首页> 外文会议>Intelligent Control, 1994., Proceedings of the 1994 IEEE International Symposium on >Sensor-based online trajectory generation for smoothly grasping moving objects
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Sensor-based online trajectory generation for smoothly grasping moving objects

机译:基于传感器的在线轨迹生成,可平稳地抓取运动物体

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Presents a new approach to online trajectory planning for target tracking, dynamic grasping and catching. The robot executes a geometric controller-it simply evaluates a nonlinear function which maps the currently measured position and velocity of the object to be grasped into a current desired robot pose. If the robot tracks these setpoints, it is guaranteed to match the object's velocity and acceleration on a specified grasp surface. The authors develop a geometric controller which specifies the full 6DOF position and orientation of the robot's end effector. A planar simulation demonstrates that this paradigm performs favorably when compared with the traditional planning approach. Since it does not depend on future object measurements, no object model is needed for trajectory prediction. Without trajectory prediction, the computational effort is drastically reduced, allowing for higher controller speed and tracking feedback gains. At the same time this approach provides a framework for general sensor based control of robotic tasks.
机译:为目标跟踪,动态抓握和捕捉提供了一种新的在线轨迹规划方法。机器人执行几何控制器 - 简单地评估将当前测量的位置和速度映射到电流所需的机器人姿势的当前测量的位置和速度。如果机器人跟踪这些设定值,则保证将对象的速度和加速度匹配指定的掌握。作者开发了一个几何控制器,该控制器指定机器人末端执行器的完整6dof位置和方向。平面模拟表明,与传统的规划方法相比,这种范例有利地执行。由于它不依赖于未来的对象测量,因此轨迹预测需要对象模型。没有轨迹预测,计算工作大大减少,允许更高的控制器速度和跟踪反馈增益。同时,这种方法为基于一般传感器的控制控制机器人任务提供了框架。

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