A Spatial Grammar Method for the Computational Design Synthesis of Virtual Soft Robots

2018 ◽  
Author(s):  
Merel van Diepen ◽  
Kristina Shea
Keyword(s):  
Objective Function ◽  
Solution Space ◽  
Computational Design ◽  
Synthesis Process ◽  
Generation Process ◽  
Soft Robots ◽  
Design Synthesis ◽  
Spatial Grammar ◽  
Computational Design Synthesis ◽  
Mass Spring

Soft robots are intrinsically compliant, which makes them suitable for interaction with delicate objects and living beings. The vast design space and the complex dynamic behavior of the elastic body of the robots make designing them by hand challenging, often requiring a large number of iterations. It is thus advantageous to design soft robots using a computational design approach that integrates simulation feedback. Since locomotion is an essential component in many robotic tasks, this paper presents the computational design synthesis of soft, virtual, locomotion robots. Methods used in previous work give little insight into and control over the computational design synthesis process. The generated solutions are also highly irregular and very different to hand-designed solutions. Also, the problem requirements are solely modeled in the objective function. Here, designs are generated using a spatial grammar with a rule set that is deduced from known locomotion principles. Spatial grammars make it possible to define the type of morphologies that are generated. The aim is to generate gaits based on different locomotion principles, e.g. walking, hopping and crawling. By combining a spatial grammar with simulated annealing, the solution space is searched for locomotive designs. The designs are simulated using a mass-spring model with stable self-collision so that all generated designs can be evaluated. The resulting virtual designs exhibit a large variety of expected and unexpected gaits. The grammar is analyzed to understand the generation process and assess the performance. The main contribution of this research is modeling of some of the results in the spatial grammar rather than the objective function. Thus, the process is guided towards a class of designs with extremities for locomotion, without having to define the class explicitly. Further, the simulation approach is new and results in a stable method that accounts for self-collision.

A Spatial Grammar Method for the Computational Design Synthesis of Virtual Soft Locomotion Robots

2019 ◽  
Vol 141 (10) ◽  
Author(s):  
Merel van Diepen ◽  
Kristina Shea
Keyword(s):  
Degrees Of Freedom ◽  
Computational Design ◽  
Simulation Method ◽  
Search Space ◽  
Search Process ◽  
Design Synthesis ◽  
Spatial Grammar ◽  
Three Stages ◽  
Computational Design Synthesis ◽  
Simulation Feedback

Soft locomotion robots are intrinsically compliant and have a large number of degrees of freedom. They lack rigid components that provide them with higher flexibility, and they have no joints that need protection from liquids or dirt. However, the hand-design of soft robots is often a lengthy trail-and-error process. This work presents the computational design of virtual, soft locomotion robots using an approach that integrates simulation feedback. The computational approach consists of three stages: (1) generation, (2) evaluation through simulation, and (3) optimization. Here, designs are generated using a spatial grammar to explicitly guide the type of solutions generated and exclude infeasible designs. The soft material simulation method developed and integrated is stable and sufficiently fast for use in a highly iterative simulated annealing search process. The resulting virtual designs exhibit a large variety of expected and unexpected gaits, thus demonstrating the method capabilities. Finally, the optimization results and the spatial grammar are analyzed to understand and map the challenges of the problem and the search space.

Automatically Transforming Object-Oriented Graph-Based Representations Into Boolean Satisfiability Problems for Computational Design Synthesis

2013 ◽  
Vol 135 (10) ◽  
Author(s):  
Clemens Münzer ◽  
Bergen Helms ◽  
Kristina Shea
Keyword(s):  
Space Exploration ◽  
Solution Space ◽  
Object Oriented ◽  
Computational Design ◽  
Building Blocks ◽  
Boolean Satisfiability ◽  
Design Synthesis ◽  
Alcohol Production ◽  
Systematic Solution ◽  
Computational Design Synthesis

Ever since computers have been used to support human designers, a variety of representations have been used to encapsulate engineering knowledge. Computational design synthesis (CDS) approaches utilize this knowledge to generate design candidates for a specified task. However, new approaches are required to enable systematic solution space exploration. This paper presents an approach that combines a graph-based object-oriented knowledge representation with first-order logic and Boolean satisfiability. This combination is used as the foundation for a generic automated approach for requirement-driven computational design synthesis. Available design building blocks and a design task defined through a set of requirements are modeled in a graph-based environment and then automatically transferred into a Boolean satisfiability problem and solved, considering a given solution size. The Boolean solution is automatically transferred back to the graph-based domain. The method is validated through two case studies: synthesis of automotive powertrains and chemical process synthesis for ethyl alcohol production. The contribution of the paper is a new method that is able to determine if an engineering task is solvable for a given set of synthesis building blocks and enables systematic solution space exploration.

