A Note on Redesign Material Substitution and Topology Optimization in a Lightweight Robotic Gripper

The gripper is required because it is the portion of the robot that makes direct contact with the object being grasped. It should weigh as little as possible without compromising functionality or its performance. This study aims to reconsider the construction of a lightweight robotic gripper by modifying the gripper's materials and topology. Using the finite element (FE) method, several types of gripper materials were evaluated for static stress. On the basis of the results of the FE analysis, the optimal material candidate was chosen using the weighted objective method. Using the Fusion 360 software, the topology of the selected material was then optimized in an effort to achieve the 40% weight reduction’s objective. In addition, the suggested optimized geometry is then fine-tuned so that it can be manufactured as efficiently as possible. The final step in the validation of the robotic gripper's design was stress static analysis. The revised gripper design has a mass of 0.08 kg, a reduction of 94% from the original mass, and a safety factor of 3.67%, which satisfies the desired level of performance for the robotic gripper. Utilizing different materials and optimizing the gripper's topology can significantly reduce the overall mass of a robotic gripper. &nbsp

A cooperative mobile robot and manipulator system (Co-MRMS) for transport and lay-up of fibre plies in modern composite material manufacture

Composite materials are widely used in industry due to their light weight and specific performance. Currently, composite manufacturing mainly relies on manual labour and individual skills, especially in transport and lay-up processes, which are time consuming and prone to errors. As part of a preliminary investigation into the feasibility of deploying autonomous robotics for composite manufacturing, this paper presents a case study that investigates a cooperative mobile robot and manipulator system (Co-MRMS) for material transport and composite lay-up, which mainly comprises a mobile robot, a fixed-base manipulator and a machine vision sub-system. In the proposed system, marker-based and Fourier transform-based machine vision approaches are used to achieve high accuracy capability in localisation and fibre orientation detection respectively. Moreover, a particle-based approach is adopted to model material deformation during manipulation within robotic simulations. As a case study, a vacuum suction-based end-effector model is developed to deal with sagging effects and to quickly evaluate different gripper designs, comprising of an array of multiple suction cups. Comprehensive simulations and physical experiments, conducted with a 6-DOF serial manipulator and a two-wheeled differential drive mobile robot, demonstrate the efficient interaction and high performance of the Co-MRMS for autonomous material transportation, material localisation, fibre orientation detection and grasping of deformable material. Additionally, the experimental results verify that the presented machine vision approach achieves high accuracy in localisation (the root mean square error is 4.04 mm) and fibre orientation detection (the root mean square error is 1.84 18) and enables dealing with uncertainties such as the shape and size of fibre plies

Systematic gripper arrangement for a handling device in lightweight production processes

Handhabungsgeräte sind ein integraler Bestandteil automatisierter Produktionsprozesse. Dennoch werden sie in der Regel als nicht wertschöpfend angesehen, weshalb ihre Planung und Projektierung mit geringem Zeit- und Personalaufwand so effektiv wie möglich sein sollte. Gleichzeitig bleiben sie ein wichtiger Teil der Prozesskette und müssen in diesem Zusammenhang bestimmte Bedingungen erfüllen. Um ihre Funktionalität zu gewährleisten und wenig Zeit in die Projektierung zu investieren, sind Handhabungsgeräte oft überdimensioniert. Insbesondere bei flachen Teilen führt dies zu schweren Handhabungslösungen, bei denen das Gewicht des Handhabungsobjekts und des Handhabungsgerätes in einem Missverhältnis zueinander stehen. Ziel der vorliegenden Arbeit ist es, die Projektierung von Handhabungsgeräten so weit wie möglich zu automatisieren. Dieser Prozess wird am Beispiel der Prozesskette zur Herstellung von Leichtbauteilen mit den Verfahren „sheet molding compound“ (SMC) und „resin transfer molding“ (RTM) dargestellt. In einem ersten Schritt wird ein modulares Handhabungsgerät entwickelt und aufgebaut, das eine große Anzahl von Greiferanordnung ermöglicht. Mit diesem Handhabungsgerät kann dann die resultierende Durchbiegung von flachen Bauteilen mit verschiedenen Greiferanordnungen gemessen werden. Um sicherzustellen, dass es nicht immer notwendig ist die Durchbiegungen zu messen, wird mit ABAQUS ein Modell aufgebaut, das eine Simulation der Durchbiegung ermöglicht. Anhand dieses Simulationsmodells wird eine Designlogik für die Anordnung der Greifer entwickelt. Diese Designlogik arbeitet in zwei Schritten und basiert auf dem Ansatz des „growing neural gas“ (GNG), das durch die Implementierung zusätzlicher Regeln an das Problem angepasst wird. Zuerst wird eine erste Greiferkonfiguration basierend auf der Geometrie des Objekts erstellt, die dann durch einen iterativen Prozess aus Simulation und Anpassung verbessert wird. Da die Herstellung von Leichtbauteilen oft mehr als nur einen Zuschnitt erfordert, werden am Ende systematisch verschiedene Lösungen für die verschiedenen Zuschnitte zu einer Greiferanordnung zusammengefasst und ein Verfahren gezeigt, wie dies ,mit dem zuvor entwickelten modularen Handhabungsgerät realisiert, werden kann

Adhesion State Estimation for Electrostatic Gripper Based on Online Capacitance Measure

Electroadhesion is a suitable technology for developing grippers for applications where fragile, compliant or variable shape objects need to be grabbed and where a retention action is typically preferred to a compression force. This article presents a self-sensing technique for electroadhesive devices (EAD) based on the capacitance measure. Specifically, we demonstrate that measuring the variation of the capacitance between electrodes of an EAD during the adhesion can provide useful information to automatically detect the successful grip of an object and the possible loss of adhesion during manipulation. To this aim, a dedicated electronic circuit is developed that is able to measure capacitance variations while the high voltage required for the adhesion is activated. A test bench characterization is presented to evaluate the self-sensing of capacitance during different states: (1) the EAD is far away from the object to be grasped; (2) the EAD is in contact with the object, but the voltage is not active (i.e., no adhesion); and (3) the EAD is activated and attached to the object. Correlation between the applied voltage, object material and shape and capacitance is made. The self-sensing EAD is then demonstrated in a closed-loop robotic application that employs a robot manipulator arm to pick and place objects of different kinds