Optimization Model for Planning Precision Grasps with Multi-Fingered Hands

Precision grasps with multi-fingered hands are important for precise placement and in-hand manipulation tasks. Searching precision grasps on the object represented by point cloud, is challenging due to the complex object shape, high-dimensionality, collision and undesired properties of the sensing and positioning. This paper proposes an optimization model to search for precision grasps with multi-fingered hands. The model takes noisy point cloud of the object as input and optimizes the grasp quality by iteratively searching for the palm pose and finger joints positions. The collision between the hand and the object is approximated and penalized by a series of least-squares. The collision approximation is able to handle the point cloud representation of the objects with complex shapes. The proposed optimization model is able to locate collision-free optimal precision grasps efficiently. The average computation time is 0.50 sec/grasp. The searching is robust to the incompleteness and noise of the point cloud. The effectiveness of the algorithm is demonstrated by experiments.Comment: Submitted to IROS2019, experiment on BarrettHand, 8 page

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

Combining the functionality of multiple automatic cells by introducing a dual-arm robot station

The industrial revolution 4.0 is resulting in a shift of production and manufacturing processes to become more efficient and streamlined. This involves the refurnishing and upgrading of existing technology in production lines. Significant research done in the field of dual-arm robot manipulators shows us that anthropomorphic robots can be used interchangeably or replace humans, without major changes to the workplace, resulting in low cost, flexible automation and increased functionality. This thesis implementation aims to merge the functionalities of two automatic workstations by upgrading the elements of one of the workstations and removing the other workstation from the line. Based on the available resources and existent in-lab facilities, the prime objective is to determine the most efficient means to utilize a dual-arm manipulator to combine and update the functionalities of these two individual cells. And, how best to create exposure, by demonstrating the operations and features of the relatively unacquainted breed of industrial robots to new generations of students. This thesis focuses on the virtual implementation of the dual-arm station and the process flow is modelled and simulated, as proof of concept. The physical implementation would be carried out subsequently. Based on an extensive analysis of relevant literature, manipulator capabilities, in-house fabrication and purchasing feasibilities; the most efficient implementation was made after multiple iterative changes in cell and tooling design, and the process was created using the offline programming tool. The created dual-arm cell has replaced two individual robot manipulators and additional conveyor systems and acts as both, a production and an Automatic Storage and Retrieval System (AS/RS) unit, additionally it enables the intelligent production line (where the cell is being installed) to interact with other isolated intelligent systems in the laboratory. The introduced changes to the production line have increased its functionality, while removing obsolete equipment. The production efficiency is increased while reducing the space utilized and demonstrates the operation of a dual-arm industrial robots. Future works to improve the operations in the cell may include using anthropomorphic hands as tooling and utilizing intelligent vision systems to additionally handle deformable linear objects for the REMODEL project of the Horizon 2020 research and innovation programming, while still serving its originally intended purpose in the intelligent production line

Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2021

This Open Access proceedings presents a good overview of the current research landscape of assembly, handling and industrial robotics. The objective of MHI Colloquium is the successful networking at both academic and management level. Thereby, the colloquium focuses an academic exchange at a high level in order to distribute the obtained research results, to determine synergy effects and trends, to connect the actors in person and in conclusion, to strengthen the research field as well as the MHI community. In addition, there is the possibility to become acquatined with the organizing institute. Primary audience is formed by members of the scientific society for assembly, handling and industrial robotics (WGMHI)

