2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION)最新文献

Repeatable & Scalable Multi-Vehicle Simulation with Offloaded Dynamics using Federated Modeling 可重复和可扩展的多车辆仿真与卸载动力学使用联邦建模

2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION) Pub Date : 2022-05-01 DOI: 10.1109/DESTION56136.2022.00016

R. Bhadani, J. Sprinkle

{"title":"Repeatable & Scalable Multi-Vehicle Simulation with Offloaded Dynamics using Federated Modeling","authors":"R. Bhadani, J. Sprinkle","doi":"10.1109/DESTION56136.2022.00016","DOIUrl":"https://doi.org/10.1109/DESTION56136.2022.00016","url":null,"abstract":"In this paper, we present a method to perform multi-vehicle simulation of autonomous systems that improves the repeatability of robotics simulations and can improve the scale of such simulations for dynamically complex devices such as autonomous vehicles (AV). Current approaches to simulation of multi-component AV typically infer the kinematics or dynamics through the rigid-body motion that uses joint angles and shapes. Such simulations encounter challenges for simulated AV, as the methods to discretize the behavior are prone to error accumulated over time and are computationally intensive – frequently resulting in chaotic behavior. The accumulated error results in a lack of repeatability of the simulation results. Further, when simulating multiple AVs, simulations typically fail to scale to tens of vehicles, even when slowed to permit more accurate results as the state evolves. This paper provides an architecture for improving the repeatability of simulations using federated modeling and state synchronization through a director. The method consists of replacing the inverse kinematic vehicle models with computational models of their dynamics, offloading dynamics from the physics engine for state evolution, synchronizing vehicle updates using a director, and performing the simulation at slower than real-time if needed. Our method reduces the error of trajectory deviation during repeated simulations by at least threefold. An implementation of the results of the work is presented through a Robot Operating System (ROS) package.","PeriodicalId":273969,"journal":{"name":"2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION)","volume":"458 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116182535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Combinatorial and Parametric Gradient-Free Optimization for Cyber-Physical System Design 网络物理系统设计的组合和参数无梯度优化

2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION) Pub Date : 2022-05-01 DOI: 10.1109/DESTION56136.2022.00012

Hongrui Zheng, Johannes Betz, Arun Ramamurthy, Hyunjee Jin, R. Mangharam

引用次数: 2

Surrogates for Computationally Expensive and Failure-Prone Simulators 计算昂贵且容易出错的模拟器的替代品

2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION) Pub Date : 2022-05-01 DOI: 10.1109/DESTION56136.2022.00007

S. Rooney, Emil Pitz, K. Pochiraju

{"title":"Surrogates for Computationally Expensive and Failure-Prone Simulators","authors":"S. Rooney, Emil Pitz, K. Pochiraju","doi":"10.1109/DESTION56136.2022.00007","DOIUrl":"https://doi.org/10.1109/DESTION56136.2022.00007","url":null,"abstract":"Simulations used for navigating design spaces or finding optimal design points and Pareto fronts require accuracy and resolution to guide the designers towards effective decisions. High-fidelity or high-resolution simulators are computationally expensive. Due to inconsistent parameter settings and physically invalid outcomes, such simulators can also fail to return a solution during design automation or optimization loops. In CPS systems, failures can be expected when there is a hard execution-time deadline on the simulator for producing a solution. Time deadlines imposed by other considerations drive simulation failure behaviors in such cases.Current strategies for modeling simulator failure incorporate failures as an additional discrete parameter or entirely disregard the failed point. This paper describes a method for classifying candidate design points as predictable or failure-prone using a Bayes Classifier. Either a global surrogate or a mixture of the expert local surrogates will be identified in design spaces where the high-fidelity simulators yield a prediction. The developed technique is illustrated with two geometry assembly examples. The simulator fails if the composition does not lead to a valid 3D geometry or produces collisions in the assembly. This paper shows that global or MOE surrogates can be trained for both these cases with validation accuracy exceeding 90 %. The results also show that the best surrogate model can be a global model or a mixture of experts models and can vary by the approximated output parameter.","PeriodicalId":273969,"journal":{"name":"2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134306571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparing Strategies for Visualizing the High-Dimensional Exploration Behavior of CPS Design Agents 比较可视化 CPS 设计代理高维探索行为的策略

2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION) Pub Date : 2022-05-01 DOI: 10.1109/DESTION56136.2022.00017

Akash Agrawal, Christopher McComb

引用次数: 0

A Flight Dynamics Model for Exploring the Distributed Electrical eVTOL Cyber Physical Design Space 探索分布式电子eVTOL网络物理设计空间的飞行动力学模型

2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION) Pub Date : 2022-05-01 DOI: 10.1109/DESTION56136.2022.00008

