applicant]
US 20160121487A1 · Mohan et al. · 2016 [cited by applicant]
US 20160154408A1 · Eade et al. · 2016 [cited by applicant]
US 20160161257A1 · Simpson et al. · 2016 [cited by applicant]
US 20160299507A1 · Shah et al. · 2016 [cited by applicant]
US 20160324587A1 · Olson · 2016 [cited by applicant]
US 20160357187A1 · Ansari · 2016 [cited by applicant]
US 20170001775A1 · Cimmerer et al. · 2017 [cited by applicant]
US 20170004406A1 · Aghamohammadi · 2017 [cited by applicant]
US 20170028559A1 · Davidi et al. · 2017 [cited by applicant]
US 20170120448A1 · Lee et al. · 2017 [cited by applicant]
US 20170123419A1 · Levinson et al. · 2017 [cited by applicant]
US 20170132334A1 · Levinson et al. · 2017 [cited by applicant]
US 20170146999A1 · Cherepinsky et al. · 2017 [cited by applicant]
US 20170157769A1 · Aghamohammadi et al. · 2017 [cited by applicant]
US 20170168485A1 · Berntorp et al. · 2017 [cited by applicant]
US 20170168488A1 · Wierzynski et al. · 2017 [cited by applicant]
US 20170193830A1 · Fragoso et al. · 2017 [cited by applicant]
US 20170210008A1 · Maeda · 2017 [cited by applicant]
US 20170219353A1 · Alesiani · 2017 [cited by applicant]
US 20170252922A1 · Levine et al. · 2017 [cited by applicant]
US 20170252924A1 · Mjayanarasimhan et al. · 2017 [cited by applicant]
US 20170305015A1 · Krasny et al. · 2017 [cited by applicant]
US 20170315530A1 · Godau et al. · 2017 [cited by applicant]
US 20180001472A1 · Konidaris et al. · 2018 [cited by applicant]
US 20180001476A1 · Tan et al. · 2018 [cited by applicant]
US 20180029231A1 · Davis · 2018 [cited by applicant]
US 20180029233A1 · Lager · 2018 [cited by applicant]
US 20180032039A1 · Huynh et al. · 2018 [cited by applicant]
US 20180074505A1 · Lv et al. · 2018 [cited by applicant]
US 20180113468A1 · Russell · 2018 [cited by applicant]
US 20180136662A1 · Kim · 2018 [cited by applicant]
US 20180150077A1 · Danielson et al. · 2018 [cited by applicant]
US 20180172450A1 · Lalonde et al. · 2018 [cited by applicant]
US 20180173242A1 · Lalonde et al. · 2018 [cited by applicant]
US 20180189683A1 · Newman · 2018 [cited by applicant]
US 20180222050A1 · Vu et al. · 2018 [cited by applicant]
US 20180222051A1 · Vu et al. · 2018 [cited by applicant]
US 20180229368A1 · Leitner et al. · 2018 [cited by applicant]
US 20180281786A1 · Oyaizu et al. · 2018 [cited by applicant]
US 20180339456A1 · Czinger et al. · 2018 [cited by applicant]
US 20180349702A1 · Gildert · 2018 [cited by examiner]
US 20190015981A1 · Yabushita et al. · 2019 [cited by applicant]
US 20190039242A1 · Fujii et al. · 2019 [cited by applicant]
US 20190087976A1 · Sugahara et al. · 2019 [cited by applicant]
US 20190101930A1 · Yadmellat · 2019 [cited by applicant]
US 20190105779A1 · Einav · 2019 [cited by applicant]
US 20190143518A1 · Maeda · 2019 [cited by applicant]
US 20190163191A1 · Sorin et al. · 2019 [cited by applicant]
US 20190164430A1 · Nix · 2019 [cited by applicant]
US 20190196480A1 · Taylor · 2019 [cited by applicant]
US 20190216555A1 · Dimaio et al. · 2019 [cited by applicant]
US 20190232496A1 · Graichen et al. · 2019 [cited by applicant]
US 20190234751A1 · Takhirov · 2019 [cited by applicant]
US 20190240835A1 · Sorin et al. · 2019 [cited by applicant]
US 20190262993A1 · Cole et al. · 2019 [cited by applicant]
US 20190291277A1 · Oleynik · 2019 [cited by examiner]
US 20190293443A1 · Kelly et al. · 2019 [cited by applicant]
US 20190391597A1 · Dupuis · 2019 [cited by applicant]
US 20200030971A1 · Oleynik · 2020 [cited by examiner]
US 20200069134A1 · Ebrahimi Afrouzi et al. · 2020 [cited by applicant]
