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Model-Less Feedback Control of Continuum Manipulators in Constrained Environments

机译:受限环境中连续机械臂的模型较少反馈控制

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Continuum manipulators offer a means for robot manipulation in a constrained environment, where the manipulator body can safely interact with, comply with, and navigate around obstacles. However, obstacle interactions impose constraints that conform the robot body into arbitrary shapes regardless of actuator positions. Generally, these effects cannot be wholly sensed on a continuum manipulator and, therefore, render model-based controllers incorrect, leading to artificial singularities and unstable behavior. We present a task-space closed-loop controller for continuum manipulators that does not rely on a model and can be used in constrained environments. Using an optimal control strategy on a tendon-driven robot, we demonstrate this method, which we term model-less control, which allows the manipulator to interact with several constrained environments in a stable manner. To the best of our knowledge, this is the first work in controlling continuum manipulators without using a model.
机译:连续操纵器提供了一种在受限环境中进行机器人操纵的方法,在该环境中操纵器主体可以安全地与障碍物交互,顺从并在障碍物周围导航。但是,障碍物的交互作用会施加约束,使约束的机器人身成为任意形状,而与执行器位置无关。通常,这些效果不能在连续操纵器上完全感知到,因此会导致基于模型的控制器不正确,从而导致人为的奇异性和不稳定的行为。我们为连续操纵器提出了一个任务空间闭环控制器,该控制器不依赖模型,可以在受限环境中使用。在肌腱驱动的机器人上使用最佳控制策略,我们演示了这种方法,我们称其为“无模型控制”,它允许机械手以稳定的方式与多个受限环境进行交互。据我们所知,这是在不使用模型的情况下控制连续操纵器的第一项工作。

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