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    • 1. 发明授权
    • Learning system and method for optimizing control of autonomous
earthmoving machinery
    • 优化自主移土机械控制的学习系统和方法
    • US6076030A
    • 2000-06-13
    • US173074
    • 1998-10-14
    • Patrick S. Rowe
    • Patrick S. Rowe
    • B25J9/22E02F3/43E02F9/20E02F9/24G05B13/02G05B19/19G06F19/00
    • E02F9/2045E02F3/435E02F3/438E02F9/2033E02F9/245G05B13/0265G05B19/19G05B2219/33032
    • In one embodiment of the present invention, a motion planning algorithm is used to control an autonomous machine. The motion planning algorithm consists of a template or script which captures the general trends of the motion, while parameters in the script are filled in with the kinematic details for a specific machine and set of movements. A learning algorithm computes the script parameters by using feedback of how the machine performed during the preceding cycle with the current parameter set, and adjusting the parameters to improve the machine's performance during succeeding work cycles. The new parameters are evaluated by the learning algorithm using a predictive function approximator to test various performance criteria such as the time required to perform a task and the accuracy with which the task was performed. The performance criteria are weighted using local regression techniques so that the prediction of the outcome of alternate motions places emphasis on the performance criteria that is considered most important. As data from repeated motions accumulates, the algorithm uses the history of the results of various motions to recompute and refine the parameters to improve performance.
    • 在本发明的一个实施例中,使用运动规划算法来控制自主机器。 运动规划算法由一个模板或脚本组成,它捕捉运动的一般趋势,而脚本中的参数则填充有特定机器的运动细节和一组运动。 学习算法通过使用机器在前一周期内执行的当前参数集的反馈来计算脚本参数,并调整参数以提高机器在后续工作循环中的性能。 通过使用预测函数逼近器的学习算法评估新参数,以测试执行任务所需的时间和执行任务的准确性的各种性能标准。 使用局部回归技术对绩效标准进行加权,以便对替代运动结果的预测将重点放在被认为最重要的绩效标准上。 随着重复运动的数据积累,该算法使用各种运动结果的历史来重新计算和细化参数以提高性能。
    • 2. 发明授权
    • Automated system and method for control of movement using parameterized
scripts
    • 使用参数化脚本控制运动的自动化系统和方法
    • US6058344A
    • 2000-05-02
    • US322849
    • 1999-05-28
    • Patrick S. RoweAnthony J. Stentz
    • Patrick S. RoweAnthony J. Stentz
    • E02F9/20B25J9/16B25J9/18B25J9/22G05D3/10B05B9/06
    • B25J9/1658E02F3/437E02F9/2041G05B2219/35263
    • Robotic machines, such as mobile manipulators, are controlled by a relatively high-level script while changes in the environment are accommodated by including parameters in the script. Sensors, manual inputs, and other software can be used as sources of data for setting the values of the parameters. The high-level script includes sets of instructions with each set defining movement of one portion of the robotic machine, such as a joint of the manipulator. The several sets of instructions are executed concurrently in a primary script. One or more secondary scripts, each containing concurrently executed sets of instructions may be executed when an abnormal condition is detected. The movements performed by the robotic machine are generally defined by the instructions, but precisely how the movements are performed is determined by the values of the parameters. By using parameterized scripts, it is unnecessary to compute and track trajectories.
    • 诸如移动操纵器的机器人机器由相对高级的脚本控制,同时通过在脚本中包括参数来适应环境的变化。 传感器,手动输入和其他软件可用作设置参数值的数据源。 高级脚本包括指令集,每组指令定义机器人机器的一部分的运动,例如操纵器的关节。 几组指令在主脚本中同时执行。 当检测到异常情况时,可以执行一个或多个辅助脚本,每个副脚本包含并发执行的指令集。 由机器人机器执行的动作通常由指令定义,但精确地如何执行移动由参数的值确定。 通过使用参数化脚本,无需计算和跟踪轨迹。