US 20200078097A1 · Gregerson et al. · 2020 [cited by applicant]
US 20200097014A1 · Wang · 2020 [cited by applicant]
US 20200215686A1 · Vijayanarasimhan et al. · 2020 [cited by applicant]
US 20200331146A1 · Vu et al. · 2020 [cited by applicant]
US 20200331155A1 · Vu et al. · 2020 [cited by applicant]
US 20200338730A1 · Yamauchi et al. · 2020 [cited by applicant]
US 20200338733A1 · Dupuis et al. · 2020 [cited by applicant]
US 20200353917A1 · Leitermann et al. · 2020 [cited by applicant]
US 20200368910A1 · Chu et al. · 2020 [cited by applicant]
US 20210009351A1 · Beinhofer et al. · 2021 [cited by applicant]
US 20210178591A1 · Floyd-Jones · 2021 [cited by examiner]
US 20220305648A1 · Oleynik · 2022 [cited by examiner]
US 20220339875A1 · Czinger et al. · 2022 [cited by applicant]
US 20230031545A1 · Oleynik · 2023 [cited by examiner]
US 20230063205A1 · Nerkar · 2023 [cited by applicant]
US 20230363833A1 · Gregerson et al. · 2023 [cited by applicant]
CA 3071332A1 · 2019 [cited by examiner]
CN 101837591A · 2010 [cited by applicant]
CN 102814813A · 2012 [cited by applicant]
CN 103722565A · 2014 [cited by applicant]
CN 104407616A · 2015 [cited by applicant]
CN 104858876A · 2015 [cited by applicant]
CN 102186638B · 2016 [cited by applicant]
CN 106660208A · 2017 [cited by applicant]
CN 107073710A · 2017 [cited by applicant]
CN 107206592A · 2017 [cited by applicant]
CN 107486858A · 2017 [cited by applicant]
CN 108297059A · 2018 [cited by applicant]
CN 108453702A · 2018 [cited by applicant]
CN 108789416A · 2018 [cited by applicant]
CN 108858183A · 2018 [cited by applicant]
CN 108942920A · 2018 [cited by applicant]
CN 109521763A · 2019 [cited by applicant]
CN 109782763B · 2021 [cited by applicant]
CN 114073585A · 2022 [cited by applicant]
EP 1241628A2 · 2002 [cited by applicant]
EP 1901150A1 · 2008 [cited by applicant]
EP 2306153A2 · 2011 [cited by applicant]
EP 3250347A1 · 2017 [cited by applicant]
EP 3486612A1 · 2019 [cited by applicant]
EP 3725472A1 · 2020 [cited by applicant]
JP 07100755 · 1995 [cited by applicant]
JP 1997212229 · 1997 [cited by applicant]
JP 1148177 · 1999 [cited by applicant]
JP 11296229A · 1999 [cited by applicant]
JP 2001166806A · 2001 [cited by applicant]
JP 2002073130A · 2002 [cited by applicant]
JP 2003127077A · 2003 [cited by applicant]
JP 2005022062A · 2005 [cited by applicant]
JP 2005032196A · 2005 [cited by applicant]
JP 2006224740A · 2006 [cited by applicant]
JP 2007257274A · 2007 [cited by applicant]
JP 2007531110A · 2007 [cited by applicant]
JP 2008502488A · 2008 [cited by applicant]
JP 2008065755A · 2008 [cited by applicant]
JP 2008134165A · 2008 [cited by applicant]
JP 2010061293A · 2010 [cited by applicant]
JP 2010210592A · 2010 [cited by applicant]
JP 2011075382A · 2011 [cited by applicant]
JP 2011249711A · 2011 [cited by applicant]
JP 2012056023A · 2012 [cited by applicant]
JP 2012190405A · 2012 [cited by applicant]
JP 2012243029A · 2012 [cited by applicant]
JP 2013193194A · 2013 [cited by applicant]
JP 2014184498A · 2014 [cited by applicant]
JP 2015044274A · 2015 [cited by applicant]
JP 2015517142A · 2015 [cited by applicant]
JP 2015208811A · 2015 [cited by applicant]
JP 2016099257A · 2016 [cited by applicant]
JP 2017131973A · 2017 [cited by applicant]
JP 2017136677A · 2017 [cited by applicant]
JP 2017148908A · 2017 [cited by applicant]
JP 2018505788A · 2018 [cited by applicant]
JP 2018130793A · 2018 [cited by applicant]
JP 2018134703A · 2018 [cited by applicant]
JP 2018144158A · 2018 [cited by applicant]
JP 2018144166A · 2018 [cited by applicant]
JP 2019136848A · 2019 [cited by applicant]
JP 2019188530A · 2019 [cited by applicant]
