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公开(公告)号：US10860882B2
公开(公告)日：2020-12-08
申请号：US16042901
申请日：2018-07-23
Applicant: Brain Corporation
Inventor： Filip Piekniewski , Micah Richert , Dimitry Fisher
IPC: G06K9/46 , G06K9/48 , G06T7/90 , G06T7/20 , G06K9/00 , G06T3/00 , G06T7/246 , G06T7/285 , H04N9/797 , G06K9/32 , G06T7/292 , B25J9/16 , G01B11/14
Abstract: Apparatus and methods for detecting and utilizing saliency in digital images. In one implementation, salient objects may be detected based on analysis of pixel characteristics. Least frequently occurring pixel values may be deemed as salient. Pixel values in an image may be compared to a reference. Color distance may be determined based on a difference between reference color and pixel color. Individual image channels may be scaled when determining saliency in a multi-channel image. Areas of high saliency may be analyzed to determine object position, shape, and/or color. Multiple saliency maps may be additively or multiplicative combined in order to improve detection performance (e.g., reduce number of false positives). Methodologies described herein may enable robust tracking of objects utilizing fewer determination resources. Efficient implementation of the methods described below may allow them to be used for example on board a robot (or autonomous vehicle) or a mobile determining platform.
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公开(公告)号：US10810456B2
公开(公告)日：2020-10-20
申请号：US15871862
申请日：2018-01-15
Applicant: Brain Corporation
Inventor： Filip Piekniewski , Micah Richert , Dimitry Fisher
IPC: G06K9/00 , G06K9/46 , G06K9/48 , G06T7/246 , G06T7/90 , G06T7/285 , H04N9/797 , G06K9/32 , G06T7/20 , G06T7/292 , B25J9/16 , G01B11/14 , G06T3/00
Abstract: Apparatus and methods for detecting and utilizing saliency in digital images. In one implementation, salient objects may be detected based on analysis of pixel characteristics. Least frequently occurring pixel values may be deemed as salient. Pixel values in an image may be compared to a reference. Color distance may be determined based on a difference between reference color and pixel color. Individual image channels may be scaled when determining saliency in a multi-channel image. Areas of high saliency may be analyzed to determine object position, shape, and/or color. Multiple saliency maps may be additively or multiplicative combined in order to improve detection performance (e.g., reduce number of false positives). Methodologies described herein may enable robust tracking of objects utilizing fewer determination resources. Efficient implementation of the methods described below may allow them to be used for example on board a robot (or autonomous vehicle) or a mobile determining platform.
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公开(公告)号：US20200086494A1
公开(公告)日：2020-03-19
申请号：US16582302
申请日：2019-09-25
Applicant: Brain Corporation
Inventor： Dimitry Fisher , Cody Griffin , Micah Richert , Filip Piekniewski , Eugene Izhikevich , Jayram Moorkanikara Nageswaran , John Black
Abstract: Systems and methods for automatic detection of spills are disclosed. In some exemplary implementations, a robot can have a spill detector comprising at least one optical imaging device configured to capture at least one image of a scene containing a spill while the robot moves between locations. The robot can process the at least one image by segmentation. Once the spill has been identified, the robot can then generate an alert indicative at least in part of a recognition of the spill.
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公开(公告)号：US10282849B2
公开(公告)日：2019-05-07
申请号：US15627096
申请日：2017-06-19
Applicant: Brain Corporation
Inventor： Filip Piekniewski , Micah Richert , Dimitry Fisher , Patryk Laurent , Csaba Petre
Abstract: Systems and methods for predictive/reconstructive visual object tracking are disclosed. The visual object tracking has advanced abilities to track objects in scenes, which can have a variety of applications as discussed in this disclosure. In some exemplary implementations, a visual system can comprise a plurality of associative memory units, wherein each associative memory unit has a plurality of layers. The associative memory units can be communicatively coupled to each other in a hierarchical structure, wherein data in associative memory units in higher levels of the hierarchical structure are more abstract than lower associative memory units. The associative memory units can communicate to one another supplying contextual data.
