IEEE Transactions on Systems Man Cybernetics-Systems最新文献

{"title":"Robust Energy Consumption Prediction With a Missing Value-Resilient Metaheuristic-Based Neural Network in Mobile App Development","authors":"Seyed Jalaleddin Mousavirad;Luís A. Alexandre","doi":"10.1109/TSMC.2025.3543786","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3543786","url":null,"abstract":"Energy consumption is a fundamental concern in mobile application development, bearing substantial significance for both developers and end-users. Main objective of this research is to propose a novel neural network-based framework, enhanced by a metaheuristic approach, to achieve robust energy prediction in the context of mobile app development. The metaheuristic approach here aims to achieve two goals: 1) identifying suitable learning algorithms and their corresponding hyperparameters, and 2) determining the optimal number of layers and neurons within each layer. Moreover, due to limitations in accessing certain aspects of a mobile phone, there might be missing data in the data set, and the proposed framework can handle this. In addition, we conducted an optimal algorithm selection strategy, employing 13 base and advanced metaheuristic algorithms, to identify the best algorithm based on accuracy and resistance to missing values. The representation in our proposed metaheuristic algorithm is variable-size, meaning that the length of the candidate solutions changes over time. We compared the algorithms based on the architecture found by each algorithm at different levels of missing values, accuracy, F-measure, and stability analysis. Additionally, we conducted a Wilcoxon signed-rank test for statistical comparison of the results. The extensive experiments show that our proposed approach significantly improves energy consumption prediction. Particularly, the JADE algorithm, a variant of differential evolution (DE), DE, and the covariance matrix adaptation evolution strategy deliver superior results under various conditions and across different missing value levels.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3642-3653"},"PeriodicalIF":8.6,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DIG: Improved DINO for Graffiti Detection","authors":"Bingshu Wang;Qianchen Mao;Aifei Liu;Long Chen;C. L. Philip Chen","doi":"10.1109/TSMC.2025.3541795","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3541795","url":null,"abstract":"Graffiti detection is essential in historic building protection and urban neighborhood management. Graffiti detection has made significant progress in recent years based on the development of deep learning. However, small-scale graffiti, interference from the background, and the false detection of word parts in graffiti make it a challenging problem. This article proposes a Transformer-based high-precision graffiti detection method, namely DIG. Precisely, it consists of three modules: 1) Spatial query selection (SQS), scale-aware IoU loss (SIL); 2) Denoising Task with binary contrastive denoising (BCDN); and 3) IoU-guided box denoising (IBD) modules. To detect small-scale graffiti, this paper proposes SIL to help the loss function to perceive small-scale graffiti and large-scale graffiti fairly. To reduce the false detection of word parts, this article presents the SQS module, which integrates spatial information into the query selection process of the Encoder to filter out falsely detected bounding boxes within the graffiti. To reduce the interference from the background, this article introduces a denoising task with BCDN and IBD modules, improving the model’s ability to distinguish graffiti from the background and accurately select appropriate bounding boxes. A large number of experimental results on the STORM dataset show that our method achieves state-of-the-art results with an <inline-formula> <tex-math>$AP_{50}$ </tex-math></inline-formula> of 87.9%. Moreover, DIG achieved competitive results on the FineFM dataset for mask detection. This indicates that DIG can also be conveniently transferred to detect other scenarios.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3557-3569"},"PeriodicalIF":8.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cognitive Robotics: Enhancing Multirobot Target Search in Unknown Environments Through Adaptive Communication Strategies","authors":"Xuewei Yu;Bo Su;Ziheng Wang;Jianlei Zhang;Chunyan Zhang","doi":"10.1109/TSMC.2025.3540059","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3540059","url":null,"abstract":"This article presents a novel approach to improving multitarget searching in unknown environments using multirobot systems while ensuring adaptability to changing communication conditions. The proposed method addresses challenges arising from limited scope, dynamic circumstances, and inaccurate decision data due to communication disruptions or interference in real-world scenarios. A comprehensive environmental map is generated using a grid-based mapping methodology, encompassing data related to obstacles, coverage, target occupancy, and communication conditions. Considering the constraints imposed by communication conditions, we develop the adaptive