Dynamic grasping of manipulator based on realtime smooth trajectory generation

Abstract

For safe and effective grasping in a dynamic environment, planning algorithms need real-time to deal with changing the target’s movement and obstacles. This paper proposes a new sequential Sense-Plan-Act (SeqSPA) dynamic grasping framework to generate a robot’s real-time and smooth grasping trajectory. Specifically, we cluster all stable grasps of the target, transform the clustering centers into pregrasps, and predict the future motion of the moving objects by using the observed values. The trajectory optimization algorithm constructing the approximative joint space gradient field can generate a smooth trajectory for a 6-DOF industrial robot arm within 2 ms. Our method generates trajectories for multiple pregrasps and selects the time-optimal trajectory for execution. Simulation comparison and actual experiments verify that our framework can immediately respond to environmental changes and efficiently find a grasping trajectory of the near-optimal time. The trajectory optimization algorithm in the framework can also be used alone to generate a real-time grasping trajectory when the prediction module cannot accurately predict the target motion.

A collision-free visual servoing method for two space manipulators capturing tumbling satellites

“…39,40 Online optimal motion planning methods are investigated to smooth the manipulator trajectory for tracking the moving target. 41,42 However, such methods do not take into account the simultaneity of two-arms planning and usually do not consider real non-cooperative measurements, simplifying the features to be identified to cooperative markers. On the other hand, trajectories can be directly planned in image space, by establishing a Jacobian matrix mapped from image features to the kinematic model of the manipulator, visual servoing is accomplished according to the change of the image.…”