Solving Design Tasks in Engineering Using Object-Oriented Graph-Based Representations and Boolean Satisfiability

2013 ◽  
Author(s):  
Clemens Münzer ◽  
Kristina Shea ◽  
Bergen Helms
Keyword(s):  
Solution Space ◽  
Object Oriented ◽  
Oriented Graph ◽  
Computational Design ◽  
Building Blocks ◽  
Boolean Satisfiability ◽  
Design Synthesis ◽  
Boolean Satisfiability Problem ◽  
Systematic Solution ◽  
Computational Design Synthesis

Ever since computers have been used to support human designers, a variety of representations have been used to encapsulate engineering knowledge. Computational design synthesis approaches utilize this knowledge to generate design candidates for a specified task. However, new approaches are required to enable systematic solution space exploration. This paper presents an approach that combines a graph-based, object-oriented knowledge representation with first-order logic and Boolean satisfiability. This combination is used as the foundation for a generic, automated approach for requirement-driven computational design synthesis. Available design building blocks and a design task defined through a set of requirements are modeled in a graph-based environment and then automatically transferred into a Boolean satisfiability problem and solved, considering a given solution size. The solution is then automatically transferred back to the graph-based domain. The method is validated through the synthesis of automotive powertrains. The contribution of the paper is a new method that is both able to determine that an engineering task is solvable or not given a set of design building blocks and able to systematically explore the solution space.

A Method for Visualizing the Relations Between Grammar Rules, Performance Objectives and Search Space Exploration in Grammar-Based Computational Design Synthesis

2015 ◽  
Author(s):  
Corinna Königseder ◽  
Kristina Shea
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Computational Design ◽  
Search Space ◽  
Synthesis Process ◽  
Design Synthesis ◽  
Novel Approach ◽  
Grammar Rules ◽  
Computational Design Synthesis

Design grammars have been successfully applied in numerous engineering disciplines, e.g. in electrical engineering, architecture and mechanical engineering. A successful application of design grammars in Computational Design Synthesis (CDS) requires a) a meaningful representation of designs and the design task at hand, b) a careful formulation of grammar rules to synthesize new designs, c) problem specific design evaluations, and d) the selection of an appropriate algorithm to guide the synthesis process. Managing these different aspects of CDS requires not only a detailed understanding of each individual part, but also of the interdependencies between them. In this paper, a new method is presented to analyze the exploration of design spaces in CDS. The method analyzes the designs generated during the synthesis process and visualizes how the design space is explored with respect to a) design characteristics, and b) objectives. The selected algorithm as well as the grammar rules can be analyzed with this approach to support the human designer in successfully understanding and applying a CDS method. The case study demonstrates how the method is used to analyze the synthesis of bicycle frames. Two algorithms are compared for this task. Results demonstrate how the method increases the understanding of the different components in CDS. The presented research can be useful for both novices to CDS to help them gain a deeper understanding of the interplay between grammar rules and guidance of the synthesis process, as well as for experts aiming to further improve their CDS application by improving parameter settings of their search algorithms, or by further refining their design grammar. Additionally, the presented method constitutes a novel approach to interactively visualize design space exploration considering not only designs objectives, but also the characteristics and interdependencies of different designs.

A Framework for Computational Design Synthesis: Model and Applications

2005 ◽  
Vol 5 (3) ◽  
pp. 171-181 ◽  
Author(s):  
Jonathan Cagan ◽  
Matthew I. Campbell ◽  
Susan Finger ◽  
Tetsuo Tomiyama
Keyword(s):  
Computational Design ◽  
Active Area ◽  
Synthesis Process ◽  
Automated Synthesis ◽  
Design Problems ◽  
Design Synthesis ◽  
Industrial Practice ◽  
Research Challenges ◽  
Computational Design Synthesis ◽  
Open Issues

The field of computational design synthesis has been an active area of research for almost half a century. Research advances in this field have increased the sophistication and complexity of the designs that can be synthesized, and advances in the speed and power of computers have increased the efficiency with which those designs can be generated. Some of the results of this research have begun to be used in industrial practice, yet many open issues and research challenges remain. This paper provides a model of the automated synthesis process as a context to discuss research in the area. The varied works of the authors are discussed as representative of the breadth of methods and results that exist under the field of computational design synthesis. Furthermore, some guidelines are presented to help researchers and designers find approaches to solving their particular design problems using computational design synthesis.

