Dynamic grasp and trajectory planning for moving objects
Research output: Contribution to journal › Article
- KUKA Robotics UK Ltd. Wednesbury.
This paper shows how a robot arm can follow and grasp moving objects tracked by a vision system, as is needed when a human hands over an object to the robot during collaborative working. While the object is being arbitrarily moved by the human co-worker, a set of likely grasps, generated by a learned grasp planner, are evaluated online to generate a feasible grasp with respect to both: the current conﬁguration of the robot respecting the target grasp; and the constraints of ﬁnding a collision-free trajectory to reach that conﬁguration. A task-based cost function enables relaxation of motion-planning constraints, enabling the robot to continue following the object by maintaining its end-eﬀector near to a likely pre-grasp position throughout the object’s motion. We propose a method of dynamic switching between: a local planner, where the hand smoothly tracks the object, maintaining a steady relative pre-grasp pose; and a global planner, which rapidly moves the hand to a new grasp on a completely diﬀerent part of the object, if the previous graspable part becomes unreachable. Various experiments are conducted using a real collaborative robot and the obtained results are discussed.
|Number of pages||14|
|Early online date||20 Aug 2018|
|Publication status||E-pub ahead of print - 20 Aug 2018|
- Human–robot collaboration, Grasp planning, Motion planning, Grasping, Pose tracking