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检索条件"主题词=Computer Aided Software Engineering"

共 11026 条记录，以下是61-70 订阅

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Self-Recalibrating Micromanipulator System for Resilient Robotic Vision-Based Control 18

Self-Recalibrating Micromanipulator System for Resilient Rob...

引用

IEEE 18th International Conference on Automation Science and engineering (IEEE CASE)

作者： Wang, Tiexin Li, Haoyu Pu, Tanhong Ding, Jingjing Du, Shoukang Chau, Zhong Hoo Tan, U-Xuan Chew, Ting Gang Yang, Liangjing Zhejiang Univ ZJU UIUC Inst Int Campus Haining Zhejiang Peoples R China Zhejiang Univ Sch Med Zhejiang Univ Univ Edinburgh Inst Hangzhou 310058 Peoples R China Singapore Univ Technol & Design Engn Prod Dev Singapore Singapore

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

A self-recalibrating micromanipulator system is developed in this work to perform vision-based control under unpredictable scenes and poor imaging conditions. To ensure resilient vision-based control in such challenging conditions, we proposed a self-recalibrating mechanism that combines the estimates from both the robot manipulator and microscope vision. Our method is demonstrated for micropipette cell aspiration. In the initialization stage, the system automatically locates the tip and selects the templates for visual tracking. At the self-calibration phase, accurate tracking of the tip is achieved by the background subtraction template matching (BSTM) method in order to estimate the calibration matrix in complex environments. During the operation, the control error is detected according to the visual information and the self-recalibration is executed when the error exceeds the threshold value. Experimental analysis shows that the BSTM method for self-calibration achieves accurate tracking with an average error of less than 1 pixel (0.18 mu m). And the system has an average control error of 4.18 pixels ( 0.75 mu m) under complex calibration backgrounds, satisfying the accuracy requirements for cell aspiration. Moreover, the system achieved stable tracking in complex operating environments, including cell interaction, occlusion, tip leaving the focal plane or beyond the field-of-view. By designing a self-recalibrating micromanipulator equipped with resilient vision-based control system, we hope to robotize the procedures for the study of cell mechanics during micropipette aspiration and pave the path for the advancement of robotic micromanipulation in biomechanical research.

关键词： Biomechanics Visualization computer aided software engineering Automation Micromanipulators Microscopy Control systems

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Causality-based Prediction Method for the Diesel Engine Assembly Line System 18

Causality-based Prediction Method for the Diesel Engine Asse...

引用

IEEE 18th International Conference on Automation Science and engineering (IEEE CASE)

作者： Hu, Jin-Hua Sun, Yan-Ning Xu, Hong-Wei Zhang, Zhan-Luo Qin, Wei Li, Xin-Yu Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

The prediction of diesel engine power is a vital prerequisite for diesel engine quality promotion. A key issue of diesel engine power prediction is the selection of representative features for forecasting. However, current feature selection methods mainly rely on correlation analysis which cannot distinguish between direct correlation and indirect correlation. This paper presents a causal feature selection method for diesel engine power forecasting. Causalities distinguish direct influences from indirect ones. Therefore, this paper proposes a diesel engine power prediction framework based on using Markov Blanket-based feature selection approach and Gradient Boosting Decision Tree (GBDT) forecasting model. The proposed framework first applies Markov Blanket to identify causalities between manufacturing variables and diesel engine power and generates a causal feature set. Then, the quantitative relationship between causal features and the diesel engine power is established through GBDT. Finally, the proposed framework is tested by the experiment on a real diesel engine dataset. And the results show that the proposed framework delivers a satisfactory performance advantage for the validation condition in actual applications, the root mean squared error and the coefficient of variation of the root mean squared error of the GBDT model under the validation condition are 2.94kW and 1.17%, respectively.

关键词： Correlation computer aided software engineering Diesel engines Markov processes Predictive models Feature extraction Boosting

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Work-in-Progress: MLGOPerf: An ML Guided Inliner to Optimize Performance

Work-in-Progress: MLGOPerf: An ML Guided Inliner to Optimize...

引用

International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (CASES)

作者： Ashouri, Amir H. Elhoushi, Mostafa Hua, Yuzhe Wang, Xiang Manzoor, Muhammad Asif Chan, Bryan Gao, Yaoqing Huawei Technol Heterogeneous Compiler Lab Toronto ON Canada

ISBN: (数字)9781665472968

ISBN: (纸本)9781665472968

This paper presents MLGOPerf;the first end-to-end framework capable of optimizing performance using LLVM's ML-Inliner. It employs a secondary ML model to generate rewards used for training a retargeted Reinforcement learning agent, previously used as the primary model by MLGO. It does so by predicting the post-inlining speedup of a function under analysis and it enables a fast training framework for the primary model which otherwise wouldn't be practical. The experimental results show MLGOPerf is able to gain up to 1.8% with respect to LLVM's optimization at O3 when trained for performance on SPEC CPU2006. Furthermore, the proposed approach provides up to 26% increased opportunities to autotune code regions for our benchmarks which can be translated into an additional 3.7% speedup value.