James D. Walker, F. M. Heim, B. Surampudi, Pablo Bueno, Alexander Carpenter, S. Chocron, Jon T. Cutshall, Richard Lammons, Theodore Bapty, Brian Swenson, Sydney Whittington

引用次数: 5

Design Oracle for AI-Based CPS Design 基于ai的CPS设计Oracle

2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION) Pub Date : 2022-05-01 DOI: 10.1109/DESTION56136.2022.00009

T. Bapty, Sydney Whittington, James Walker, Joseph Hite, Brian Swenson, Katherine Owens, Fred Eisele, J. Scott, R. Owens

{"title":"Design Oracle for AI-Based CPS Design","authors":"T. Bapty, Sydney Whittington, James Walker, Joseph Hite, Brian Swenson, Katherine Owens, Fred Eisele, J. Scott, R. Owens","doi":"10.1109/DESTION56136.2022.00009","DOIUrl":"https://doi.org/10.1109/DESTION56136.2022.00009","url":null,"abstract":"Automated design processes, especially using Machine Learning/AI techniques, require proposed systems to be evaluated across all relevant attributes, requirements, and concerns. Traditionally, teams create models in a set of engineering tools for design evaluation data. We describe a Design Oracle, where automated designers can submit a system as a graph of components and request a full range of evaluations, composing analysis workflows containing multiple engineering tools across multiple physical domains, fidelity, and scenarios. Manually created system models are not required. The system works across cloud architectures, supporting the use of parallel computation.The system leverages technology developed under the DARPA Adaptive Vehicle Make/META program, which created a uniform, multi-domain design and component representation, and tools for composition to engineering tool models across multiple tool types, domains, and fidelity levels [1]. The Design Oracle has been used within the DARPA Symbiotic Design for Cyber-Physical Systems, across two classes of target designs, Unmanned Air Vehicles and Unmanned Underwater Vehicles.","PeriodicalId":273969,"journal":{"name":"2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124619674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Trinity AI Co-Designer for Hierarchical Oracle-guided Design of Cyber-Physical Systems Trinity AI协同设计器，用于网络物理系统的分层oracle引导设计

2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION) Pub Date : 2022-05-01 DOI: 10.1109/DESTION56136.2022.00013

A. Cobb, Anirban Roy, D. Elenius, Susmit Jha

{"title":"Trinity AI Co-Designer for Hierarchical Oracle-guided Design of Cyber-Physical Systems","authors":"A. Cobb, Anirban Roy, D. Elenius, Susmit Jha","doi":"10.1109/DESTION56136.2022.00013","DOIUrl":"https://doi.org/10.1109/DESTION56136.2022.00013","url":null,"abstract":"The design of complex cyber-physical systems entails satisfying several competing performance objectives. In practice, some design requirements are often implicit in the intuition and knowledge of designers who have many years of experience working with similar designs. Designers use this experience to sample a few promising candidates in the design space and evaluate or simulate them using detailed, typically slow scientific models. The goal in design is usually to generate a diverse set of high-performing design configurations that allow trade-offs across different objectives and avoid early concretization. In this paper, we present a demonstration of Trinity AI co-designer that implements a machine learning approach to automate some aspects of system design. Trinity implements an extension of oracle-guided inductive synthesis, where the learning approaches interact with a hierarchy of oracles that range from detailed slow-to-evaluate scientific models to fast but low fidelity deep neural network surrogate models and symbolic rules. The goal is to enable fast design iterations for earlier phases of design. Trinity uses deep generative models to learn a manifold of the valid design space, followed by a joint exploration and optimization of designs over the learned manifold, producing a diverse set of optimal designs with respect to given design objectives. In our demonstration, we will use several case studies including the design of propellers, a ground vehicle, air vehicle and underwater vehicle. Across these case studies, we successfully show how our method generates high-performing and diverse designs.","PeriodicalId":273969,"journal":{"name":"2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131022997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

DESTION 2022 Committee 2022委员会

2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION) Pub Date : 2022-05-01 DOI: 10.1109/destion56136.2022.00006

引用次数: 0

Rapid Design Space Exploration with Constraint Programming 基于约束规划的快速设计空间探索

2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION) Pub Date : 2022-05-01 DOI: 10.1109/DESTION56136.2022.00011

M. Maróti, Will Hedgecock, P. Volgyesi

引用次数: 1

Developing a Testing Framework for Cyber-Physical Systems using Gazebo 利用Gazebo开发网络物理系统测试框架

2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION) Pub Date : 2022-05-01 DOI: 10.1109/DESTION56136.2022.00015

Rizwan Parveen, Tanishq Nandan

引用次数: 0