公开(公告)号：US20160279790A1

公开(公告)日：2016-09-29

申请号：US15174858

申请日：2016-06-06

Applicant: Brain Corporation

Inventor： Philip Meier ,  Jean-Baptiste Passot ,  Borja Ibarz Gabardos ,  Patryk Laurent ,  Oleg Sinyavskiy ,  Peter O'Connor ,  Eugene Izhikevich

IPC: B25J9/16 ,  G06N99/00 ,  G06N3/00

CPC classification number: B25J9/163 ,  B25J9/1602 ,  B25J9/161 ,  B25J9/1656 ,  G05B2219/40116 ,  G05D1/0033 ,  G05D1/0088 ,  G05D2201/02 ,  G06N3/008 ,  G06N99/005 ,  Y10S901/01 ,  Y10S901/46

Abstract: Robots have the capacity to perform a broad range of useful tasks, such as factory automation, cleaning, delivery, assistive care, environmental monitoring and entertainment. Enabling a robot to perform a new task in a new environment typically requires a large amount of new software to be written, often by a team of experts. It would be valuable if future technology could empower people, who may have limited or no understanding of software coding, to train robots to perform custom tasks. Some implementations of the present invention provide methods and systems that respond to users' corrective commands to generate and refine a policy for determining appropriate actions based on sensor-data input. Upon completion of learning, the system can generate control commands by deriving them from the sensory data. Using the learned control policy, the robot can behave autonomously.

公开(公告)号：US10322507B2

公开(公告)日：2019-06-18

申请号：US15785181

申请日：2017-10-16

Applicant: Brain Corporation

Inventor： Philip Meier ,  Jean-Baptiste Passot ,  Borja Ibarz Gabardos ,  Patryk Laurent ,  Oleg Sinyavskiy ,  Peter O'Connor ,  Eugene Izhikevich

IPC: B25J9/00 ,  B25J9/16 ,  G06N20/00 ,  G06N3/00 ,  G05D1/00 ,  G05B13/02

Abstract: Robots have the capacity to perform a broad range of useful tasks, such as factory automation, cleaning, delivery, assistive care, environmental monitoring and entertainment. Enabling a robot to perform a new task in a new environment typically requires a large amount of new software to be written, often by a team of experts. It would be valuable if future technology could empower people, who may have limited or no understanding of software coding, to train robots to perform custom tasks. Some implementations of the present invention provide methods and systems that respond to users' corrective commands to generate and refine a policy for determining appropriate actions based on sensor-data input. Upon completion of learning, the system can generate control commands by deriving them from the sensory data. Using the learned control policy, the robot can behave autonomously.

公开(公告)号：US20180099409A1

公开(公告)日：2018-04-12

申请号：US15785181

申请日：2017-10-16

Applicant: Brain Corporation

Inventor： Philip Meier ,  Jean-Baptiste Passot ,  Borja Ibarz Gabardos ,  Patryk Laurent ,  Oleg Sinyavskiy ,  Peter O'Connor ,  Eugene Izhikevich

IPC: B25J9/16 ,  G05D1/00 ,  G06N99/00 ,  G06N3/00

CPC classification number: B25J9/163 ,  B25J9/1602 ,  B25J9/161 ,  B25J9/1656 ,  G05B2219/40116 ,  G05D1/0033 ,  G05D1/0088 ,  G05D2201/02 ,  G06N3/008 ,  G06N99/005 ,  Y10S901/01 ,  Y10S901/46

Abstract: Robots have the capacity to perform a broad range of useful tasks, such as factory automation, cleaning, delivery, assistive care, environmental monitoring and entertainment. Enabling a robot to perform a new task in a new environment typically requires a large amount of new software to be written, often by a team of experts. It would be valuable if future technology could empower people, who may have limited or no understanding of software coding, to train robots to perform custom tasks. Some implementations of the present invention provide methods and systems that respond to users' corrective commands to generate and refine a policy for determining appropriate actions based on sensor-data input. Upon completion of learning, the system can generate control commands by deriving them from the sensory data. Using the learned control policy, the robot can behave autonomously.

