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Sensor-based online trajectory generation for smoothly grasping moving objects

M. Zhang, M. Buehler

Year
2002
Citations
23

Abstract

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.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Keywords

TrajectoryGRASPController (irrigation)Computer scienceRobotObject (grammar)Position (finance)Computer visionArtificial intelligenceAcceleration

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