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公开(公告)号：US20190061160A1
公开(公告)日：2019-02-28
申请号：US15997397
申请日：2018-06-04
Applicant: BRAIN CORPORATION
Inventor： Dimitry Fisher , Cody Griffin , Micah Richert , Filip Piekniewski , Eugene Izhikevich , Jayram Moorkanikara Nageswaran , John Black
Abstract: Systems and methods for automatic detection of spills are disclosed. In some exemplary implementations, a robot can have a spill detector comprising at least one optical imaging device configured to capture at least one image of a scene containing a spill while the robot moves between locations. The robot can process the at least one image by segmentation. Once the spill has been identified, the robot can then generate an alert indicative at least in part of a recognition of the spill.
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Patent Agency Ranking
公开(公告)号：US10032280B2
公开(公告)日：2018-07-24
申请号：US14637164
申请日：2015-03-03
Applicant: Brain Corporation
Inventor： Filip Piekniewski , Micah Richert , Dimitry Fisher
Abstract: Apparatus and methods for detecting and utilizing saliency in digital images. In one implementation, salient objects may be detected based on analysis of pixel characteristics. Least frequently occurring pixel values may be deemed as salient. Pixel values in an image may be compared to a reference. Color distance may be determined based on a difference between reference color and pixel color. Individual image channels may be scaled when determining saliency in a multi-channel image. Areas of high saliency may be analyzed to determine object position, shape, and/or color. Multiple saliency maps may be additively or multiplicative combined in order to improve detection performance (e.g., reduce number of false positives). Methodologies described herein may enable robust tracking of objects utilizing fewer determination resources. Efficient implementation of the methods described below may allow them to be used for example on board a robot (or autonomous vehicle) or a mobile determining platform.
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公开(公告)号：US09533413B2
公开(公告)日：2017-01-03
申请号：US14209826
申请日：2014-03-13
Applicant: Brain Corporation
Inventor： Eugene Izhikevich , Dimitry Fisher , Jean-Baptiste Passot , Heathcliff Hatcher , Vadim Polonichko
CPC classification number: B25J9/163 , A63H3/20 , B25J9/1694 , B25J13/08 , G06N3/008 , G06N3/049 , G06N99/005 , Y10S901/02 , Y10S901/04 , Y10S901/09 , Y10S901/50
Abstract: Apparatus and methods for a modular robotic device with artificial intelligence that is receptive to training controls. In one implementation, modular robotic device architecture may be used to provide all or most high cost components in an autonomy module that is separate from the robotic body. The autonomy module may comprise controller, power, actuators that may be connected to controllable elements of the robotic body. The controller may position limbs of the toy in a target position. A user may utilize haptic training approach in order to enable the robotic toy to perform target action(s). Modular configuration of the disclosure enables users to replace one toy body (e.g., the bear) with another (e.g., a giraffe) while using hardware provided by the autonomy module. Modular architecture may enable users to purchase a single AM for use with multiple robotic bodies, thereby reducing the overall cost of ownership.
Abstract translation: 具有接受训练控制的人造智能的模块化机器人装置的装置和方法。 在一个实现中，模块化机器人设备架构可以用于在与机器人主体分离的自主模块中提供全部或最高成本的组件。 自主模块可以包括可以连接到机器人身体的可控元件的控制器，电源，致动器。 控制器可将玩具的四肢定位在目标位置。 用户可以利用触觉训练方法，以使机器人玩具能够执行目标动作。 本公开的模块化配置使得用户可以在使用由自主模块提供的硬件的同时，用另一个（例如，长颈鹿）来替换一个玩具体（例如熊）。 模块化架构可以使用户能够购买单个AM以用于多个机器人体，从而降低总拥有成本。
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公开(公告)号：US09426946B2
公开(公告)日：2016-08-30
申请号：US14558403
申请日：2014-12-02
Applicant: Brain Corporation
Inventor： Dimitry Fisher
CPC classification number: A01G3/0435 , A01D34/008 , G05D1/0221 , G05D2201/0208 , G06Q30/0241
Abstract: A method and an apparatus for shaping of lawns and hedges into desired 3D patterns or shapes. The apparatus consists of a bStem and/or other computational device comprising storage, a motorized platform, and trimmer end effectors. The computational device instructs the end effectors to extend or retract as the platform moves along at a steady pace, thus producing a target pattern (e.g., a company logo) in a hedge, lawn, a wall or a ground-cover of any material suitable for such shaping. The apparatus may be configured to operate autonomously based on a pre-loaded pattern file. Software (e.g., such as BrainOS) may be used to provide real-time feedback to trimmers regarding the process and the results, and possibly to train the inverse model accordingly. The apparatus may learn to minimize predicted or current mismatches between the desired pattern and the one being produced. Users compete for the best designs.
