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Actuator and sensor fault isolation in a class of nonlinear dynamical systems

Journal of Automation and Intelligence 2024年第2期3卷 57-72页

作者： Hamed Tirandaz Christodoulos Keliris Marios M.Polycarpou KIOS Research Center for Intelligent Systems and Networks and the Department of Electrical and Computer EngineeringUniversity of CyprusNicosia 1678Cyprus

Fault isolation in dynamical systems is a challenging task due to modeling uncertainty and measurement noise,interactive effects of multiple faults and fault *** paper proposes a unified approach for isolation of multiple actuator or sensor faults in a class of nonlinear uncertain dynamical *** and sensor fault isolation are accomplished in two independent modules,that monitor the system and are able to isolate the potential faulty actuator(s)or sensor(s).For the sensor fault isolation(SFI)case,a module is designed which monitors the system and utilizes an adaptive isolation threshold on the output residuals computed via a nonlinear estimation scheme that allows the isolation of single/multiple faulty sensor(s).For the actuator fault isolation(AFI)case,a second module is designed,which utilizes a learning-based scheme for adaptive approximation of faulty actuator(s)and,based on a reasoning decision logic and suitably designed AFI thresholds,the faulty actuator(s)set can be *** effectiveness of the proposed fault isolation approach developed in this paper is demonstrated through a simulation example.

关键词： Actuator and sensor fault isolation Adaptive approximation Observer-based fault diagnosis Reasoning-based decision logic

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Reducing the Computational Cost of Transformers for Person Re-identification

Reducing the Computational Cost of Transformers for Person R...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Wang, Wen Lin, Zheyuan Ji, Shanshan Li, Te Gu, Jason Wan, Minhong Zhang, Chunlong Research Center for Intelligent Robotics Zhejiang Lab Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering Canada

ISBN: (纸本)9798350325706

Transformer-based visual technologies have witnessed remarkable progress in recent years, and person re-identification (ReID) is one of the active research areas that adopts transformers to improve the performance. However, a major challenge of applying transformers to ReID is the high computational cost, which hinders the real-time deployment of such methods. To address this issue, this paper proposes two simple yet effective techniques to reduce the computation of transformers for ReID. The first technique is to eliminate the invalid patches that do not contain any person information, thereby reducing the number of tokens fed into the transformer. Considering that computational complexity is quadratic with respect to input tokens, the second technique partitions the image into multiple windows, applies separate transformers to each window, and merges class tokens from each window, which can reduce the complexity of the self-attention mechanism. By combining these two techniques, our proposed method reduces the SOTA baseline model by 12.2% FLOPs, while slightly improving the rank-1 accuracy and only sacrificing 1.1% mAP on DukeMTMC-ReID dataset. © 2023 IEEE.

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Modeling and Parameter Identification for Human-robot Coupled systems in Powered Lower Limb Prostheses. 5

Modeling and Parameter Identification for Human-robot Couple...

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5th World Robot Conference Symposium on Advanced robotics and Automation, WRC SARA 2023

作者： Huang, Yongshan Wang, Xin Liang, Dingkun Xiong, Jiaming Xie, Anhuan Gu, Jason Research Center for Intelligent Robotics Zhejiang Lab Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNS Canada

ISBN: (纸本)9798350307320

Good trajectory tracking results are the basis for the implementation of other upper-level algorithms in powered lower limb prostheses, which rely on dynamics modeling and good parameter identification. However, powered lower limb prosthesis are human-robot coupled systems with human-inthe-loop, and it has been a challenge to model them as well as to perform parameter identification. This paper proposes a modeling method that can realize the decoupling of human-machine, and by constructing the linearized models of human-machine coupled system and prosthetic subsystem about the physical parameter sets respectively, and finally obtaining the relationship of their corresponding physical parameter sets, thus the method of indirectly identifying the parameters of human-machine coupled system through the prosthetic subsystem can be realized. The experimental results verify the feasibility and effectiveness of the method proposed in this paper. And the experimental results also shows that prosthetic controller should take advantage of dynamic of hip motion in order to make the wearer more comfortable and fluid when swinging the leg, and will also make the prosthesis more energy efficient. © 2023 IEEE.

关键词： Energy efficiency

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Integrated Direct/Indirect Adaptive Robust Control for electrical Driven Injection Machine Mold Closing with Accurate Parameter Estimations 16th

Integrated Direct/Indirect Adaptive Robust Control for Elec...

