Pub Date : 2022-05-01DOI: 10.1109/iccps54341.2022.00051
W. Wang, Georg Friedrich Schuppe, Jana Tumova
We propose a decentralized framework to solve a coordination problem for multiagent systems consisting of heterogeneous agents, each of which uses only local information based on limited sensing and communication capabilities. In the proposed method, slower heavy-duty robots are each assigned a task specification specified in metric interval temporal logic. These specifications express complex, time-bounded tasks that are potentially dependent on other agents' actions. Heavy-duty robots update their task plans upon receiving a cooperative request from other heavy-duty robots in order to complete cooperative tasks. These requests are transmitted by the more agile light-duty robots responsible for information exchange, which systematically pursue heavy-duty robots. Our work in progress aims to present the framework together with a set of assumptions under which the solution is complete. We also aim to evaluate the framework on a series of use cases motivated by search and rescue.
{"title":"Decentralized Multi-agent Coordination under MITL Tasks and Communication Constraints","authors":"W. Wang, Georg Friedrich Schuppe, Jana Tumova","doi":"10.1109/iccps54341.2022.00051","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00051","url":null,"abstract":"We propose a decentralized framework to solve a coordination problem for multiagent systems consisting of heterogeneous agents, each of which uses only local information based on limited sensing and communication capabilities. In the proposed method, slower heavy-duty robots are each assigned a task specification specified in metric interval temporal logic. These specifications express complex, time-bounded tasks that are potentially dependent on other agents' actions. Heavy-duty robots update their task plans upon receiving a cooperative request from other heavy-duty robots in order to complete cooperative tasks. These requests are transmitted by the more agile light-duty robots responsible for information exchange, which systematically pursue heavy-duty robots. Our work in progress aims to present the framework together with a set of assumptions under which the solution is complete. We also aim to evaluate the framework on a series of use cases motivated by search and rescue.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"14 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":"115072134","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}
Pub Date : 2022-05-01DOI: 10.1109/iccps54341.2022.00005
{"title":"Foreword to the ICCPS 2022 Proceedings Message from the Program Chairs","authors":"","doi":"10.1109/iccps54341.2022.00005","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00005","url":null,"abstract":"","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"55 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":"116273475","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}
Pub Date : 2022-05-01DOI: 10.1109/iccps54341.2022.00032
Florian Hofer
Programmable Logic Controllers (PLCs) are the most used digital systems in the manufacturing industry, but there is little support for testing such systems. Despite the recommendations of the IEC 61131–3 standards, testing is mainly done manually or not at all. Recent successful attempts for a testing framework for PLCs include proposals close to object orientation. This work presents a test generation approach using such a testing system. Via our Advanced POU Testing (APTest) Framework written in a native IEC 61131–3 - compliant language, we demonstrate the automatic generation and execution of unit tests for existing software units. We introduce the software, discuss its features, and demonstrate its use.
{"title":"IEC 61131–3 Software Testing - Automatic test generation for native applications","authors":"Florian Hofer","doi":"10.1109/iccps54341.2022.00032","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00032","url":null,"abstract":"Programmable Logic Controllers (PLCs) are the most used digital systems in the manufacturing industry, but there is little support for testing such systems. Despite the recommendations of the IEC 61131–3 standards, testing is mainly done manually or not at all. Recent successful attempts for a testing framework for PLCs include proposals close to object orientation. This work presents a test generation approach using such a testing system. Via our Advanced POU Testing (APTest) Framework written in a native IEC 61131–3 - compliant language, we demonstrate the automatic generation and execution of unit tests for existing software units. We introduce the software, discuss its features, and demonstrate its use.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"285 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":"116108258","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}
Pub Date : 2022-05-01DOI: 10.1109/iccps54341.2022.00024
Takuma Yabe, Takuya Azumi
This paper explores and evaluates the potential of deep neural network (DNN)-based machine learning algorithms on embed-ded many-core processors in cyber-physical systems, such as self-driving systems. To run applications in embedded systems, a plat-form characterized by low power consumption with high accuracy and real-time performance is required. Furthermore, a platform is required that allows the coexistence of DNN applications and other applications, including conventional real-time control soft-ware, to enable advanced embedded systems, such as self-driving systems. Clustered many-core processors, such as Kalray MPPA3-80 Coolidge, can run multiple applications on a single platform because each cluster can run applications independently. Moreover, MPPA3-80 integrates multiple arithmetic elements that operate at low frequencies, thereby enabling high performance and low power consumption comparable to that of embedded graphics processing units. Furthermore, the Kalray Neural Network (KaNN) code generator, a deep learning inference compiler for the MPPA3-80 platform, can efficiently perform DNN inference on MPPA3-80. This paper evaluates DNN models, including You Only Look Once (YOLO)-based and Single Shot MultiBox Detector (SSD)-based mod-els, on MPPA3-80. The evaluation examines the frame rate and power consumption in relation to the size of the input image, the computational accuracy, and the number of clusters.
