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    • 3. 发明申请
    • SYSTEMS AND METHODS FOR ROBOTIC MAPPING
    • 用于机器人映射的系统和方法
    • WO2018085291A1
    • 2018-05-11
    • PCT/US2017/059376
    • 2017-10-31
    • BRAIN CORPORATION
    • ROMBOUTS, JaldertGABARDOS, Borja, IbarzPASSOT, Jean-BaptisteSMITH, Andrew
    • G05D1/00G05D1/02G05D1/12
    • 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.
    • 公开了用于机器人映射的系统和方法。 在一些示例性实现中,机器人可以在环境中行进。 从在环境中行进,机器人可以创建包括多个节点的图形,其中每个节点对应于机器人在环境中的位置处的传感器所进行的扫描。 在一些示例性实施方式中,机器人可以从图形生成环境地图。 在某些情况下,为了便于生成地图,机器人可以限制图形在大致相似的位置开始和结束。 机器人还可以通过识别扫描之间的重叠来确定扩展扫描组上的扫描匹配,以进一步确定地图中要素的位置。
    • 9. 发明申请
    • REDUCED DEGREE OF FREEDOM ROBOTIC CONTROLLER APPARATUS AND METHODS
    • 自由度机器人控制器设备和方法的降低程度
    • WO2015116270A2
    • 2015-08-06
    • PCT/US2014/063540
    • 2014-10-31
    • BRAIN CORPORATION
    • PASSOT, Jean-BaptisteSINYAVSKIY, OlegIZHIKEVICH, Eugene
    • B25J9/16
    • G06N3/008G06N3/049G06N99/005
    • Apparatus and methods for training and controlling of, for instance, robotic devices. In one implementation, a robot may be trained by a user using supervised learning. The user may be unable to control all degrees of freedom of the robot simultaneously. The user may interface to the robot via a control apparatus configured to select and operate a subset of the robot's complement of actuators. The robot may comprise an adaptive controller comprising a neuron network. The adaptive controller may be configured to generate actuator control commands based on the user input and output of the learning process. Training of the adaptive controller may comprise partial set training. The user may train the adaptive controller to operate first actuator subset. Subsequent to learning to operate the first subset, the adaptive controller may be trained to operate another subset of degrees of freedom based on user input via the control apparatus.
    • 用于训练和控制例如机器人装置的装置和方法。 在一个实现中,可以由使用监督学习的用户训练机器人。 用户可能无法同时控制机器人的所有自由度。 用户可以通过配置成选择和操作机器人的执行器补码的子集的控制装置与机器人接口。 机器人可以包括包括神经元网络的自适应控制器。 自适应控制器可以被配置为基于学习过程的用户输入和输出来生成致动器控制命令。 自适应控制器的训练可以包括部分组训练。 用户可以训练自适应控制器来操作第一致动器子集。 在学习操作第一子集之后,可以训练自适应控制器以基于经由控制装置的用户输入来操作另一自由度子集。