公开(公告)号：US20170291301A1

公开(公告)日：2017-10-12

申请号：US15495804

申请日：2017-04-24

Applicant: Brain Corporation

Inventor： Borja Ibarz Gabardos ,  Andrew Smith ,  Peter O'Connor

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

CPC classification number: B25J9/163 ,  B25J9/0081 ,  B25J9/1602 ,  B25J9/1607 ,  B25J9/161 ,  B25J9/1666 ,  B25J9/1697 ,  G05D1/0088 ,  G05D1/0246 ,  G05D2201/02 ,  G06N3/00 ,  G06N3/008 ,  G06N3/049 ,  G06N20/00 ,  Y10S901/01 ,  Y10S901/03 ,  Y10S901/09 ,  Y10S901/47

Abstract: A robotic device may be operated by a learning controller comprising a feature learning configured to determine control signal based on sensory input. An input may be analyzed in order to determine occurrence of one or more features. Features in the input may be associated with the control signal during online supervised training. During training, learning process may be adapted based on training input and the predicted output. A combination of the predicted and the target output may be provided to a robotic device to execute a task. Feature determination may comprise online adaptation of input, sparse encoding transformations. Computations related to learning process adaptation and feature detection may be performed on board by the robotic device in real time thereby enabling autonomous navigation by trained robots.

公开(公告)号：US09630318B2

公开(公告)日：2017-04-25

申请号：US14542391

申请日：2014-11-14

Applicant: Brain Corporation

Inventor： Borja Ibarz Gabardos ,  Andrew Smith ,  Peter O'Connor

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

CPC classification number: B25J9/163 ,  B25J9/1607 ,  B25J9/1666 ,  B25J9/1697 ,  G05D1/0088 ,  G05D1/0246 ,  G05D2201/02 ,  G06N3/00 ,  G06N3/008 ,  G06N3/049 ,  Y10S901/01 ,  Y10S901/03 ,  Y10S901/09 ,  Y10S901/47

Abstract: A robotic device may be operated by a learning controller comprising a feature learning configured to determine control signal based on sensory input. An input may be analyzed in order to determine occurrence of one or more features. Features in the input may be associated with the control signal during online supervised training. During training, learning process may be adapted based on training input and the predicted output. A combination of the predicted and the target output may be provided to a robotic device to execute a task. Feature determination may comprise online adaptation of input, sparse encoding transformations. Computations related to learning process adaptation and feature detection may be performed on board by the robotic device in real time thereby enabling autonomous navigation by trained robots.

公开(公告)号：US11691289B2

公开(公告)日：2023-07-04

申请号：US16030690

申请日：2018-07-09

Applicant: Brain Corporation

Inventor： Oleg Sinyavskiy ,  Borja Ibarz Gabardos ,  Jean-Baptiste Passot

IPC: B25J9/16 ,  B25J5/00

CPC classification number: B25J9/1676 ,  B25J5/007 ,  B25J9/1697 ,  G05B2219/40442 ,  G05B2219/49143 ,  G05B2219/49157 ,  Y10S901/01

Abstract: Systems and methods for detection of people are disclosed. In some exemplary implementations, a robot can have a plurality of sensor units. Each sensor unit can be configured to generate sensor data indicative of a portion of a moving body at a plurality of times. Based on at least the sensor data, the robot can determine that the moving body is a person by at least detecting the motion of the moving body and determining that the moving body has characteristics of a person. The robot can then perform an action based at least in part on the determination that the moving body is a person.

公开(公告)号：US20220026911A1

公开(公告)日：2022-01-27

申请号：US17409274

申请日：2021-08-23

Applicant: Brain Corporation

Inventor： Oleg Sinyavskiy ,  Borja Ibarz Gabardos ,  Jean-Baptiste Passot

IPC: G05D1/02

Abstract: The safe operation and navigation of robots is an active research topic for many real-world applications, such as the automation of large industrial equipment. This technological field often requires heavy machines with arbitrary shapes to navigate very close to obstacles, a challenging and largely unsolved problem. To address this issue, a new planning architecture is developed that allows wheeled vehicles to navigate safely and without human supervision in cluttered environments. The inventive methods and systems disclosed herein belong to the Model Predictive Control (MPC) family of local planning algorithms. The technological features disclosed herein works in the space of two-dimensional (2D) occupancy grids and plans in motor command space using a black box forward model for state inference. Compared to the conventional methods and systems, the inventive methods and systems disclosed herein include several properties that make it scalable and applicable to a production environment. The inventive concepts disclosed herein are at least deterministic, computationally efficient, run in constant time and can be deployed in many common non-holonomic systems.