Abstract translation: 一种用于将草坪和树篱整形成所需3D图案或形状的方法和装置。 该装置由包括存储器，电动平台和修剪器末端执行器的bStem和/或其他计算设备组成。 当平台以稳定的速度移动时，计算设备指示终端执行器延伸或缩回，从而在适合的任何材料的树篱，草坪，墙壁或地面覆盖物中产生目标图案（例如，公司标志） 用于这种塑形。 该装置可以被配置为基于预加载模式文件自主地操作。 可以使用软件（例如，诸如BrainOS）来提供关于过程和结果的修剪器的实时反馈，并且可能相应地训练逆模型。 该装置可以学习最小化期望图案与正在生产的图案之间的预测或当前不匹配。 用户竞争最好的设计。
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公开(公告)号：US09364950B2
公开(公告)日：2016-06-14
申请号：US14209578
申请日：2014-03-13
Applicant: Brain Corporation
Inventor： Eugene Izhikevich , Dimitry Fisher , Jean-Baptiste Passot , Heathcliff Hatcher , Vadim Polonichko
CPC classification number: B25J9/0081 , A63H29/22 , A63H30/04 , B25J9/104 , B25J13/00 , G06N99/005 , Y10T74/20305 , Y10T74/20311 , Y10T74/20317
Abstract: Apparatus and methods for a modular robotic device with artificial intelligence that is receptive to training controls. In one implementation, modular robotic device architecture may be used to provide all or most high cost components in an autonomy module that is separate from the robotic body. The autonomy module may comprise controller, power, actuators that may be connected to controllable elements of the robotic body. The controller may position limbs of the toy in a target position. A user may utilize haptic training approach in order to enable the robotic toy to perform target action(s). Modular configuration of the disclosure enables users to replace one toy body (e.g., the bear) with another (e.g., a giraffe) while using hardware provided by the autonomy module. Modular architecture may enable users to purchase a single AM for use with multiple robotic bodies, thereby reducing the overall cost of ownership.
Abstract translation: 具有接受训练控制的人造智能的模块化机器人装置的装置和方法。 在一个实现中，模块化机器人设备架构可以用于在与机器人主体分离的自主模块中提供全部或最高成本的组件。 自主模块可以包括可以连接到机器人身体的可控元件的控制器，电源，致动器。 控制器可将玩具的四肢定位在目标位置。 用户可以利用触觉训练方法，以使机器人玩具能够执行目标动作。 本公开的模块化配置使得用户可以在使用由自主模块提供的硬件的同时，用另一个（例如，长颈鹿）来替换一个玩具体（例如熊）。 模块化架构可以使用户能够购买单个AM以用于多个机器人体，从而降低总拥有成本。
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公开(公告)号：US10818016B2
公开(公告)日：2020-10-27
申请号：US16357536
申请日：2019-03-19
Applicant: BRAIN CORPORATION
Inventor： Filip Piekniewski , Micah Richert , Dimitry Fisher , Patryk Laurent , Csaba Petre
Abstract: Systems and methods for predictive/reconstructive visual object tracking are disclosed. The visual object tracking has advanced abilities to track objects in scenes, which can have a variety of applications as discussed in this disclosure. In some exemplary implementations, a visual system can comprise a plurality of associative memory units, wherein each associative memory unit has a plurality of layers. The associative memory units can be communicatively coupled to each other in a hierarchical structure, wherein data in associative memory units in higher levels of the hierarchical structure are more abstract than lower associative memory units. The associative memory units can communicate to one another supplying contextual data.
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