公开(公告)号：US10274325B2

公开(公告)日：2019-04-30

申请号：US15340807

申请日：2016-11-01

Applicant: BRAIN CORPORATION

Inventor： Jaldert Rombouts ,  Borja Ibarz Gabardos ,  Jean-Baptiste Passot ,  Andrew Smith

IPC: G01C21/32 ,  G01S17/89 ,  G01S15/89

Abstract: Systems and methods for robotic mapping are disclosed. In some exemplary implementations, a robot can travel in an environment. From travelling in the environment, the robot can create a graph comprising a plurality of nodes, wherein each node corresponds to a scan taken by a sensor of the robot at a location in the environment. In some exemplary implementations, the robot can generate a map of the environment from the graph. In some cases, to facilitate map generation, the robot can constrain the graph to start and end at a substantially similar location. The robot can also perform scan matching on extended scan groups, determined from identifying overlap between scans, to further determine the location of features in a map.

公开(公告)号：US20180120116A1

公开(公告)日：2018-05-03

申请号：US15340807

申请日：2016-11-01

Applicant: BRAIN CORPORATION

Inventor： Jaldert Rombouts ,  Borja Ibarz Gabardos ,  Jean-Baptiste Passot ,  Andrew Smith

IPC: G01C21/32 ,  B25J9/16

CPC classification number: G01C21/32 ,  G01S15/89 ,  G01S17/89

Abstract: Systems and methods for robotic mapping are disclosed. In some exemplary implementations, a robot can travel in an environment. From travelling in the environment, the robot can create a graph comprising a plurality of nodes, wherein each node corresponds to a scan taken by a sensor of the robot at a location in the environment. In some exemplary implementations, the robot can generate a map of the environment from the graph. In some cases, to facilitate map generation, the robot can constrain the graph to start and end at a substantially similar location. The robot can also perform scan matching on extended scan groups, determined from identifying overlap between scans, to further determine the location of features in a map.

公开(公告)号：US09384443B2

公开(公告)日：2016-07-05

申请号：US13918338

申请日：2013-06-14

Applicant: BRAIN CORPORATION

Inventor： Jean-Baptiste Passot ,  Oleg Sinyavskiy ,  Filip Ponulak ,  Patryk Laurent ,  Borja Ibarz Gabardos ,  Eugene Izhikevich

IPC: B25J9/16 ,  G06N3/00 ,  G05D1/02 ,  G06N3/04

CPC classification number: B25J9/163 ,  B25J9/161 ,  G05D1/0221 ,  G06N3/008 ,  G06N3/049 ,  G06N3/08

Abstract: Apparatus and methods for training of robotic devices. Robotic devices may be trained by a user guiding the robot along target trajectory using an input signal. A robotic device may comprise an adaptive controller configured to generate control commands based on one or more of the user guidance, sensory input, and/or performance measure. Training may comprise a plurality of trials. During first trial, the user input may be sufficient to cause the robot to complete the trajectory. During subsequent trials, the user and the robot's controller may collaborate so that user input may be reduced while the robot control may be increased. Individual contributions from the user and the robot controller during training may be may be inadequate (when used exclusively) to complete the task. Upon learning, user's knowledge may be transferred to the robot's controller to enable task execution in absence of subsequent inputs from the user.

Abstract translation: 用于训练机器人装置的装置和方法。 机器人装置可以由用户使用输入信号沿目标轨迹引导机器人进行训练。 机器人设备可以包括自适应控制器，其被配置为基于用户引导，感觉输入和/或性能测量中的一个或多个来产生控制命令。 培训可能包括多项试验。 在第一次试用期间，用户输入可能足以使机器人完成轨迹。 在随后的试验期间，用户和机器人的控制器可以协作，以便可以减少用户输入，同时可以增加机器人控制。 在训练期间来自用户和机器人控制器的个人贡献可能不足以（完全用于完成任务）。 在学习之后，用户的知识可以传送到机器人的控制器，以便在没有用户的后续输入的情况下执行任务执行。

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：US09314924B1

公开(公告)日：2016-04-19

申请号：US13918620

申请日：2013-06-14

Applicant: BRAIN CORPORATION

Inventor： Patryk Laurent ,  Jean-Baptiste Passot ,  Oleg Sinyavskiy ,  Filip Ponulak ,  Borja Ibarz Gabardos ,  Eugene Izhikevich

IPC: G05B19/18 ,  B25J9/16

CPC classification number: B25J9/163 ,  G05B2219/39271 ,  G05B2219/39289 ,  G06N3/008 ,  G06N3/049

Abstract: Robotic devices may be trained by a user guiding the robot along target action trajectory using an input signal. A robotic device may comprise an adaptive controller configured to generate control signal based on one or more of the user guidance, sensory input, performance measure, and/or other information. Training may comprise a plurality of trials, wherein for a given context the user and the robot's controller may collaborate to develop an association between the context and the target action. Upon developing the association, the adaptive controller may be capable of generating the control signal and/or an action indication prior and/or in lieu of user input. The predictive control functionality attained by the controller may enable autonomous operation of robotic devices obviating a need for continuing user guidance.

Abstract translation: 机器人设备可以由用户使用输入信号沿着目标动作轨迹引导机器人进行训练。 机器人设备可以包括自适应控制器，其被配置为基于用户引导，感觉输入，性能测量和/或其他信息中的一个或多个来产生控制信号。 培训可以包括多个试验，其中对于给定的上下文，用户和机器人的控制器可以协作以在上下文和目标动作之间建立关联。 在开发关联时，自适应控制器可以能够在用户输入之前和/或代替用户输入时产生控制信号和/或动作指示。 由控制器获得的预测控制功能可以实现机器人设备的自主操作，从而避免需要持续的用户指导。

公开(公告)号：US20140371912A1

公开(公告)日：2014-12-18

申请号：US13918298

申请日：2013-06-14

Applicant: BRAIN CORPORATION

Inventor： Jean-Baptiste Passot ,  Oleg Sinyavskiy ,  Filip Ponulak ,  Patryk Laurent ,  Borja Ibarz Gabardos ,  Eugene Izhikevich ,  Vadim Polonichko

IPC: B25J9/16

CPC classification number: G06N3/049 ,  G06N3/008

Abstract: A robot may be trained by a user guiding the robot along target trajectory using a control signal. A robot may comprise an adaptive controller. The controller may be configured to generate control commands based on the user guidance, sensory input and a performance measure. A user may interface to the robot via an adaptively configured remote controller. The remote controller may comprise a mobile device, configured by the user in accordance with phenotype and/or operational configuration of the robot. The remote controller may detect changes in the robot phenotype and/or operational configuration. The remote controller may comprise multiple control elements configured to activate respective portions of the robot platform. Based on training, the remote controller may configure composite controls configured based two or more of control elements. Activation of a composite control may enable the robot to perform a task.

Abstract translation: 机器人可以由使用者使用控制信号沿目标轨迹引导机器人的用户进行训练。 机器人可以包括自适应控制器。 控制器可以被配置为基于用户指导，感觉输入和性能测量来产生控制命令。 用户可以通过自适应配置的遥控器与机器人接口。 遥控器可以包括由用户根据机器人的表型和/或操作配置来配置的移动设备。 遥控器可以检测机器人表型和/或操作配置的变化。 遥控器可以包括配置成激活机器人平台的相应部分的多个控制元件。 基于培训，遥控器可以配置基于两个或多个控制元件的复合控制。 激活复合控件可以使机器人执行任务。