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Stiffness optimization for two-armed robotic sculpting

机译:双臂机器人雕刻的刚度优化

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Purpose - Recent research has considered robotic machining as a dextrous alternative to traditional CNC machine tools for complex sculptured surfaces. One challenge in using robotic machining is that the stiffness is lower than traditional machine tools, due to the cantilever design of the links and low-torsional stiffness of the actuators. This paper seeks to examine this limitation, using optimization algorithms to determine the best trajectories for the manipulators such that the stiffness is maximized. Design/methodology/approach - The issue of low stiffness is addressed with an integrated off-line planner and real-time re-planner. The available manipulator stiffness is maximized during off-line planning through a trajectory resolution method that exploits the nullspace of the robot machining system. In response to unmodeled disturbances, a real-time trajectory re-planner utilizes a time-scaling method to reduce the tool speed, thereby reducing the demand on the actuator torques, increasing the robot's dynamic stiffness capabilities. During real-time re-planning, priorities are assigned to conflicting performance criteria such as stiffness, collision avoidance, and joint limits. Findings - The algorithms developed were able to generate trajectories with stiffer configurations, which resulted in a reduction in the actuator torques. The real-time re-planner successfully allowed the process plan to continue when disturbances were encountered. Research limitations/implications - Simulations are presented to demonstrate the effectiveness of the approach. Practical implications - Addressing the limitation of stiffness in serial-link manipulators will enable robots to become more suitable for machining tasks. The real-time re-planning approach will allow robots to become more autonomous during the execution of a given task. Originality/value - An integrated off-line and real-time planning approach has been applied to robotic machining.
机译:目的-最近的研究已将机器人加工视为复杂雕刻表面的传统CNC机床的灵巧替代品。使用机械加工的一个挑战是,由于连杆的悬臂设计和致动器的低扭转刚度,其刚度要低于传统机床。本文试图通过使用优化算法来确定机械手的最佳轨迹,从而使刚度最大化,来研究这种限制。设计/方法/方法-通过集成的离线计划器和实时重新计划器解决了低刚度问题。通过使用机器人加工系统的零空间的轨迹解析方法,可以在离线计划期间最大化可用的机械手刚度。响应未建模的干扰,实时轨迹重新规划器利用时间缩放方法来降低工具速度,从而减少对执行器扭矩的需求,从而提高机器人的动态刚度能力。在实时重新计划期间,优先级被分配给冲突的性能标准,例如刚度,避免碰撞和关节极限。发现-开发的算法能够生成具有更硬配置的轨迹,从而降低了执行器扭矩。遇到问题时,实时重新计划程序成功地使过程计划得以继续。研究局限性/含义-进行仿真以证明该方法的有效性。实际意义-解决串行链接操纵器中刚度的局限性将使机器人变得更适合于加工任务。实时重新计划方法将使机器人在执行给定任务期间变得更加自主。原创性/价值-集成的离线和实时计划方法已应用于机器人加工。

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