communication condition hierarchical distributed model predictive control framework. This framework incorporates a hierarchical communication strategy for multirobot target search. To assess the effectiveness of our approach, a series of comparative experiments are conducted on three distinct maps, each characterized by unique communication environments, obstacle layouts, and target distributions. These experiments employ four commonly used swarm intelligence algorithms. The research findings indicate that implementing the proposed search framework and communication strategy significantly reduces the time and communication costs associated with locating targets in complex and unfamiliar environments. This is particularly relevant for multirobot systems operating under diverse and limited communication conditions, substantially increasing the task’s success rate.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3449-3463"},"PeriodicalIF":8.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural Network-Based Indirect Adaptive Force Control of a Two-Fingered Hand Exoskeleton Toward Robust Grasping Assistance","authors":"Kaushik Halder;Arnab Roy;M. Felix Orlando","doi":"10.1109/TSMC.2025.3541994","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3541994","url":null,"abstract":"Grasping task is one of the crucial objectives in activities of daily living. However, elderly human subjects are facing significant challenges when attempting to perform grasping task. In this regard, a hand exoskeleton with a proper force control strategy is necessary to improve the performance of assistive technology. In this article, a lightweight, size-adjustable, underactuated, and force-controllable two-fingered exoskeleton prototype is developed for grasping assistance. A novel radial basis function network-based indirect adaptive force controller for robust grasping assistance is proposed along with the prototype design. We have conducted real-time grasping experiments on six elderly human subjects to verify the feasibility of the developed exoskeleton with a novel grasping force control strategy. Furthermore, we have performed force trajectory tracking experiment to validate the efficacy of the proposed force control scheme. Moreover, the robustness of the proposed grasping force control strategy has been validated through a disturbance rejection experiment. Extensive simulation and experimental studies with the developed kinematic model and feasibility tests involving elderly human subjects show that the newly developed hand exoskeleton with the proposed robust intelligent control strategy is efficient for object-grasping tasks aimed at the assistance of elderly human subjects.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3614-3629"},"PeriodicalIF":8.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Group-Based Many-Task Collaborative Optimization Framework for Evolutionary Robots Design","authors":"Yaqing Hou;Zhaoping Yu;Zheng Guo;Wenbin Pei;Yaoxin Wu;Hongwei Ge;Bing Xue;Mengjie Zhang","doi":"10.1109/TSMC.2025.3541002","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3541002","url":null,"abstract":"In evolutionary robotics (ER), the evolution of a robot’s morphology (i.e., physical structure) or controller (i.e., control algorithm or instruction sequence) often entails tackling an extensive number of tasks. The use of evolutionary multitasking (EMT) in ER, which optimizes multiple tasks simultaneously by reusing potentially useful knowledge across diverse tasks, could improve the performance of problem-solving to each task. However, existing EMT methods do not fully use intertask correlations, limiting knowledge sharing. In view of this, this study introduces a novel framework, termed adaptive group-based collaborative optimization, tailored for handling optimization problems involving a large number of tasks within the ER domain simultaneously. The proposed framework divides tasks into groups according to their similarity and then proceeds through two principal stages, namely, intergroup knowledge separation and intragroup knowledge reunion. During intergroup knowledge separation stage, an adaptive method for selecting crossover operators enables source tasks to share useful knowledge to the target task across groups. During intragroup knowledge reunion stage, an adaptive knowledge combination strategy facilitates the target task in assimilating knowledge from multiple sources intragroup. We validated the efficacy of the proposed framework in both planar manipulators and hexapod robot experiments. The results indicate that our method outperforms existing state-of-the-art algorithms (i.e., MME, MMKT) on several metrics (e.g., mean fitness and quality diversity metrics). The proposed method can effectively improve the effectiveness and diversity of solutions in solving ER problems with a large number of tasks (e.g., 5 000 or 10 000), and has broad potential in practical ER applications.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3492-3505"},"PeriodicalIF":8.