4,821 research outputs found

    Assembly Sequence Planning Using Neural Network Approach

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    A strategy planner for NASA robotics applications

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    Automatic strategy or task planning is an important element of robotics systems. A strategy planner under development at Goddard Space Flight Center automatically produces robot plans for assembly, disassembly, or repair of NASA spacecraft from computer aided design descriptions of the individual parts of the spacecraft

    Computation Reuse in Statics and Dynamics Problems for Assemblies of Rigid Bodies

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    The problem of determining the forces among contacting rigid bodies is fundamental to many areas of robotics, including manipulation planning, control, and dynamic simulation. For example, consider the question of how to unstack an assembly, or how to find stable regions of a rubble pile. In considering problems of this type over discrete or continuous time, we often encounter a sequence of problems with similar substructure. The primary contribution of our work is the observation that in many cases, common physical structure can be exploited to solve a sequence of related problems more efficiently than if each problem were considered in isolation. We examine three general problems concerning rigid-body assemblies: dynamic simulation, assembly planning, and assembly stability given limited knowledge of the structure\u27s geometry. To approach the dynamic simulation and assembly planning applications, we have optimized a known method for solving the system dynamics. The accelerations of and forces among contacting rigid bodies may be computed by formulating the dynamics equations and contact constraints as a complementarity problem. Dantzig\u27s algorithm, when applicable, takes n or fewer major cycles to find a solution to the linear complementarity problem corresponding to an assembly with n contacts. We show that Dantzig\u27s algorithm will find a solution in n - k or fewer major cycles if the algorithm is initialized with a solution to the dynamics problem for a subassembly with k internal contacts. Finally, we show that if we have limited knowledge of a structure\u27s geometry, we can still learn about stable regions of its surface by physically pressing on it. We present an approach for finding stable regions of planar assemblies: sample presses on the surface to identify a stable cone in wrench space, partition the space of applicable wrenches into stable and unstable regions, and map these back to the surface of the structure

    Computer Aided Optimal Robotic Assembly Sequence Generation

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    Robots are widely used for assembly operations across manufacturing industries to attain high productivity through automation. An appropriate robotic assembly sequence further minimizes the total production lead time and overall cost by minimizing the number of assembly direction changes, assembly gripper changes and assembly energy thus selection of a valid optimal robotic assembly sequence is significantly essential to achieve economized manufacturing process. An optimal assembly sequence must comply with various assembly requirements in order to make sure that the sequence of assembly operations is functionally feasible in physical environment. In order to test an assembly sequence for its practical possibility, necessary assembly information must be collected accurately from the product. Obtaining such assembly information from product drawings or Computer Aided Design (CAD) models in manual mode were involved in lots of complexity and needs high level skills to ensure correctness. Though retrieving such information from products with less number of parts is simple and less time consuming, for products composed of huge number parts it is very complicated and time consuming. Besides retrieving the assembly information, using it for validating an assembly sequence further raises the complexity of the Assembly Sequence Generation (ASG) problem. To perform optimal feasible assembly sequence generation efficiently, an effective computer aided automated method is developed and executed at two phases. The first phase of research is mainly focused on representing the assembly information in a streamlined manner by considering all possible states of assembly configurations for ease of computerization and developing efficient methods to extract the assembly information automatically from CAD environment though Computer Aided Automation (CAA). These methods basically use assembly contact analysis, part transformations and laws of equilibrium & balancing of rigid bodies. From the existing ASG methods, it is observed most of the researchers ignored/not-considered few of the assembly information such as assembly stability data and mechanical feasibility data due to higher complexity in retrieving it from CAD environment....

