A fundamental aspect to consider in factories is the transportation of the items at differentsteps in the production process. Conveyor belts do a great to bring items from point A topoint B but to load the item onto a working station it can demands a more precise and,in some cases, delicate approach. Nowadays this part is mostly handled by robotic arms.The issue encountered is that a robot arm extremity, its gripper, cannot directly instinctivelyknow how to grip an object. It is usually up to a technician to configure how andwhere the gripper goes to grip an item.The goal of this thesis is to analyse a problem given by a company which is to find a wayto automate the grasp pose synthesis of a new object with the adapted gripper.This automatized process can be separated into two sub-problems.First, how to choose the adapted gripper for a new object.Second, how to find a grasp pose on the object, with the previously chosen gripper.In the problem given by the company, the computer-aided design (CAD) 3D model of theconcerned object is given. Also, the grasp shall always be done vertically, i.e., the grippercomes vertically to the object and the gripper does not rotate on the x and y axis. Thegripper for a new object is selected between two kinds of grippers: two-finger paralleljawgripper and three-finger parallel-jaw gripper. No dataset of objects is provided.Object grasping is a well researched subject, especially for 2 finger grippers. However,few research is done for the 3 finger grippers grasp pose synthesis, or for gripper comparison,which are key part of the studied problem.To answer the sub-problems mentioned above, machine learning will be used for the gripperselection and a grasp synthesis method will be used for the grasp pose finding. However,due to the lack of gripper comparison in the related work, a new approach needsto be created, which will be inspired by the findings in the literature about grasp posesynthesis in general.This approach will consist of two parts.First, for each gripper and each object ...
New object grasp synthesis with gripper selection: process development
2022-01-01
Hochschulschrift
Elektronische Ressource
Englisch
DDC: | 629 |
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