本文探讨并评估了基于深度神经网络(DNN)的机器学习算法在网络物理系统(如自动驾驶系统)中嵌入式多核处理器上的潜力。为了在嵌入式系统中运行应用程序，需要具有低功耗、高精度和实时性的平台。此外，需要一个平台，允许DNN应用和其他应用共存，包括传统的实时控制软件，以实现先进的嵌入式系统，如自动驾驶系统。集群式多核处理器(如Kalray MPPA3-80 Coolidge)可以在单个平台上运行多个应用程序，因为每个集群都可以独立运行应用程序。此外，MPPA3-80集成了多个低频运算元件，从而实现了与嵌入式图形处理单元相当的高性能和低功耗。此外，基于MPPA3-80平台的深度学习推理编译器Kalray Neural Network (KaNN)代码生成器可以在MPPA3-80平台上高效地进行深度神经网络推理。本文在MPPA3-80上评估了DNN模型，包括基于You Only Look Once (YOLO)的模型和基于Single Shot MultiBox Detector (SSD)的模型。评估检查与输入图像的大小、计算精度和簇的数量有关的帧率和功耗。
{"title":"Exploring the Performance of Deep Neural Networks on Embedded Many-Core Processors","authors":"Takuma Yabe, Takuya Azumi","doi":"10.1109/iccps54341.2022.00024","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00024","url":null,"abstract":"This paper explores and evaluates the potential of deep neural network (DNN)-based machine learning algorithms on embed-ded many-core processors in cyber-physical systems, such as self-driving systems. To run applications in embedded systems, a plat-form characterized by low power consumption with high accuracy and real-time performance is required. Furthermore, a platform is required that allows the coexistence of DNN applications and other applications, including conventional real-time control soft-ware, to enable advanced embedded systems, such as self-driving systems. Clustered many-core processors, such as Kalray MPPA3-80 Coolidge, can run multiple applications on a single platform because each cluster can run applications independently. Moreover, MPPA3-80 integrates multiple arithmetic elements that operate at low frequencies, thereby enabling high performance and low power consumption comparable to that of embedded graphics processing units. Furthermore, the Kalray Neural Network (KaNN) code generator, a deep learning inference compiler for the MPPA3-80 platform, can efficiently perform DNN inference on MPPA3-80. This paper evaluates DNN models, including You Only Look Once (YOLO)-based and Single Shot MultiBox Detector (SSD)-based mod-els, on MPPA3-80. The evaluation examines the frame rate and power consumption in relation to the size of the input image, the computational accuracy, and the number of clusters.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"19 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":"128136943","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}
Pub Date : 2022-05-01DOI: 10.1109/iccps54341.2022.00046
M. Lora, P. Nuzzo
This work-in-progress paper presents our current effort toward the development of compositional modeling formalisms and scalable algorithms for high-assurance design of industrial cyber-physical systems, with emphasis on smart manufacturing systems. A require-ment engineering methodology is implemented within CHASE, a software framework supporting contract-based representations of systems and components to facilitate analysis and design space exploration. We provide an overview of CHASE and discuss its application to the design of a robotic arm. This paper is accompanied by a poster describing the architecture of CHASE and a demonstration of its application to the case study.
