INTELLIGENT ROBOTIC GRIPPER WITH AN ADAPTIVE GRASP TECHNIQUE

Abstract

This thesis presents a robotic gripper with an intelligent sensor system to grasp objects with an adaptive grasp technique. Two techniques are used, one for small objects and one for large objects. The sensor system is able to detect the object and measure its size to adapt the grasp. Optical motion sensors are used to see when the object is slipping between the fingers which means that more force needs to be applied. This makes it possible to grasp rigid and soft objects without damaging them. The functionality of the gripper was tested on eight objects with various characteristics. The results show that it can adapt the grasp technique and grasping force to the objects’ size and softness. It also shows that adding one more grasp technique made it possible to grasp more objects, compared to a different gripper with a single grasp technique which were used as a foundation for this thesis.