关键词： Training Analytical models Embedded systems computer aided software engineering Codes Reinforcement learning Predictive models

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Fusing Panoptic Segmentation and Geometry Information for Robust Visual SLAM in Dynamic Environments 18

Fusing Panoptic Segmentation and Geometry Information for Ro...

引用

IEEE 18th International Conference on Automation Science and engineering (IEEE CASE)

作者： Zhu, Hu Yao, Chen Zhu, Zheng Liu, Zhengtao Jia, Zhenzhong Southern Univ Sci & Technol SUSTech Shenzhen Key Lab Biomimet Robot & Intelligent Sys Dept Mech & Energy Engn Shenzhen 518055 Peoples R China Southern Univ Sci & Technol SUSTech Guangdong Prov Key Lab Human Augmentat & Rehabil Dept Mech & Energy Engn Shenzhen 518055 Peoples R China

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

Mobile robots need reliable maps for autonomous operation. Traditional SLAM systems, which are mainly developed for static scenes, often fail in dynamic environments with moving objects present in the scene. Learning based dynamic SLAM systems often suffer from insufficient or inaccurate identification of feature points. This paper proposes a novel real-time RGB-D SLAM system, which is targeted for dynamic environments, can further enhance feature detection and dynamic removal. This is done by fusing panoptic segmentation and geometry information. The system includes four components: dynamic segmentation that reduces the impact of moving objects, pose estimation with dynamic object removal, panoptic mapping, and loop closing. The pose estimation uses coarse-to-fine dynamic/static classification to further reduce the impact of unknown moving objects. Extensive evaluations demonstrate that our system can achieve robust performance in complex dynamic environments.

关键词： Geometry Visualization Simultaneous localization and mapping computer aided software engineering Automation Feature detection Pose estimation

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Rotational Slippage Minimization in Object Manipulation 18

Rotational Slippage Minimization in Object Manipulation

引用

IEEE 18th International Conference on Automation Science and engineering (IEEE CASE)

作者： Hu, Jiaming Christensen, Henrik, I Univ Calif San Diego Contextual Robot Inst La Jolla CA 92093 USA

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

Rotational slippage due to the gravitational torque is common in grasping tasks using a parallel gripper. To pick the object with a specific desirable grasp pose, if the parallel gripper cannot provide enough force to eliminate the gravitational torque, rotational slippage will cause the manipulation failure. This paper presents an approach to eliminate rotational slippage by pivoting an object on a supporting surface to a pose where it can be picked up, while minimizing the gravitational torque. For evaluation we compare the proposed method with a simple grasping approach, which lifts the object directly, without avoiding slippage. Extensive experiments conducted across both simulation, and real-world environments show that our approach can significantly reduce the rotational slippage problem and help in completing several pick-and-place tasks.

关键词： Torque computer aided software engineering Automation Force Grasping Minimization Task analysis

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Identifying Inconsistencies in the Design of Large-scale Casting Systems - An Ontology-based Approach 18

Identifying Inconsistencies in the Design of Large-scale Cas...

引用

IEEE 18th International Conference on Automation Science and engineering (IEEE CASE)

作者： Ji, Fan Ocker, Felix Zou, Minjie Vogel-Heuser, Birgit Oligschlaeger, Marius Tech Univ Munich TUM Sch Engn & Design Inst Automat & Informat Syst Boltzmannstr 15 D-85748 Garching Germany MDSI Munich Germany MIRMI Munich Germany SMS Grp GmbH Eduard Schloemann Str 4 D-40237 Dusseldorf Germany

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

The development of modern automated production systems requires the close cooperation of engineers from different domains. Due to the large amount of domain-specific documents and heterogeneous data they create during the multidisciplinary engineering activities, ensuring the consistency of information is always challenging. Since most of these documents are texted-based and lack a standardized structure, extracting required information from these files is oftentimes problematic. This issue is particularly critical in the development of large-scale production plants due to the high complexity of the systems and the diversity of disciplines involved. To help engineers efficiently utilize unstructured data sources as well as identify potential information contradictions, we propose an ontology-based inconsistency management approach for large-scale production systems that generates the knowledge base from unstructured engineering data and (semi-) automatically detects multiple types of inconsistencies. In addition, the presented framework also supports the tracking of information changes during the system design process.

关键词： Production systems Casting computer aided software engineering Automation Soft sensors Knowledge based systems Complexity theory

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Balancing Production Capacity of Steelmaking by Considering the Demands of Downstream Processes 18

Balancing Production Capacity of Steelmaking by Considering ...