{"title":"A Contract-Based Requirement Engineering Framework for the Design of Industrial Cyber-Physical Systems","authors":"M. Lora, P. Nuzzo","doi":"10.1109/iccps54341.2022.00046","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00046","url":null,"abstract":"This work-in-progress paper presents our current effort toward the development of compositional modeling formalisms and scalable algorithms for high-assurance design of industrial cyber-physical systems, with emphasis on smart manufacturing systems. A require-ment engineering methodology is implemented within CHASE, a software framework supporting contract-based representations of systems and components to facilitate analysis and design space exploration. We provide an overview of CHASE and discuss its application to the design of a robotic arm. This paper is accompanied by a poster describing the architecture of CHASE and a demonstration of its application to the case study.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"21 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":"131993740","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}
Pub Date : 2022-05-01DOI: 10.1109/iccps54341.2022.00037
Matthew Nice, Derek Gloudemans, D. Work
Millions of vehicles are on the road with RADAR sensors in use for adaptive cruise control (ACC), and RADAR sen-sors are not tracking all of the objects in the field of view. This work shows a work-in-progress tool to improve tracking from RADAR and controller area network (CAN) which should be vitally useful for safety of transportation systems and automated vehicle development. The CAN data provides object detections, but there is a lingering data association problem. The contribution of this work in progress is the solution to the data association problem by posing the data association as a minimum cost network flow problem, and doing it at low cost with an eye toward scalable CPS research.
{"title":"Automated Vehicle Multi-Object Tracking at Scale with CAN","authors":"Matthew Nice, Derek Gloudemans, D. Work","doi":"10.1109/iccps54341.2022.00037","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00037","url":null,"abstract":"Millions of vehicles are on the road with RADAR sensors in use for adaptive cruise control (ACC), and RADAR sen-sors are not tracking all of the objects in the field of view. This work shows a work-in-progress tool to improve tracking from RADAR and controller area network (CAN) which should be vitally useful for safety of transportation systems and automated vehicle development. The CAN data provides object detections, but there is a lingering data association problem. The contribution of this work in progress is the solution to the data association problem by posing the data association as a minimum cost network flow problem, and doing it at low cost with an eye toward scalable CPS research.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"91 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":"126654402","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}
Pub Date : 2022-05-01DOI: 10.1109/iccps54341.2022.00011
H. Kroep, V. Gokhale, R. V. Prasad
Tactile Internet (TI) enables the transfer of human skills over the Internet, enabling teleoperation with force feed-back. Advancements are being made rapidly at several fronts to realize a functional TI soon. Generally, TI is expected to faithfully reproduce operator's actions at the other end, where a robotic arm emulates it while providing force feedback to the operator. Performance of TI is usually characterized using objective metrics such as network delay, packet losses, and RMSE. Pari passu, subjective evaluations are used as additional validation, and performance evaluation itself is not primarily based on user experience. Hence objective evaluation, which generally minimizes error (signal mismatch), is oblivious to subjective experience. In this paper, we argue that user-centric designs of TI solutions are necessary. We first consider a few common TI errors and examine their perceivability, The idea is to reduce the impact of perceivable errors and exploit the imperceivable errors to our advantage, while the objective metrics may indicate that the errors are high. To harness the imperceivable errors, we design Adaptive Offset Framework (AOF) to improve the TI signal reconstruction under realistic network settings. We use AOF to highlight the contradictory inferences drawn by objective and subjective evaluations while realizing that subjective evaluations are closer to ground truth. This strongly suggests the existence of 'blind spots of objective measures‘. Further, we show that AOF significantly improves the user grade, up to 3 points (on a scale of 10) compared to the standard reconstruction method.