JP 2020049623 · 2020 [cited by applicant]
JP 2020082332A · 2020 [cited by applicant]
KR 19980024584A · 1998 [cited by applicant]
KR 20110026776A · 2011 [cited by applicant]
KR 20130112507A · 2013 [cited by applicant]
KR 20150126482A · 2015 [cited by applicant]
KR 20170018564A · 2017 [cited by applicant]
KR 20170044987A · 2017 [cited by applicant]
KR 20170050166A · 2017 [cited by applicant]
KR 20180125646A · 2018 [cited by applicant]
TW 201318793A · 2013 [cited by applicant]
TW 615691 · 2018 [cited by applicant]
TW 653130 · 2019 [cited by applicant]
WO 9924914A1 · 1999 [cited by applicant]
WO 2015113203A1 · 2015 [cited by applicant]
WO 2016122840A1 · 2016 [cited by applicant]
WO 2017168187A1 · 2017 [cited by applicant]
WO 2017214581A1 · 2017 [cited by applicant]
WO 2018043525A1 · 2018 [cited by applicant]
WO 2019183141A1 · 2019 [cited by applicant]
WO WO2020040979A1 · 2020 [cited by examiner]
WO 2020117958A1 · 2020 [cited by applicant]
Notice of Reasons for Rejection dated Feb. 16, 2023, for Japanese Application No. 2021-571340, 10 pages. [cited by applicant]
Office Action issued in Taiwan Application No. 108104094, mailed Feb. 6, 2023, 24 pages. [cited by applicant]
Atay, Nuzhet , et al., “A Motion Planning Processor on Reconfigurable Hardware”, All Computer Science and Engineering Research, Computer Science and Engineering; Report No. WUCSE-2005-46; Sep. 23, 2005. [cited by applicant]
Chen, Chao , Motion Planning for Nonholonomic Vehicles with Space Exploration Guided Heuristic Search, 2016, IEEE.com, Whole Document, 140 pages. [cited by applicant]
Corrales, J.A. , et al., Safe Human-robot interaction based on dynamic sphere-swept line bounding volumes, Robotic and Computer-Integrated Manufacturing 27 (2011) 177-185, 9 page. [cited by applicant]
Hauck, Scott , et al., “Configuration Compression for the Xilinx XC6200 FPGA”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 18, No. 8; Aug. 1999. [cited by applicant]
Johnson, David E., et al., “Bound Coherence for Minimum Distance Computations”, Proceedings of the 1999 IEEE International Conference on Robotics and Automation, May 1999. [cited by applicant]
Kavraki, L.E. , et al., “Probabilistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces”, IEEE Transactions on Robotics and Automation, IEEE Inc .; vol. 12, No. 4, pp. 566-580; Aug. 1, 1996. [cited by applicant]
Pan, Jia , et al., Efficient Configuration Space Construction and Optimization for Motion Planning, 2015, Research Robotics, Whole Document, 12 pages. [cited by applicant]
Stilman, Mike , et al., “Manipulation Planning Among Movable Obstacles”, Proceedings of the IEEE Int. Conf. on Robotics and Automation, Apr. 2007. [cited by applicant]
Hassan, “Modeling and Stochastic Optimization of Complete Coverage under Uncertainties in Multi-Robot Base Placements,” 2016, Intelligent Robots and Systems (IROS} (Year: 2016). [cited by applicant]
Hassan, et al., “An Approach to Base Placement for Effective Collaboration of Multiple Autonomous Industrial Robots,” 2015 IEEE International Conference on Robotics and Automation (ICRA}, pp. 3286-3291 (Year: 2015). [cited by applicant]
Hassan, et al., “Simultaneous area partitioning and allocation for complete coverage by multiple autonomous industrial robots,” 2017, Autonomous Robots 41, pp. 1609-1628 (Year: 2017). [cited by applicant]
Hassan, et al., “Task Oriented Area Partitioning and Allocation for Optimal Operation of Multiple Industrial Robots in Unstructured Environments,” 2014, 13th International Conference on Control, Automation, Robotics & V… [cited by applicant]
