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公开(公告)号：US20220212342A1
公开(公告)日：2022-07-07
申请号：US17574760
申请日：2022-01-13
Applicant: Brain Corporation
Inventor： Patryk Laurent , Jean-Baptiste Passot , Oleg Sinyavskiy , Filip Ponulak , Borja Ibarz Gabardos , Eugene Izhikevich
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.
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公开(公告)号：US20190302791A1
公开(公告)日：2019-10-03
申请号：US15942123
申请日：2018-03-30
Applicant: Brain Corporation
Abstract: Systems and methods for robotic mapping are disclosed. In some example implementations, an automated device can travel in an environment. From travelling in the environment, the automated device can create a graph comprising a plurality of nodes, wherein each node corresponds to a scan taken by one or more sensors of the automated device at a location in the environment. In some example embodiments, the automated device can reevaluate its travel along a desired path if it encounters objects or obstructions along its path, whether those objects or obstructions are present in the front, rare or side of the automated device. In some example embodiments, the automated device uses a timestamp methodology to maneuver around its environment that provides faster processing and less usage of memory space.
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公开(公告)号：US20190299410A1
公开(公告)日：2019-10-03
申请号：US16376237
申请日：2019-04-05
Applicant: BRAIN CORPORATION
Inventor： Oleg Sinyavskiy , Jean-Baptiste Passot , Borja Ibarz Gabardos , Diana Vu Le
Abstract: Systems and methods for robotic path planning are disclosed. In some implementations of the present disclosure, a robot can generate a cost map associated with an environment of the robot. The cost map can comprise a plurality of pixels each corresponding to a location in the environment, where each pixel can have an associated cost. The robot can further generate a plurality of masks having projected path portions for the travel of the robot within the environment, where each mask comprises a plurality of mask pixels that correspond to locations in the environment. The robot can then determine a mask cost associated with each mask based at least in part on the cost map and select a mask based at least in part on the mask cost. Based on the projected path portions within the selected mask, the robot can navigate a space.
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公开(公告)号：US10377040B2
公开(公告)日：2019-08-13
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
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.
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公开(公告)号：US10001780B2
公开(公告)日：2018-06-19
申请号：US15341612
申请日：2016-11-02
Applicant: BRAIN CORPORATION
Inventor： Borja Ibarz Gabardos , Jean-Baptiste Passot
CPC classification number: G05D1/0214 , A47L11/4011 , A47L11/4061 , A47L2201/04 , G01C21/3415 , G01C21/343 , G05D1/0088 , G05D1/0274 , G05D1/0276 , G05D2201/0203
Abstract: Systems and methods for dynamic route planning in autonomous navigation are disclosed. In some exemplary implementations, a robot can have one or more sensors configured to collect data about an environment including detected points on one or more objects in the environment. The robot can then plan a route in the environment, where the route can comprise one or more route poses. The route poses can include a footprint indicative at least in part of a pose, size, and shape of the robot along the route. Each route pose can have a plurality of points therein. Based on forces exerted on the points of each route pose by other route poses, objects in the environment, and others, each route pose can reposition. Based at least in part on interpolation performed on the route poses (some of which may be repositioned), the robot can dynamically route.
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Patent Agency Ranking
公开(公告)号：US20180001474A1
公开(公告)日：2018-01-04
申请号：US15199224
申请日：2016-06-30
Applicant: BRAIN CORPORATION
Inventor： Oleg Sinyavskiy , Borja Ibarz Gabardos , Jean-Baptiste Passot
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.
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7.发明申请APPARATUS AND METHODS FOR CONTROL OF ROBOT ACTIONS BASED ON CORRECTIVE USER INPUTS 有权基于正确的用户输入控制机器人动作的装置和方法公开(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
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。
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公开(公告)号：US11701778B2
公开(公告)日：2023-07-18
申请号：US17157897
申请日：2021-01-25
Applicant: BRAIN CORPORATION
Inventor： Oleg Sinyavskiy , Jean-Baptiste Passot , Borja Ibarz Gabardos , Diana Vu Le
CPC classification number: B25J9/1666 , A47L11/283 , A47L11/4008 , A47L11/4011 , A47L11/4061 , A47L11/4066 , B25J11/0085 , G01C21/3407 , G01C21/3804 , G05D1/0214 , G05D1/0217 , G05D1/0274 , G05D2201/0203
Abstract: Systems and methods for robotic path planning are disclosed. In some implementations of the present disclosure, a robot can generate a cost map associated with an environment of the robot. The cost map can comprise a plurality of pixels each corresponding to a location in the environment, where each pixel can have an associated cost. The robot can further generate a plurality of masks having projected path portions for the travel of the robot within the environment, where each mask comprises a plurality of mask pixels that correspond to locations in the environment. The robot can then determine a mask cost associated with each mask based at least in part on the cost map and select a mask based at least in part on the mask cost. Based on the projected path portions within the selected mask, the robot can navigate a space.
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公开(公告)号：US11340630B2
公开(公告)日：2022-05-24
申请号：US15942123
申请日：2018-03-30
Applicant: Brain Corporation
Abstract: Systems and methods for robotic mapping are disclosed. In some example implementations, an automated device can travel in an environment. From travelling in the environment, the automated device can create a graph comprising a plurality of nodes, wherein each node corresponds to a scan taken by one or more sensors of the automated device at a location in the environment. In some example embodiments, the automated device can reevaluate its travel along a desired path if it encounters objects or obstructions along its path, whether those objects or obstructions are present in the front, rare or side of the automated device. In some example embodiments, the automated device uses a timestamp methodology to maneuver around its environment that provides faster processing and less usage of memory space.
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公开(公告)号：US11224971B2
公开(公告)日：2022-01-18
申请号：US16447261
申请日：2019-06-20
Applicant: Brain Corporation
Inventor： Patryk Laurent , Jean-Baptiste Passot , Oleg Sinyavskiy , Filip Ponulak , Borja Ibarz Gabardos , Eugene Izhikevich
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.
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