Visual Perception System for Aerial Manipulation: Methods and Implementations

La tecnología se evoluciona a gran velocidad y los sistemas autónomos están empezado a ser una realidad. Las compañías están demandando, cada vez más, soluciones robotizadas para mejorar la eficiencia de sus operaciones. Este también es el caso de los robots aéreos. Su capacidad única de moverse libremente por el aire los hace excelentes para muchas tareas que son tediosas o incluso peligrosas para operadores humanos. Hoy en día, la gran cantidad de sensores y drones comerciales los hace soluciones muy tentadoras. Sin embargo, todavía se requieren grandes esfuerzos de obra humana para customizarlos para cada tarea debido a la gran cantidad de posibles entornos, robots y misiones. Los investigadores diseñan diferentes algoritmos de visión, hardware y sensores para afrontar las diferentes tareas. Actualmente, el campo de la robótica manipuladora aérea está emergiendo con el objetivo de extender la cantidad de aplicaciones que estos pueden realizar. Estas pueden ser entre otras, inspección, mantenimiento o incluso operar válvulas u otras máquinas. Esta tesis presenta un sistema de manipulación aérea y un conjunto de algoritmos de percepción para la automatización de las tareas de manipulación aérea. El diseño completo del sistema es presentado y una serie de frameworks son presentados para facilitar el desarrollo de este tipo de operaciones. En primer lugar, la investigación relacionada con el análisis de objetos para manipulación y planificación de agarre considerando diferentes modelos de objetos es presentado. Dependiendo de estos modelos de objeto, se muestran diferentes algoritmos actuales de análisis de agarre y algoritmos de planificación para manipuladores simples y manipuladores duales. En Segundo lugar, el desarrollo de algoritmos de percepción para detección de objetos y estimación de su posicione es presentado. Estos permiten al sistema identificar objetos de cualquier tipo en cualquier escena para localizarlos para efectuar las tareas de manipulación. Estos algoritmos calculan la información necesaria para los análisis de manipulación descritos anteriormente. En tercer lugar. Se presentan algoritmos de visión para localizar el robot en el entorno al mismo tiempo que se elabora un mapa local, el cual es beneficioso para las tareas de manipulación. Estos mapas se enriquecen con información semántica obtenida en los algoritmos de detección. Por último, se presenta el desarrollo del hardware relacionado con la plataforma aérea, el cual incluye unos manipuladores de bajo peso y la invención de una herramienta para realizar tareas de contacto con superficies rígidas que sirve de estimador de la posición del robot. Todas las técnicas presentadas en esta tesis han sido validadas con extensiva experimentación en plataformas reales.Technology is growing fast, and autonomous systems are becoming a reality. Companies are increasingly demanding robotized solutions to improve the efficiency of their operations. It is also the case for aerial robots. Their unique capability of moving freely in the space makes them suitable for many tasks that are tedious and even dangerous for human operators. Nowadays, the vast amount of sensors and commercial drones makes them highly appealing. However, it is still required a strong manual effort to customize the existing solutions to each particular task due to the number of possible environments, robot designs and missions. Different vision algorithms, hardware devices and sensor setups are usually designed by researchers to tackle specific tasks. Currently, aerial manipulation is being intensively studied to allow aerial robots to extend the number of applications. These could be inspection, maintenance, or even operating valves or other machines. This thesis presents an aerial manipulation system and a set of perception algorithms for the automation aerial manipulation tasks. The complete design of the system is presented and modular frameworks are shown to facilitate the development of these kind of operations. At first, the research about object analysis for manipulation and grasp planning considering different object models is presented. Depend on the model of the objects, different state of art grasping analysis are reviewed and planning algorithms for both single and dual manipulators are shown. Secondly, the development of perception algorithms for object detection and pose estimation are presented. They allows the system to identify many kind of objects in any scene and locate them to perform manipulation tasks. These algorithms produce the necessary information for the manipulation analysis described in the previous paragraph. Thirdly, it is presented how to use vision to localize the robot in the environment. At the same time, local maps are created which can be beneficial for the manipulation tasks. These maps are are enhanced with semantic information from the perception algorithm mentioned above. At last, the thesis presents the development of the hardware of the aerial platform which includes the lightweight manipulators and the invention of a novel tool that allows the aerial robot to operate in contact with static objects. All the techniques presented in this thesis have been validated throughout extensive experimentation with real aerial robotic platforms