Kalawoun, “Motion planning of multi-robot system for airplane stripping.” 2019, Universite Clermont Auvergne (Year: 2019). [cited by applicant]
Kapanoglu, et al., “A pattern-based genetic algorithm for multi-robot coverage path planning minimizing completion time,” 2012, Journal of Intelligent Manufacturing 23, pp. 1035-1045 (Year: 2012). [cited by applicant]
Notice of Allowance for U.S. Appl. No. 17/153,662, mailed Dec. 6, 2022, 15 pages. [cited by applicant]
Pires, et al., “Robot Trajectory Planning Using Multi-objective Genetic Algorithm Optimization,” 2004, Genetic and Evolutionary Computation—GECCO 2004, pp. 615-626 (Year: 2004). [cited by applicant]
Final Office Action for U.S. Appl. No. 17/506,364, mailed Aug. 25, 2023, 55 pages. [cited by applicant]
Non-Final Office Action Issued in U.S. Appl. No. 17/270,597, mailed Aug. 18, 2023, 25 pages. [cited by applicant]
Office Action, ROC (Taiwan) Pat. Appln. No. 108130161 and Search Report—APP.108130161—mailed Sep. 19, 2023. [cited by applicant]
Bharathi Akilan et al: “Feed-rate optimization for smooth minimum-time trajectory generation with higher order constraints”, The International Journal of Advanced Manufacturing Technology,vol. 82, No. 5, Jun. 28, 2015 (… [cited by applicant]
Communication Pursuant to Article 94(3) EPC, issued in European Application No. 17811131.6, Mailed Date: Jun. 16, 2020, 5 pages. [cited by applicant]
Communication Pursuant to Article 94(3) EPC, Issued in European Application No. 18209405.2, Mailed Date: Nov. 23, 2020, 4 pages. [cited by applicant]
Dong et al: “Feed-rate optimization with jerk constraints for generating minimum-time trajectories”, International Journal of Machine Tool Design and Research, Pergamon Press, Oxford, GB, vol. 47, No. 12-13, Aug. 9, 200… [cited by applicant]
European Search Report dated Jul. 23, 2021, for European Application No. 19851097.6, 15 pages. [cited by applicant]
European Search Report issued in European Application No. 19771537.8, Mailed Date: Mar. 29, 2021, 8 pages. [cited by applicant]
European Search Report, Mailed Date: Nov. 17, 2020 for EP Application No. 16743821.7, 4 pages. [cited by applicant]
Extended EP Search Report mailed Jul. 18, 2022 EP App No. 20832308.9-1205, 10 pages. [cited by applicant]
Extended EP Search Report mailed Jul. 25, 2022 EP App No. 20857383.2-1205, 10 pages. [cited by applicant]
Extended European Search Report issued in European Application No. 17811131.6, Mailed Date: Apr. 24, 2019, 16 pages. [cited by applicant]
Extended European Search Report issued in European Application No. 18209405.2, Mailed Date: Aug. 2, 2019, 9 pages. [cited by applicant]
Extended European Search Report issued in European Application No. 19893874.8, Mailed Date: Jan. 5, 2022, 13 pages. [cited by applicant]
Extended European Search Report, Mailed Date: Apr. 10, 2018 for EP Application No. 16743821.7, in 9 pages. [cited by applicant]
Final Office Action Issued in U.S. Appl. No. 16/268,290, Mailed Date: Apr. 21, 2021, 58 pages. [cited by applicant]
Final Office Action mailed Aug. 2, 2021 for U.S. Appl. No. 16/240,086, 66 pages. [cited by applicant]
Final Office Action mailed Sep. 7, 2022, for U.S. Appl. No. 16/909,096, 54 pages. [cited by applicant]
First Office Action issued in Chinese No. 201680006941.3 with English translation, Mailed Date: Sep. 29, 2019, 16 pages. [cited by applicant]
Non-Final Office Action Issued in U.S. Appl. No. 16/268,290, Mailed Date: Jan. 27, 2021, 54 pages. [cited by applicant]