公开(公告)号：US11099575B2

公开(公告)日：2021-08-24

申请号：US16260590

申请日：2019-01-29

Applicant: Brain Corporation

Inventor： Oleg Sinyavskiy ,  Borja Ibarz Gabardos ,  Jean-Baptiste Passot

IPC: G05D1/02

Abstract: The safe operation and navigation of robots is an active research topic for many real-world applications, such as the automation of large industrial equipment. This technological field often requires heavy machines with arbitrary shapes to navigate very close to obstacles, a challenging and largely unsolved problem. To address this issue, a new planning architecture is developed that allows wheeled vehicles to navigate safely and without human supervision in cluttered environments. The inventive methods and systems disclosed herein belong to the Model Predictive Control (MPC) family of local planning algorithms. The technological features disclosed herein works in the space of two-dimensional (2D) occupancy grids and plans in motor command space using a black box forward model for state inference. Compared to the conventional methods and systems, the inventive methods and systems disclosed herein include several properties that make it scalable and applicable to a production environment. The inventive concepts disclosed herein are at least deterministic, computationally efficient, run in constant time and can be deployed in many common non-holonomic systems.

公开(公告)号：US20190030713A1

公开(公告)日：2019-01-31

申请号：US16150609

申请日：2018-10-03

Applicant: Brain Corporation

Inventor： Borja Ibarz Gabardos ,  Oleg Sinyavskiy

IPC: B25J9/16

Abstract: An apparatus and methods for training and/or operating a robotic device to perform a target task autonomously. The target task execution may be configured based on analysis of sensory context by the robot. Target action may comprise execution of two or more mutually exclusive actions for a given context. The robotic device may be operable in accordance with a persistent switching process. For a given sensor input, the switching process may be trained to select one of two or more alternative actions based on a prior action being executed. Switching process operation may comprise assigning priorities to the available tasks based on the sensory context; the task priorities may be modified during training based on input from a trainer. The predicted task priorities may be filtered by a “persistent winner-take-all process configured to switch from a current task to another task based on the priority breaching a switching threshold.

公开(公告)号：US20180215039A1

公开(公告)日：2018-08-02

申请号：US15423442

申请日：2017-02-02

Applicant: BRAIN CORPORATION

Inventor： Oleg Sinyavskiy ,  Jean-Baptiste Passot ,  Borja Ibarz Gabardos ,  Diana Vu Le

IPC: B25J9/16

CPC classification number: B25J9/1666 ,  G05B2219/39082 ,  G05D1/0044 ,  G05D1/0274 ,  G05D2201/0203

Abstract: Systems and methods assisting a robotic apparatus are disclosed. In some exemplary implementations, a robot can encounter situations where the robot cannot proceed and/or does not know with a high degree of certainty it can proceed. Accordingly, the robot can determine that it has encountered an error and/or assist event. In some exemplary implementations, the robot can receive assistance from an operator and/or attempt to resolve the issue itself. In some cases, the robot can be configured to delay actions in order to allow resolution of the error and/or assist event.

公开(公告)号：US20170329347A1

公开(公告)日：2017-11-16

申请号：US15152425

申请日：2016-05-11

Applicant: Brain Corporation

Inventor： Jean-Baptiste Passot ,  Andrew Smith ,  Botond Szatmary ,  Borja Ibarz Gabardos ,  Cody Griffin ,  Jaldert Rombouts ,  Oleg Sinyavskiy ,  Eugene Izhikevich

IPC: G05D1/02 ,  A47L11/40 ,  G05D1/00

CPC classification number: G05D1/0274 ,  A47L9/2826 ,  A47L9/2852 ,  A47L11/4011 ,  A47L11/4061 ,  A47L2201/04 ,  G05D1/0088 ,  G05D1/0221 ,  G05D1/0246 ,  G05D2201/0203

Abstract: Systems and methods for training a robot to autonomously travel a route. In one embodiment, a robot can detect an initial placement in an initialization location. Beginning from the initialization location, the robot can create a map of a navigable route and surrounding environment during a user-controlled demonstration of the navigable route. After the demonstration, the robot can later detect a second placement in the initialization location, and then autonomously navigate the navigable route. The robot can then subsequently detect errors associated with the created map. Methods and systems associated with the robot are also disclosed.

公开(公告)号：US09792546B2

公开(公告)日：2017-10-17

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 ,  G06N3/04 ,  G06N3/00

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.

公开(公告)号：US20160303738A1

公开(公告)日：2016-10-20

申请号：US15132003

申请日：2016-04-18

Applicant: BRAIN Corporation

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

IPC: 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。