    Algorithms for generating multi-stage molding plans for articulated assemblies

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    Plastic products such as toys with articulated arms, legs, and heads are traditionally produced by first molding individual components separately, and then assembling them together. A recent alternative, referred to as in-mold assembly process, performs molding and assembly steps concurrently inside the mold itself. The most common technique of performing in-mold assembly is through multi-stage molding, in which the various components of an assembly are injected in a sequence of molding stages to produce the final assembly. Multi-stage molding produces better-quality articulated products at a lower cost. It however, gives rise to new mold design challenges that are absent from traditional molding. We need to develop a molding plan that determines the mold design parameters and sequence of molding stages. There are currently no software tools available to generate molding plans. It is difficult to perform the planning manually because it involves evaluating large number of combinations and solving complex geometric reasoning problems. This dissertation investigates the problem of generating multi-stage molding plans for articulated assemblies. The multi-stage molding process is studied and the underlying governing principles and constraints are identified. A hybrid planning framework that combines elements from generative and variant techniques is developed. A molding plan representation is developed to build a library of feasible molding plans for basic joints. These molding plans for individual joints are reused to generate plans for new assemblies. As part of this overall planning framework, we need to solve the following geometric subproblems -- finding assembly configuration that is both feasible and optimal, finding mold-piece regions, and constructing an optimal shutoff surface. Algorithms to solve these subproblems are developed and characterized. This dissertation makes the following contributions. The representation for molding plans provides a common platform for sharing feasible and efficient molding plans for joints. It investigates the multi-stage mold design problem from the planning perspective. The new hybrid planning framework and geometric reasoning algorithms will increase the level of automation and reduce chances of design mistakes. This will in turn reduce the cost and lead-time associated with the deployment of multi-stage molding process

    Génération des séquences de désassemblage et leur évaluation : Intégration dans un environnement de réalité virtuelle

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    Integration of disassembly operations during product design is an important issue today. It is estimated that at the earliest stages of product design, the cost of disassembly operations almost represents 30 % of its total cost. Nowadays, disassembly operation simulation of industrial products finds a strong interest in interactive simulations through immersive and real-time schemes. In this context, in the first place, this thesis presents a method for generating the feasible disassembly sequences for selective disassembly. The method is based on the lowest levels of a disassembly product graph. Instead of considering the geometric constraints for each pair of components, the proposed method considers the geometric contact and collision relationships among the components in order to generate the so-called Disassembly Geometry Contacting Graph (DGCG). The latter is then used for disassembly sequence generation thus allowing the number of possible sequences to be reduced by ignoring any components which are unrelated to the target. A simulation framework was developed integrated in a Virtual reality environment thus allowing generating the minimum number of possible disassembly sequences. Secondly, a method for disassembly operation evaluation by 3D geometric removability analysis in a Virtual environment is proposed. It is based on seven new criteria which are: visibility of a part, disassembly angles, number of tools' changes, path orientation changing, sub-assembly stability, neck score and bending score. All criteria are presented by dimensionless coefficients automatically calculated, thus allowing evaluating disassembly sequences complexity. For this purpose, a mixed virtual reality disassembly environment (VRDE) is developed based on Python programming language, utilizing VTK (Visualization Toolkit) and ODE (Open Dynamics Engine) libraries. The framework is based on STEP, WRL and STL exchange formats. The analysis results and findings demonstrate the feasibility of the proposed approach thus providing significant assistance for the evaluation of disassembly sequences during Product Development Process (PDP). Further consequences of the present work consist in ranking the criteria according to their importance. For this purpose, moderation coefficients may be allocated to each of them thus allowing a more comprehensive evaluating method.De nos jours, l'intégration des opérations de désassemblage lors de la conception des produits est un enjeu crucial. On estime que dans la phase initiale de la conception d'un produit, le coût des opérations de désassemblage représente environ 30% de son coût total. Ainsi, la simulation des opérations de désassemblage de produits industriels trouve un fort intérêt pour des simulations interactives grâce à des programmes d'immersion et en temps réel. Dans ce contexte, dans un premier temps, cette thèse présente une méthode de génération des séquences de désassemblage possibles pour le désassemblage sélectif. La méthode est basée sur les niveaux les plus bas du graphe de désassemblage des produits. Au lieu de considérer les contraintes géométriques pour chaque paire de composants, la méthode proposée tient compte des contacts (relations géométriques entre les composants) et des collisions afin de générer le Graphe Géométrique de Contacts et de Désassemblage (DGCG). Celui-ci est ensuite utilisé pour la génération des séquences de désassemblage permettant ainsi de réduite le nombre de séquences possibles en ignorant les composants non liés avec la cible. Une application de simulation a été développée, intégrée dans un environnement de réalité virtuelle (RV) permettant ainsi la génération du nombre minimum de séquences possibles de désassemblage.Dans un second temps, une méthode d'évaluation des opérations de désassemblage par analyse géométrique 3D de l'amovibilité dans un environnement RV est proposée. Elle est basée sur sept nouveaux critères qui sont: la visibilité d'une pièce, les angles de désassemblage, le nombre des changements d'outils, le changement d'orientation des trajectoires, la stabilité des sous-ensembles, les angles de rotation du cou et flexion du corps. Tous ces critères sont présentés par des coefficients sans dimension calculés automatiquement par l'application développée, permettant ainsi d'évaluer la complexité des séquences de désassemblage. A cet effet, un environnement mixte de réalité virtuelle pour le désassemblage (VRDE) est développé, basé sur le langage de programmation Python, en utilisant deux bibliothèques : VTK (Visualisation Toolkit) et ODE (Open Dynamics Engine), les formats d'échange étant fichiers: STEP, WRL et STL. L'analyse des résultats obtenus démontrent la fiabilité de l'approche proposée fournissant ainsi une aide non négligeable pour l'évaluation des séquences de désassemblage lors de processus de développement de produits (PDP). Les autres conséquences de ce travail consistent à classer les critères en fonction de leur importance. A cet effet, des coefficients de modération peuvent être attribués à chacun d'eux permettant ainsi une méthode d'évaluation plus complète