{"title":"Blind Spots of Objective Measures: Exploiting Imperceivable Errors for Immersive Tactile Internet","authors":"H. Kroep, V. Gokhale, R. V. Prasad","doi":"10.1109/iccps54341.2022.00011","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00011","url":null,"abstract":"Tactile Internet (TI) enables the transfer of human skills over the Internet, enabling teleoperation with force feed-back. Advancements are being made rapidly at several fronts to realize a functional TI soon. Generally, TI is expected to faithfully reproduce operator's actions at the other end, where a robotic arm emulates it while providing force feedback to the operator. Performance of TI is usually characterized using objective metrics such as network delay, packet losses, and RMSE. Pari passu, subjective evaluations are used as additional validation, and performance evaluation itself is not primarily based on user experience. Hence objective evaluation, which generally minimizes error (signal mismatch), is oblivious to subjective experience. In this paper, we argue that user-centric designs of TI solutions are necessary. We first consider a few common TI errors and examine their perceivability, The idea is to reduce the impact of perceivable errors and exploit the imperceivable errors to our advantage, while the objective metrics may indicate that the errors are high. To harness the imperceivable errors, we design Adaptive Offset Framework (AOF) to improve the TI signal reconstruction under realistic network settings. We use AOF to highlight the contradictory inferences drawn by objective and subjective evaluations while realizing that subjective evaluations are closer to ground truth. This strongly suggests the existence of 'blind spots of objective measures‘. Further, we show that AOF significantly improves the user grade, up to 3 points (on a scale of 10) compared to the standard reconstruction method.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"9 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":"115811732","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}
Pub Date : 2022-05-01DOI: 10.1109/iccps54341.2022.00040
Soumya Vasisht, Aowabin Rahman, Thiagarajan Ramachandran, Arnab Bhattacharya, V. Adetola
A simulation-based optimization framework is developed to con-currently design the system and control parameters to meet de-sired performance and operational resiliency objectives. Leveraging system information from both data and models of varying fideli-ties, a rigorous probabilistic approach is employed for co-design experimentation. Significant economic benefits and resilience im-provements are demonstrated using co-design compared to existing sequential designs for cyber-physical systems.
{"title":"Multi-fidelity Bayesian Optimization for Co-design of Resilient Cyber-Physical Systems","authors":"Soumya Vasisht, Aowabin Rahman, Thiagarajan Ramachandran, Arnab Bhattacharya, V. Adetola","doi":"10.1109/iccps54341.2022.00040","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00040","url":null,"abstract":"A simulation-based optimization framework is developed to con-currently design the system and control parameters to meet de-sired performance and operational resiliency objectives. Leveraging system information from both data and models of varying fideli-ties, a rigorous probabilistic approach is employed for co-design experimentation. Significant economic benefits and resilience im-provements are demonstrated using co-design compared to existing sequential designs for cyber-physical systems.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"1 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":"114779712","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}
Pub Date : 2022-05-01DOI: 10.1109/iccps54341.2022.00027
Yahan Yang, R. Kaur, Souradeep Dutta, Insup Lee
The use of learning based components in cyber-physical systems (CPS) has created a gamut of possible avenues to use high dimensional real world signals generated from sensors like camera and LiDAR. The ability to process such signals can be largely attributed to the adoption of high-capacity function approximators like deep neural networks. However, this does not come without its potential perils. The pitfalls arise from possible over-fitting, and subsequent unsafe behavior when exposed to unknown environments. One challenge is that, in high dimensional input spaces it is almost impossible to experience enough training data in the design phase. What is required here, is an efficient way to flag out-of-distribution (OOD) samples that is precise enough to not raise too many false alarms. In addition, the system needs to be able to detect these in a computationally efficient manner at runtime. In this paper, our proposal is to build good representations for in-distribution data. We introduce the idea of a memory bank to store prototypical samples from the input space. We use these memories to compute probability density estimates using kernel density estimation techniques. We evaluate our technique on two challenging scenarios : a self-driving car setting implemented inside the simulator CARLA with image inputs, and an autonomous racing car navigation setting, with LiDAR inputs. In both settings, it was observed that a deviation from indistribution setting can potentially lead to deviation from safe behavior. An added benefit of using training samples as memories to detect out-of-distribution inputs is that the system is interpretable to a human operator. Explanation of this nature is generally hard to obtain from pure deep learning based alter-natives. Our code for reproducing the experiments is available at https://github.com/yangy96/interpretable_ood_detection.git