A Spatial Grammar for the Computational Design Synthesis of Vise Jaws

2013 ◽  
Author(s):  
Thomas Gmeiner ◽  
Kristina Shea
Keyword(s):  
Low Cost ◽  
Computational Design ◽  
Design Synthesis ◽  
Industry Standard ◽  
Solid Models ◽  
Spatial Grammar ◽  
Cylindrical Parts ◽  
Batch Sizes ◽  
Computational Design Synthesis ◽  
3D Solid

For the machining and assembly of mechanical parts, their secure fixation in a defined position is crucial. To achieve this task, flexible fixture devices (FFDs) are the industry standard for small and medium batch-sizes. Unlike dedicated fixtures, FFDs allow for the fixation of different part shapes, increasing their applicability and economic efficiency. Aiming to create a low-cost and autonomous FFD, a reconfigurable vise with adaptable jaws was developed. The jaws can be machined to a variety of shapes to securely hold prismatic and cylindrical parts. In this paper, a spatial grammar approach for the computational design synthesis of these customizable jaws is presented. Different sets of rules for the generation of 3D solid models of vise jaws based on the model of the workpiece to be held are developed and realized in a CAD environment. The approach is verified by generating jaw designs for example parts.

Visualizing Relations Between Grammar Rules, Objectives, and Search Space Exploration in Grammar-Based Computational Design Synthesis1

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Corinna Königseder ◽  
Kristina Shea
Keyword(s):  
Method Development ◽  
Search Algorithm ◽  
Computational Design ◽  
Search Space ◽  
Synthesis Process ◽  
Design Synthesis ◽  
Grammar Rules ◽  
Computational Design Synthesis ◽  
Design Characteristics ◽  
Selection Of

Design grammars have been successfully applied in numerous engineering disciplines, e.g., in electrical engineering, architecture, and mechanical engineering. A successful application of design grammars in computational design synthesis (CDS) requires (a) meaningful representation of designs and the design task at hand, (b) careful formulation of grammar rules to synthesize new designs, (c) problem-specific design evaluation, and (d) selection of an appropriate algorithm to guide the synthesis process. Determining these different components of a CDS method requires not only a detailed understanding of each individual part but also of the interdependencies between them. In this paper, a new method is presented to support both CDS method development and application. The method analyzes the designs generated during the synthesis process and visualizes how the design space is explored with respect to design characteristics and objectives. The search algorithm as well as the grammar rules are analyzed with this approach. Two case studies, the synthesis of gearboxes and of bicycle frames, demonstrate how the method can be used to analyze the different components of CDS methods. The presented research can analyze the interplay between grammar rules and the search process during method development.

scholarly journals Closed Shell Iron(IV) Oxo Complex with an Fe–O Triple Bond: Computational Design, Synthesis, and Reactivity

2020 ◽  
Vol 59 (51) ◽  
pp. 23137-23144
Author(s):  
Erik Andris ◽  
Koen Segers ◽  
Jaya Mehara ◽  
Lubomír Rulíšek ◽  
Jana Roithová
Keyword(s):  
Triple Bond ◽  
Computational Design ◽  
Closed Shell ◽  
Design Synthesis ◽  
Computational Design Synthesis

Computational design, synthesis and utilization of a magnetic molecularly imprinted polymer on graphene oxide nanosheets for highly selective extraction and determination of buprenorphine in biological fluids and tablets

2018 ◽  
Vol 10 (43) ◽  
pp. 5214-5226 ◽  
Author(s):  
Farideh Ganjavi ◽  
Mehdi Ansari ◽  
Maryam Kazemipour ◽  
Leila Zeidabadinejad
Keyword(s):  
Biological Fluids ◽  
Computational Design ◽  
Selective Extraction ◽  
Graphene Oxide Nanosheets ◽  
Imprinted Polymer ◽  
Design Synthesis ◽  
Molecularly Imprinted ◽  
Plasma And Urine Samples ◽  
Computational Design Synthesis

A magnetic MIP for the selective extraction of buprenorphine (BUP) from real plasma and urine samples and tablets based on computational design as a novel procedure has been developed.

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