    Computational Foundations for Safe and Efficient Human-Robot Collaboration in Assembly Cells

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    Human and robots have complementary strengths in performing assembly operations. Humans are very good at perception tasks in unstructured environments. They are able to recognize and locate a part from a box of miscellaneous parts. They are also very good at complex manipulation in tight spaces. The sensory characteristics of the humans, motor abilities, knowledge and skills give the humans the ability to react to unexpected situations and resolve problems quickly. In contrast, robots are very good at pick and place operations and highly repeatable in placement tasks. Robots can perform tasks at high speeds and still maintain precision in their operations. Robots can also operate for long periods of times. Robots are also very good at applying high forces and torques. Typically, robots are used in mass production. Small batch and custom production operations predominantly use manual labor. The high labor cost is making it difficult for small and medium manufacturers to remain cost competitive in high wage markets. These manufactures are mainly involved in small batch and custom production. They need to find a way to reduce the labor cost in assembly operations. Purely robotic cells will not be able to provide them the necessary flexibility. Creating hybrid cells where humans and robots can collaborate in close physical proximities is a potential solution. The underlying idea behind such cells is to decompose assembly operations into tasks such that humans and robots can collaborate by performing sub-tasks that are suitable for them. Realizing hybrid cells that enable effective human and robot collaboration is challenging. This dissertation addresses the following three computational issues involved in developing and utilizing hybrid assembly cells: - We should be able to automatically generate plans to operate hybrid assembly cells to ensure efficient cell operation. This requires generating feasible assembly sequences and instructions for robots and human operators, respectively. Automated planning poses the following two challenges. First, generating operation plans for complex assemblies is challenging. The complexity can come due to the combinatorial explosion caused by the size of the assembly or the complex paths needed to perform the assembly. Second, generating feasible plans requires accounting for robot and human motion constraints. The first objective of the dissertation is to develop the underlying computational foundations for automatically generating plans for the operation of hybrid cells. It addresses both assembly complexity and motion constraints issues. - The collaboration between humans and robots in the assembly cell will only be practical if human safety can be ensured during the assembly tasks that require collaboration between humans and robots. The second objective of the dissertation is to evaluate different options for real-time monitoring of the state of human operator with respect to the robot and develop strategies for taking appropriate measures to ensure human safety when the planned move by the robot may compromise the safety of the human operator. In order to be competitive in the market, the developed solution will have to include considerations about cost without significantly compromising quality. - In the envisioned hybrid cell, we will be relying on human operators to bring the part into the cell. If the human operator makes an error in selecting the part or fails to place it correctly, the robot will be unable to correctly perform the task assigned to it. If the error goes undetected, it can lead to a defective product and inefficiencies in the cell operation. The reason for human error can be either confusion due to poor quality instructions or human operator not paying adequate attention to the instructions. In order to ensure smooth and error-free operation of the cell, we will need to monitor the state of the assembly operations in the cell. The third objective of the dissertation is to identify and track parts in the cell and automatically generate instructions for taking corrective actions if a human operator deviates from the selected plan. Potential corrective actions may involve re-planning if it is possible to continue assembly from the current state. Corrective actions may also involve issuing warning and generating instructions to undo the current task
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