23 research outputs found
Manipulation Planning and Control for Shelf Replenishment
Manipulation planning and control are relevant building blocks of a robotic
system and their tight integration is a key factor to improve robot autonomy
and allows robots to perform manipulation tasks of increasing complexity, such
as those needed in the in-store logistics domain. Supermarkets contain a large
variety of objects to be placed on the shelf layers with specific constraints,
doing this with a robot is a challenge and requires a high dexterity. However,
an integration of reactive grasping control and motion planning can allow
robots to perform such tasks even with grippers with limited dexterity. The
main contribution of the paper is a novel method for planning manipulation
tasks to be executed using a reactive control layer that provides more control
modalities, i.e., slipping avoidance and controlled sliding. Experiments with a
new force/tactile sensor equipping the gripper of a mobile manipulator show
that the approach allows the robot to successfully perform manipulation tasks
unfeasible with a standard fixed grasp.Comment: 8 pages, 12 figures, accepted at RA