公开(公告)号：US09446515B1

公开(公告)日：2016-09-20

申请号：US14625464

申请日：2015-02-18

Applicant: BRAIN CORPORATION

Inventor： Philip Meier

IPC: G05B15/00 ,  G05B19/00 ,  B25J9/16

CPC classification number: B25J9/163 ,  B25J9/1656 ,  B25J9/1694 ,  G05B19/42 ,  G05B2219/31048 ,  G05B2219/36447 ,  G05B2219/40103 ,  Y02P90/04

Abstract: Apparatus and methods for controlling attention and training of autonomous robotic devices. In one approach, attention of the robot may be manipulated by use of a spot-light device illuminating a portion of the aircraft undergoing inspection in order to indicate to inspection robot target areas requiring more detailed inspection. The robot guidance may be aided by way of an additional signal transmitted by the agent to the robot indicating that the object has been illuminated and attention switch may be required. Responsive to receiving the additional signal, the robot may initiate a search for the signal reflected by the illuminated area requiring its attention. Responsive to detecting the illuminated object and receipt of the additional signal, the robot may develop an association between the two events and the inspection task. The light guided attention system may influence the robot learning for subsequent actions.

公开(公告)号：US09789605B2

公开(公告)日：2017-10-17

申请号：US15174858

申请日：2016-06-06

Applicant: Brain Corporation

Inventor： Philip Meier ,  Jean-Baptiste Passot ,  Borja Ibarz Gabardos ,  Patryk Laurent ,  Oleg Sinyavskiy ,  Peter O'Connor ,  Eugene Izhikevich

IPC: G05B19/04 ,  B25J9/16 ,  G06N99/00 ,  G06N3/00 ,  G05D1/00

CPC classification number: B25J9/163 ,  B25J9/1602 ,  B25J9/161 ,  B25J9/1656 ,  G05B2219/40116 ,  G05D1/0033 ,  G05D1/0088 ,  G05D2201/02 ,  G06N3/008 ,  G06N99/005 ,  Y10S901/01 ,  Y10S901/46

Abstract: Robots have the capacity to perform a broad range of useful tasks, such as factory automation, cleaning, delivery, assistive care, environmental monitoring and entertainment. Enabling a robot to perform a new task in a new environment typically requires a large amount of new software to be written, often by a team of experts. It would be valuable if future technology could empower people, who may have limited or no understanding of software coding, to train robots to perform custom tasks. Some implementations of the present invention provide methods and systems that respond to users' corrective commands to generate and refine a policy for determining appropriate actions based on sensor-data input. Upon completion of learning, the system can generate control commands by deriving them from the sensory data. Using the learned control policy, the robot can behave autonomously.

公开(公告)号：US20150217449A1

公开(公告)日：2015-08-06

申请号：US14171762

申请日：2014-02-03

Applicant: Brain Corporation

Inventor： Philip Meier ,  Jean-Baptiste Passot ,  Borja Ibarz Gabardos ,  Patryk Laurent ,  Oleg Sinyavskiy ,  Peter O'Connor ,  Eugene Izhikevich

IPC: B25J9/16 ,  G06N5/04 ,  G06N99/00

CPC classification number: B25J9/163 ,  B25J9/1602 ,  B25J9/161 ,  B25J9/1656 ,  G05B2219/40116 ,  G05D1/0033 ,  G05D1/0088 ,  G05D2201/02 ,  G06N3/008 ,  G06N99/005 ,  Y10S901/01 ,  Y10S901/46

Abstract: Robots have the capacity to perform a broad range of useful tasks, such as factory automation, cleaning, delivery, assistive care, environmental monitoring and entertainment. Enabling a robot to perform a new task in a new environment typically requires a large amount of new software to be written, often by a team of experts. It would be valuable if future technology could empower people, who may have limited or no understanding of software coding, to train robots to perform custom tasks. Some implementations of the present invention provide methods and systems that respond to users' corrective commands to generate and refine a policy for determining appropriate actions based on sensor-data input. Upon completion of learning, the system can generate control commands by deriving them from the sensory data. Using the learned control policy, the robot can behave autonomously.

Abstract translation: 机器人有能力执行广泛的有用任务，如工厂自动化，清洁，交付，辅助护理，环境监测和娱乐。 使机器人在新环境中执行新任务通常需要大量新的软件来编写，通常由专家小组编写。 如果未来的技术可以赋予人们对软件编码有限或不了解的机会来训练机器人来执行定制任务，这将是有价值的。 本发明的一些实施方案提供了响应于用户的校正命令以生成和改进用于基于传感器数据输入确定适当动作的策略的方法和系统。 完成学习后，系统可以通过从感官数据中导出控制命令来生成控制命令。 使用学习的控制策略，机器人可以自主行为。

公开(公告)号：US20190321973A1

公开(公告)日：2019-10-24

申请号：US16402758

申请日：2019-05-03

Applicant: Brain Corporation

Inventor： Philip Meier ,  Jean-Baptiste Passot ,  Borja Ibarz Gabardos ,  Patryk Laurent ,  Oleg Sinyavskiy ,  Peter O'Connor ,  Eugene Izhikevich