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16th International Conference on intelligent robotics and Applications, ICIRA 2023

作者： Liao, Jianfeng Zhu, Shiqiang Meng, Qiwei Song, Wei Gu, Jason Research Center for Intelligent Robotics Zhejiang Engineering Research Center for Intelligent Robotics Zhejiang Lab Hangzhou Hangzhou China Zhejiang University Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax Canada

ISBN: (纸本)9789819964949

In this paper, the control issue of the mold closing system of Injection machine is studied. In actual application, there are two major control problems needed to be addressed in controller design: to ensure the quality of products, the precision of mold needs to be guaranteed;the operation parameters of the machines are willing to be recorded for analysis, such as health monitoring and prognosis. However, the existing controllers usually rely on the servo motor, where the dynamics of the mold closing system is not taken into consideration, that may lead to degraded tracking performances. Moreover, the uncertain model parameters are usually ignored or simply treated as disturbances. Instead in this paper, the nonlinear dynamic model of mold closing system is first proposed including parameter uncertainties and disturbances for controller design. Subsequently, an integrated direct/indirect adaptive robust control law(DIARC) is proposed that not only achieves excellent tracking performance but also attenuates the parameter uncertainties with accurate parameter learning. Comparative experiments are carried out to verify our proposed approach and the results demonstrate the effectiveness of the integrated direct/indirect adaptive robust control. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Robust control

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Decision-Making in Robotic Grasping with Large Language Models 16th

Decision-Making in Robotic Grasping with Large Language Mo...

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16th International Conference on intelligent robotics and Applications, ICIRA 2023

作者： Liao, Jianfeng Zhang, Haoyang Qian, Haofu Meng, Qiwei Sun, Yinan Sun, Yao Song, Wei Zhu, Shiqiang Gu, Jason Research Center for Intelligent Robotics Zhejiang Lab Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Zhejiang University Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax Canada

ISBN: (纸本)9789819964949

Recent advances in large language models have highlighted their potential to encode massive amounts of semantic knowledge for long-term autonomous decision-making, positioning them as a promising solution for powering the cognitive capabilities of future home-assistant robots. However, while large language models can provide high-level decision, there is still no unified paradigm for integrating them with robots’ perception and low-level action. In this paper, we propose a framework centered around a large language model, integrated with visual perception and motion planning modules, to investigate the robotic grasping task. Unlike traditional methods that only focus on generating stable grasps, our proposed approach can handle personalized user instructions and perform tasks more effectively in home scenarios. Our approach integrates existing state-of-the-art models in a simple and effective way, without requiring any fine-tuning, which makes it low-cost and easy to deploy. Experiments on a physical robot system demonstrate the feasibility of our approach. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Decision making

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Sub-Optimal Decentralized Navigation of Multiple Holonomic Agents in Simply-Connected Workspaces 63

Sub-Optimal Decentralized Navigation of Multiple Holonomic A...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Kotsinis, Dimitrios Bechlioulis, Charalampos P. Robotics Institute Maroussi Greece University of Patras Athena Research Center Department of Electrical and Computer Engineering Greece

ISBN: (纸本)9798350316339

In this paper, we propose a sub-optimal approach for the multi-agent navigation problem in simply-connected workspaces. We design a decentralized control law exhibiting the following three properties: (1) navigation of each agent with the optimal policy towards its destination, (2) avoidance of collision with other nearby agents and the workspace boundary, and (3) knowledge about the current position and not the destination of nearby agents. Moreover, we refer to the sub-optimal approach because the computational complexity and time needed to calculate the global optimal solution become unrealistic as the number of agents increases. In our case, each agent has a predetermined optimal policy calculated by a novel off-policy iterative method, to go towards its destination and it deviates from it in order to avoid collisions. The purpose of the simulation study is to examine how much the sub-optimal greedy trajectory of each agent deviates from the optimal one. © 2024 IEEE.