{"title":"Interpretable Detection of Distribution Shifts in Learning Enabled Cyber-Physical Systems","authors":"Yahan Yang, R. Kaur, Souradeep Dutta, Insup Lee","doi":"10.1109/iccps54341.2022.00027","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00027","url":null,"abstract":"The use of learning based components in cyber-physical systems (CPS) has created a gamut of possible avenues to use high dimensional real world signals generated from sensors like camera and LiDAR. The ability to process such signals can be largely attributed to the adoption of high-capacity function approximators like deep neural networks. However, this does not come without its potential perils. The pitfalls arise from possible over-fitting, and subsequent unsafe behavior when exposed to unknown environments. One challenge is that, in high dimensional input spaces it is almost impossible to experience enough training data in the design phase. What is required here, is an efficient way to flag out-of-distribution (OOD) samples that is precise enough to not raise too many false alarms. In addition, the system needs to be able to detect these in a computationally efficient manner at runtime. In this paper, our proposal is to build good representations for in-distribution data. We introduce the idea of a memory bank to store prototypical samples from the input space. We use these memories to compute probability density estimates using kernel density estimation techniques. We evaluate our technique on two challenging scenarios : a self-driving car setting implemented inside the simulator CARLA with image inputs, and an autonomous racing car navigation setting, with LiDAR inputs. In both settings, it was observed that a deviation from indistribution setting can potentially lead to deviation from safe behavior. An added benefit of using training samples as memories to detect out-of-distribution inputs is that the system is interpretable to a human operator. Explanation of this nature is generally hard to obtain from pure deep learning based alter-natives. Our code for reproducing the experiments is available at https://github.com/yangy96/interpretable_ood_detection.git","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"13 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":"128383733","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}
Pub Date : 2022-05-01DOI: 10.1109/iccps54341.2022.00042
Abhinav Chawla, Stanley Bak
Cyber-Physical Systems (CPS) are created as complex interactions of multiple physical systems and play a vital role in automating real-life systems. In this work, we present a testing methodology for CPS based on modified version of the Rapidly-exploring Random Tree (RRT) algorithm which is used traditionally to solve the motion planning problem in the context of the CPS testing problem. Directly using RRT for testing CPS requires storing the state of the CPS controller at each node of the RRT which is often memory intensive. Further, the simulator needs to support initialization from arbitrary states, which is not always possible, especially for complex simulation environments. We present our progress towards a modified RRT algorithm where the state of the controller is not required to be saved at each node, and show promising improvements in testing efficiency using a 9-D simulated point example system.
{"title":"CPS Testing using Stateless RRT","authors":"Abhinav Chawla, Stanley Bak","doi":"10.1109/iccps54341.2022.00042","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00042","url":null,"abstract":"Cyber-Physical Systems (CPS) are created as complex interactions of multiple physical systems and play a vital role in automating real-life systems. In this work, we present a testing methodology for CPS based on modified version of the Rapidly-exploring Random Tree (RRT) algorithm which is used traditionally to solve the motion planning problem in the context of the CPS testing problem. Directly using RRT for testing CPS requires storing the state of the CPS controller at each node of the RRT which is often memory intensive. Further, the simulator needs to support initialization from arbitrary states, which is not always possible, especially for complex simulation environments. We present our progress towards a modified RRT algorithm where the state of the controller is not required to be saved at each node, and show promising improvements in testing efficiency using a 9-D simulated point example system.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"50 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":"133942374","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}
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