Murray, Sean , et al., “The microarchitecture of a real-time robot motion planning accelerator”, 2016 49th Annual IEEE/ACM International Symposium on Microarchitecture (Micro), IEEE, Oct. 15, 2016, 12 pages. [cited by applicant]
Pobil, Angel P, et al., “A New Representation for Collision Avoidance and Detection”, Proceedings of the 1992 IEEE, XP000300485, pp. 246-251. [cited by applicant]
Sato, Yuichi , et al., “Efficient Collision Detection using Fast Distance-Calculation Algorithms for Convex and Non-Convex Objects”, Proceeding of the 1996 IEEE, XP-000750294, 8 pages. [cited by applicant]
Turrillas, Alexander Martin, “Improvement of a Multi-Body Collision Computation Framework and Its Application to Robot (Self-) Collision Avoidance”, German Aerospace Center (DLR). Master's Thesis, Jun. 1, 2015, 34 pages. [cited by applicant]
First Office Action issued in Chinese No. 201980024188.4 with English translation, Mailed Date: Feb. 22, 2023, 28 pages. [cited by applicant]
Non-Final Office Action Issued in U.S. Appl. No. 16/981,467, Mailed Mar. 16, 2023, 19 Pages. [cited by applicant]
Notice of Reasons for Rejection dated Feb. 7, 2023, for Japanese Application No. 2022-054900, 7 pages. [cited by applicant]
Communication Pursuant to Article 94(3) EPC, dated Jul. 12, 2023, for European Application No. 19 893 874.8-1205, 5 pages. [cited by applicant]
Final Office Action for U.S. Appl. No. 17/682,732, mailed Jul. 7, 2023, 46 pages. [cited by applicant]
First Office Action issued in Chinese No. 201980055188.0 with English translation, Mailed Date: Jul. 1, 2023, 16 pages. [cited by applicant]
First Office Action issued in Chinese No. 201980080759.6 with English translation, Mailed Date: Jun. 28, 2023, 4 pages. [cited by applicant]
First Office Action issued in Chinese No. 202080055382.1 with English translation, Mailed Date: Jun. 28, 2023, 30 pages. [cited by applicant]
International Search Report and Written Opinion for PCT/US2023/064012, mailed Jul. 10, 2023, 15 pages. [cited by applicant]
Extended EP Search Report mailed May 10, 2023, EP App No. 20818760.9-1012, 9 pages. [cited by applicant]
First Office Action and Search Report issued in Chinese No. 202080040382.4 with English translation, Mailed Date: May 26, 2023, 15 pages. [cited by applicant]
First Office Action issued in Chinese No. 202080059714.3 with English translation, Mailed Date: May 24, 2023, 24 pages. [cited by applicant]
Japanese Office Action, Japanese Application No. 2021-576425, Mar. 13, 2023, 14 pages. [cited by applicant]
Li, et al., “A Novel Cost Function for Decision-Making Strategies in Automotive Collision Avoidance Systems”, 2018 IEEE, ICVES, 8 pages. [cited by applicant]
Non-Final Office Action Issued in U.S. Appl. No. 17/506,364, Mailed Apr. 28, 2023, 50 pages. [cited by applicant]
Schwesinger, “Motion Planning n Dynamic Environments with Application to Self-Driving Vehicles”, Dr. Andreas Krause, Jan. 1, 2017, XP093029842. [cited by applicant]
Final Office Action Issued in U.S. Appl. No. 17/270,597, mailed Oct. 27, 2023, 29 pages. [cited by applicant]
Non-Final Office Action Issued in U.S. Appl. No. 17/604,285, mailed Nov. 21, 2023, 28 pages. [cited by applicant]
Notice of Reasons for Refusal dated Nov. 27, 2023, for Japanese Application No. 2021-561986, 10 pages. [cited by applicant]
Oleynikova, et al., “Singed Distance Fields: a Natural Representation for Both Mapping and Planning”, 2016, 7 pages. [cited by applicant]
Taiwanese First Office Action—Application No. 109120779 dated Nov. 9, 2023, 11 pages. [cited by applicant]