引用

IEEE 18th International Conference on Automation Science and engineering (IEEE CASE)

作者： Wang, Gongshu Liu, Sibo Lin, Yujun Northeastern Univ Frontier Sci Ctr Ind Intelligence & Syst Optimiza Shenyang Peoples R China Northeastern Univ Liaoning Key Lab Mfg Syst & Logist Optimizat Shenyang Peoples R China Northeastern Univ Liaoning Engn Lab Data Analyt & Optimizat Smart I Shenyang Peoples R China

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

For steel production, due to the characteristics of long process flow, batch production model, limited capacity of bottleneck units and strict delivery requirements, how to balance the production capacity of different units in each stage is an important problem to be solved arising in production management. In this paper, we concentrate on the planning problem at the steelmaking stage with goal of balancing the production capacity of units in the entire production system. To solve the problem, we propose a hierarchical solution framework in which the demands of downstream stages are transmitted to steelmaking stage through planned time windows and a combination of mixed integer programing model and local search heuristics is employed to balance the capacity of units in steelmaking stage. To verify the performance of the proposed solution framework, computational tests are conducted on synthetic instances. The results show the efficiency of the proposed solution framework.

关键词： Integer programming Production systems Production management computer aided software engineering Computational modeling Production Search problems

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Automated Pruning of Polyculture Plants 18

Automated Pruning of Polyculture Plants

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IEEE 18th International Conference on Automation Science and engineering (IEEE CASE)

作者： Presten, Mark Parikh, Rishi Aeron, Shrey Mukherjee, Sandeep Adebola, Simeon Sharma, Satvik Theis, Mark Teitelbaum, Walter Goldberg, Ken Univ Calif Berkeley AUTOLab Berkeley CA 94720 USA UC Santa Cruz Dept Robot Engn Santa Cruz CA USA

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

Polyculture farming has environmental advantages but requires substantially more pruning than monoculture farming. We present novel hardware and algorithms for automated pruning. Using an overhead camera to collect data from a physical scale garden testbed, the autonomous system utilizes a learned Plant Phenotyping convolutional neural network and a Bounding Disk Tracking algorithm to evaluate the individual plant distribution and estimate the state of the garden each day. From this garden state, AlphaGardenSim [1] selects plants to autonomously prune. A trained neural network detects and targets specific prune points on the plant. Two custom-designed pruning tools, compatible with a FarmBot [2] gantry system, are experimentally evaluated and execute autonomous cuts through controlled algorithms. We present results for four 60-day garden cycles. Results suggest the system can autonomously achieve 0.94 normalized plant diversity with pruning shears while maintaining an average canopy coverage of 0.84 by the end of the cycles. For code, videos, and datasets, see this url.

关键词： Automation Target tracking computer aided software engineering Neural networks Visual servoing Hardware Seeds (agriculture)

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SWAP-IT: A Scalable and Lightweight Industry 4.0 Architecture for Cyber-Physical Production Systems 18

SWAP-IT: A Scalable and Lightweight Industry 4.0 Architectur...

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IEEE 18th International Conference on Automation Science and engineering (IEEE CASE)

作者： Luensch, Dennis Detzner, Peter Ebner, Andreas Kerner, Soeren Fraunhofer Inst Mat Flow & Logist Dept Robot & Cognit Syst D-44227 Dortmund Germany Fraunhofer Inst Mat Flow & Logist Dept AI & Autonomous Syst D-44227 Dortmund Germany Fraunhofer Inst Optron Syst Technol & Image Explo Dept Cyber Phys Distributed Syst D-76131 Karlsruhe Germany

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

In recent years, various abstract and practical architectures have been proposed in the context of Industry 4.0. While these architectures focus on different aspects, their common goal is to facilitate the transformation of a static production into a flexible, resilient, interconnected cyber-physical production system (CPPS). However, reviewing those reveals that a general procedure for applying those architectures is missing. In this paper, we propose a modular, scalable and lightweight architecture utilizing simplified semantic information models. We also present an integration guide that helps factory owners and process engineers to apply the proposed architecture. Furthermore, we also show how the factory operators can make architectural decisions according to their needs. This approach will help speed up the application of the architecture for the realization of a modular and scalable CPPS.

关键词： Production systems computer aided software engineering Semantics Production facilities Fourth Industrial Revolution

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Group-based control of large-scale micro-robot swarms with on-board Physical Finite-State Machines 18

Group-based control of large-scale micro-robot swarms with o...

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IEEE 18th International Conference on Automation Science and engineering (IEEE CASE)

作者： Li, Siyu Zefran, Milos Paprotny, Igor Univ Illinois Dept Elect & Comp Engn Chicago IL 60607 USA

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

An important problem in microrobotics is how to control a large group of microrobots with a global control signal. This paper focuses on controlling a large-scale swarm of MicroStressBots with on-board physical finite-state machines. We introduce the concept of group-based control, which makes it possible to scale up the swarm size while reducing the complexity both of robot fabrication as well as swarm control. We prove that the group-based control system is locally accessible in terms of the robot positions. We further hypothesize based on extensive simulations that the system is globally controllable. A nonlinear optimization strategy is proposed to control the swarm by minimizing control effort. We also propose a probabilistically complete collision avoidance method that is suitable for online use. The paper concludes with an evaluation of the proposed methods in simulations.

关键词： Fabrication Uncertainty computer aided software engineering Automata Probabilistic logic Controllability Numerical models

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