Design of the hybrid gripper with the jaw-tip grip and suction
End effectors are disposed in the end of the manipulator. And the end effectors do physical contact with target materials for doing assigned and required tasks. On the analysis of requirements for assigned tasks, there is one gripper should handle the solid material and soft material together. In the pick and place task, it is better to do suctions than grips. For this need, in this paper, we describe the proposed gripper that can do grip the solid material and absorb the soft material. Further the proposed gripper has linear motion guide (LM guide) and electric motor for linear displacements. This leads to various suction strategies.
A robust soft and vacuum hybrid end-effector and compliant arm for picking in clutter
OF THE THESIS A Robust Soft and Vacuum Hybrid End-Effector and Compliant Arm for Picking in Clutter by Hristiyan Kourtev Thesis Director: Kostas Bekris Robotic grasping has been an active area of research since the dawn of robotics. With recent advancements in artificial intelligence, vision, planning and machine learning, robots are beginning to enter unstructured and unknown environments, such as warehouses. Warehouse automation and, in particular, picking, is an increasingly popular application domain due to its significance in logistics operations. It usually involves a robot picking a list of items from a shelf, often in parallel with human workers. Different items are usually packed close together in bins and require an end-effector that is small and versatile. Due to the constrained and unstructured nature of the corresponding workspace, sometimes collisions with the environment are not easily avoidable. This thesis outlines the design and fabrication of a hybrid end-effector that uses both suction and mechanical grasping courtesy of soft-robotics inspired fingers mounted on a flexible arm extension, both of which very robust and capable of sustaining multiple collisions without failure, which could otherwise be expensive and time-consuming. Furthermore, the combination of suction, grasping and soft robotics is a novel idea and offers additional benefits such as low weight and inexpensive components.
Design of a six-axis wrist force/moment sensor using FEM and its fabrication for an intelligent robot
Abstract This paper describes the design of a six-axis force/moment sensor using FEM (finite element method) and its fabrication. In order to safely grasp an unknown object using an intelligent hand in robot, the hand has to perceive the weight of it. The weight is calculated by forces F x , F y , F z measured from the six-axis wrist force/moment sensor attached to an intelligent robot's hand. And, in order to accurately push and pull an object, forces and moments should be measured. Also, the position of the robot's finger contacted on an object are calculated by forces F x , F y and F z , and moments M x , M y and M z measured from the six-axis wrist force/moment sensor. Therefore, an intelligent robot's hand should get a six-axis wrist force/moment sensor that can measure forces F x , F y and F z , and moments M x , M y and M z simultaneously. The size of the six-axis force/moment sensor for an intelligent robot’ wrist is very important. If its diameter is larger or its thickness (length) is longer, it cannot be mounted in robot's wrist or it will break down under the applied moment M x or M y . So, its size is similar to that of the wrist of human being, that is, the diameter is about 60–80 mm and the thickness (length) about 20–40 mm. But the manufactured sensors are not proper in size for the intelligent robot's wrist. Thus, the six-axis force/moment sensor should be developed for the intelligent robot's wrist. In this paper, the structure of a six-axis wrist force/moment sensor was modeled for an intelligent hand in robot newly. And the sensing elements of it were designed by using FEM and were fabricated by attaching strain-gages on the sensing elements. And, the characteristic test of the developed sensor was carried out. The rated outputs from FEM analysis agree well with the results from the experiments. The interference error of the sensor is less than 2.85%.