关键词： Decentralized control

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Design and Development of the Dual-Arm Robot DARO 5

Design and Development of the Dual-Arm Robot DARO

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5th World Robot Conference Symposium on Advanced robotics and Automation, WRC SARA 2023

作者： Liu, Yun Huang, Qiulang Zhang, Pu Yan, Mindong Liang, Dingkun Kong, Lingyu Wang, Xin Xie, Anhuan Gu, Jason Zhu, Shiqiang Research Institute of Interdisciplinary Innovation Zhejiang Lab Research Center for Intelligent Robotics Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Dalhousie University Electrical and Computer Engineering HalifaxNS Canada

ISBN: (纸本)9798350307320

This paper presents the design and development of a humanoid dual-arm robot called DARO, along with its improved version, DARO-N. DARO and DARO-N consist of two arms and humanoid hands, each with 6/7 degrees of freedom for the arms and 7 active degrees of freedom for the hands. Modular commercial actuators are employed as the driving joints of the arms, allowing for reduced development time and cost. The design principles of modularity, simplicity, lightweight construction, human likeness, information perception capability, and scalability are incorporated into the design. Furthermore, this work establishes a control framework for the humanoid dual-arm robot and conducts simulations and multiple physical experiments to validate the performance of the robots. © 2023 IEEE.

关键词： Degrees of freedom (mechanics)

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Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

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computer Modeling in engineering & Sciences 2024年第2期138卷 1341-1364页

作者： Mohamed Zarouan Ibrahim M.Mehedi Shaikh Abdul Latif Md.Masud Rana Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Electronic Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh

Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Industry ***, various modernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with monitoring the status of *** diagnosis of rotating machines serves a main role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand human knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and automatic feature learning. Therefore, this article designs a Gradient Optimizer Algorithm with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environment. The presented GOAHDL-FDC technique initially applies continuous wavelettransform (CWT) for preprocessing the actual vibrational signals of the rotating machinery. Next, the residualnetwork (ResNet18) model was exploited for the extraction of features from the vibration signals which are thenfed into theHDLmodel for automated fault detection. Finally, theGOA-based hyperparameter tuning is performedtoadjust the parameter valuesof theHDLmodel *** experimental result analysis of the GOAHDL-FD Calgorithm takes place using a series of simulations and the experimentation outcomes highlight the better resultsof the GOAHDL-FDC technique under different aspects.

关键词： Fault detection Industry 4.0 gradient optimizer algorithm deep learning rotating machineries artificial intelligence

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Vision-Based Categorical Object Pose Estimation and Manipulation 16th

Vision-Based Categorical Object Pose Estimation and Manipul...

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16th International Conference on intelligent robotics and Applications, ICIRA 2023

作者： Meng, Qiwei Liao, Jianfeng Jun, Shao Xu, Nuo Xu, Zeming Sun, Yinan Sun, Yao Zhu, Shiqiang Gu, Jason Song, Wei Center for Intelligent Robotics Zhejiang Lab Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China School of Mechanical Engineering Zhejiang University Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax Canada

ISBN: (纸本)9789819964826

Object manipulation and environment interaction are of great significance for intelligent robots, especially service robots working under unstructured household and office scenarios. This paper proposes a novel approach for categorical unseen object grasping and manipulation. Different from recently popular end-to-end reinforcement learning methods, we develop models for geometric primitive abstraction of target objects, and accordingly estimate their pose as well as generate task-orientated grasp points. Such design emphasizes visual perception in guiding robotic manipulation, thereby enhancing model interpretability and reliability during implementation. In addition, we also conduct object grasping experiments both under simulation and real-world settings, which further verify the effectiveness and superiority of our method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： intelligent robots

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Real-time Architecture for Audio-Visual Active Speaker Detection

Real-time Architecture for Audio-Visual Active Speaker Detec...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Huang, Min Wang, Wen Lin, Zheyuan Tesema, Fiseha B. Ji, Shanshan Gu, Jason Wan, Minhong Song, Wei Li, Te Zhu, Shiqiang The Intelligent Robotics Research Center Zhejiang Lab Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Department of Electrical and Computer Engineering Dalhousie University Canada

ISBN: (纸本)9781665481090

Continuously measuring the speaking state of users with robot in a human-robot Interaction(HRI) system improves metrics of interaction quality. Meanwhile, mainstream active speaker detection (ASD) algorithms emphasize achieving high AUCs at frame level in the AVA-Active Speaker dataset and pay less attention to get real-time performance in robotic systems. In this paper, we propose a model named FSDNet to keep a high AUC score in the AVA-Active Speaker dataset while reducing time cost, our model increase AUC score by 0.1% compared with the State-Of-The-Art and need only 75% running time. Furthermore, we put forward an architecture with a time-related prediction function to make our algorithm more effective and generative in interactive robotic systems. The code is released at https://***/huangmin9966/FSDNet-RealTimeArch. © 2022 IEEE.

关键词： Human robot interaction

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