Barral D et al: “Simulated Annealing Combined With a Constructive Algorithm for Optimising Assembly Workcell Layout”, The International Journal of Advanced Manufacturing Technology, Springer, London, vol. 17, No. 8, Jan… [cited by applicant]
Extended EP Search Report mailed Nov. 7, 2022, EP App No. 21744840.6-1205, 14 pages. [cited by applicant]
Klampfl Erica et al: “Optimization of workcell layouts in a mixed-model assembly line environment” International Journal of Flexible Manufacturing Systems, Kluwer Academic Publishers, Boston, vol. 17, No. 4, 23 pages., … [cited by applicant]
Long Tao et al: “Optimization on multi-robot workcell layout in vertical plane”, Information and Automation (ICIA), 2011 IEEE International Conference on, IEEE, Jun. 6, 2011, 6 pages. [cited by applicant]
Pashkevich AP et al: “Multiobjective optimisation of robot location in a workcell using genetic algorithms”, Control '98. UKACC International Conference on (Conf. Publ. No. 455) Swansea, Uk Sep. 1-4, 1998, London, UK, v… [cited by applicant]
Zhen Yang et al: “Multi-objective hybrid algorithms for layout optimization in multi-robot cellular manufacturing systems”, Knowledge-Based Systems, Elsevier, Amsterdam, NL, vol. 120, Jan. 3, 2017, 12 pages. [cited by applicant]
First Office Action issued in Japanese Patent Application No. 2017-557268, Mailed Date: Aug. 7, 2018, 15 pages. [cited by applicant]
Gasparetto A et al: “Experimental validation and comparative analysis of optimal time-jerk algorithms for trajectory planning”, Robotics and Computer Integrated Manufacturing, Elsevier Science Publishers BV. , Barking, … [cited by applicant]
Gasparetto et al: “A new method for smooth trajectory planning of robot manipulators”, Mechanism and Machine Theory, Pergamon, Amsterdam, NL, vol. 42, No. 4, Jan. 26, 2007. [cited by applicant]
Haschke R et al: “On-Line Planning of Time-Opti.mal, Jerk-Limited Trajectories”, Internet Citation, Jul. 1, 2008 (Jul. 1, 2008), pp. 1-6, XP00278977 6. [cited by applicant]
International Search Report and Written Opinion for PCT/US2019/016700, Mailed Date: May 20, 2019, 14 pages,. [cited by applicant]
International Search Report and Written Opinion for PCT/US2019/023031, Mailed Date: Aug. 14, 2019 in 19 pages. [cited by applicant]
International Search Report and Written Opinion for PCT/US2019/064511, Mailed Date: Mar. 27, 2020, 10 pages. [cited by applicant]
International Search Report and Written Opinion for PCT/US2021/061427, mailed Apr. 29, 2022, 14 pages. [cited by applicant]
International Search Report and Written Opinion issued in PCT Application No. PCT/2020/034551, Mailed Date: Aug. 31, 2020, 18 pages. [cited by applicant]
International Search Report and Written Opinion issued in PCT Application No. PCT/US2016/012204; Mailed Date: Mar. 21, 2016, 10 pages. [cited by applicant]
International Search Report and Written Opinion issued in PCT Application No. PCT/US2017/036880; Mailed Date: Oct. 10, 2017, 15 pages. [cited by applicant]
International Search Report and Written Opinion issued in PCT Application No. PCT/US2019/045270; Mailed Date: Nov. 25, 2019, 11 pages. [cited by applicant]
International Search Report and Written Opinion issued in PCT/US2019/012209, Mailed Date: Apr. 25, 2019, 24 pages. [cited by applicant]
International Search Report and Written Opinion, mailed Apr. 22, 2021, for International Application No. PCT/US2021/013610, 9 pages. [cited by applicant]
International Search Report and Written Opinion, Mailed Date: Jul. 29, 2020, in PCT/US2020/028343, 11 pages,. [cited by applicant]
International Search Report and Written Opinion, Mailed Date: Nov. 23, 2020, for PCT/US2020/047429, 11 Pages. [cited by applicant]