IPC: B25J9/16 ,  G06N20/00 ,  G06N3/00 ,  G05D1/00 ,  G05B13/02

Abstract: Robots have the capacity to perform a broad range of useful tasks, such as factory automation, cleaning, delivery, assistive care, environmental monitoring and entertainment. Enabling a robot to perform a new task in a new environment typically requires a large amount of new software to be written, often by a team of experts. It would be valuable if future technology could empower people, who may have limited or no understanding of software coding, to train robots to perform custom tasks. Some implementations of the present invention provide methods and systems that respond to users' corrective commands to generate and refine a policy for determining appropriate actions based on sensor-data input. Upon completion of learning, the system can generate control commands by deriving them from the sensory data. Using the learned control policy, the robot can behave autonomously.

公开(公告)号：US09358685B2

公开(公告)日：2016-06-07

申请号：US14171762

申请日：2014-02-03

Applicant: BRAIN CORPORATION

Inventor： Philip Meier ,  Jean-Baptiste Passot ,  Borja Ibarz Gabardos ,  Patryk Laurent ,  Oleg Sinyavskiy ,  Peter O'Connor ,  Eugene Izhikevich

IPC: G05B19/04 ,  B25J9/16 ,  G06N99/00 ,  G06N3/00

CPC classification number: B25J9/163 ,  B25J9/1602 ,  B25J9/161 ,  B25J9/1656 ,  G05B2219/40116 ,  G05D1/0033 ,  G05D1/0088 ,  G05D2201/02 ,  G06N3/008 ,  G06N99/005 ,  Y10S901/01 ,  Y10S901/46

Abstract: Robots have the capacity to perform a broad range of useful tasks, such as factory automation, cleaning, delivery, assistive care, environmental monitoring and entertainment. Enabling a robot to perform a new task in a new environment typically requires a large amount of new software to be written, often by a team of experts. It would be valuable if future technology could empower people, who may have limited or no understanding of software coding, to train robots to perform custom tasks. Some implementations of the present invention provide methods and systems that respond to users' corrective commands to generate and refine a policy for determining appropriate actions based on sensor-data input. Upon completion of learning, the system can generate control commands by deriving them from the sensory data. Using the learned control policy, the robot can behave autonomously.

Abstract translation: 机器人有能力执行广泛的有用任务，如工厂自动化，清洁，交付，辅助护理，环境监测和娱乐。 使机器人在新环境中执行新任务通常需要大量新的软件来编写，通常由专家小组编写。 如果未来的技术可以赋予人们对软件编码有限或不了解的机会来训练机器人来执行定制任务，这将是有价值的。 本发明的一些实施方案提供了响应于用户的校正命令以生成和改进用于基于传感器数据输入确定适当动作的策略的方法和系统。 完成学习后，系统可以通过从感官数据中导出控制命令来生成控制命令。 使用学习的控制策略，机器人可以自主行为。

公开(公告)号：US20150350614A1

公开(公告)日：2015-12-03

申请号：US14332322

申请日：2014-07-15

Applicant: BRAIN CORPORATION

Inventor： Philip Meier ,  Heathcliff Hatcher ,  Marius Buibas

IPC: H04N7/18 ,  H04N5/28 ,  G06K9/00 ,  H04N5/232

CPC classification number: G06K9/00369 ,  G05D1/0094 ,  G06K9/0063 ,  H04N5/23229 ,  H04N5/23296 ,  H04N5/28 ,  H04N7/188

Abstract: In some implementations, a camera may be disposed on an autonomous aerial platform. A user may operate a smart wearable device adapted to configured, and/or operate video data acquisition by the camera. The camera may be configured to produce a time stamp, and/or a video snippet based on receipt of an indication of interest from the user. The aerial platform may comprise a controller configured to navigate a target trajectory space. In some implementation, a data acquisition system may enable the user to obtain video footage of the user performing an action from the platform circling around the user.

Abstract translation: 在一些实施方案中，照相机可以设置在自主空中平台上。 用户可以操作适于配置和/或操作由照相机进行的视频数据采集的智能可穿戴设备。 摄像机可以被配置为基于从用户接收感兴趣的指示而产生时间戳和/或视频片段。 空中平台可以包括被配置为导航目标轨迹空间的控制器。 在一些实现中，数据采集系统可以使得用户能够从围绕用户盘旋的平台获取执行动作的用户的视频素材。