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Integrated Control Framework for Safe and Ergonomic Human-Drone Interaction in Industrial Warehouses","authors":"Silvia Proia;Graziana Cavone;Paolo Scarabaggio;Raffaele Carli;Mariagrazia Dotoli","doi":"10.1109/TSMC.2025.3540635","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3540635","url":null,"abstract":"This study introduces a novel control framework for human-drone interaction (HDI) in industrial warehouses, targeting pick-and-delivery operations. The goals are to enhance operator safety as well as well-being and, at the same time, to improve efficiency and reduce production costs. To these aims, the speed and separation monitoring (SSM) operation method is employed for the first time in HDI, drawing an analogy to the safety requirements outlined in collaborative robots’ ISO standards. The so-called protective separation distance is used to ensure the safety of operators engaged in collaborative tasks with drones. In addition, we employ the rapid upper limb assessment (RULA) method to evaluate the ergonomic posture of operators during interactions with drones. To validate the proposed approach in a realistic industrial setting, a quadrotor is deployed for pick-and-delivery tasks along a predefined trajectory from the picking bay to the palletizing area, where the interaction between the drone and a moving operator takes place. The drone navigates toward the interaction space while avoiding collisions with shelves and other drones in motion. The control strategy for the drone cruise navigation integrates simultaneously the time-variant artificial potential field (APF) technique for trajectory planning and the iterative linear quadratic regulator (LQR) controller for trajectory tracking. Differently, in the descent phase, the receding horizon LQR algorithm is employed to follow a trajectory planned in accordance with the SSM, which starts from the approach point at the border of the interaction space and ends in the volume with the operator’s minimum RULA. The presented control strategy facilitates drone management by adapting the drone’s position to changes in the operator’s position while satisfying HDI safety requirements. The results of the proposed HDI framework simulations for the case study demonstrate the effectiveness of the method in ensuring a safe and ergonomic HDI within industrial warehouses.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3570-3585"},"PeriodicalIF":8.6,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hyperbolic Sine Function-Based Full-State Feedback Attitude Tracking Control for Rigid Spacecraft","authors":"Rui-Qi Dong;Ai-Guo Wu;Bin Li;Guang-Ren Duan","doi":"10.1109/TSMC.2024.3524479","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3524479","url":null,"abstract":"The attitude tracking control with unwinding-free performance for rigid spacecraft is studied in this article. A full-state feedback control law based on a hyperbolic sine function is developed such that the resulted closed-loop system can achieve two stable equilibria. By Lyapunov stability theory and Barbalat’s Lemma, it is proven that the obtained closed-loop system is almost globally asymptotically stable, and achieves unwinding-free performance. Further, by constructing a strict Lyapunov function, it is demonstrated that the two stable equilibria are exponentially stable. Moreover, subsets of attraction regions corresponding to each stable equilibrium are characterized. The simulation results illustrate that the proposed attitude control scheme can effectively avoid the unwinding problem during attitude tracking.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3412-3424"},"PeriodicalIF":8.6,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cross-Domain Random Pretraining With Prototypes for Reinforcement Learning","authors":"Xin Liu;Yaran Chen;Haoran Li;Boyu Li;Dongbin Zhao","doi":"10.1109/TSMC.2025.3541926","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3541926","url":null,"abstract":"Unsupervised cross-domain reinforcement learning (RL) pretraining shows great potential for challenging continuous visual control but poses a big challenge. In this article, we propose cross-domain random pretraining with prototypes (CRPTpro), a novel, efficient, and effective self-supervised cross-domain RL pretraining framework. CRPTpro decouples data sampling from encoder pretraining, proposing decoupled random collection to easily and quickly generate a qualified cross-domain pretraining dataset. Moreover, a novel prototypical self-supervised algorithm is proposed to pretrain an effective visual encoder that is generic across different domains. Without finetuning, the cross-domain encoder can be implemented for challenging downstream tasks defined in different domains, either seen or unseen. Compared with recent advanced methods, CRPTpro achieves better performance on downstream policy learning without extra training on exploration agents for data collection, greatly reducing the burden of pretraining. We conduct extensive experiments across multiple challenging continuous visual-control domains, including balance control, robot locomotion, and manipulation. CRPTpro significantly outperforms the next best Proto-RL(C) on 11/12 cross-domain downstream tasks with only 54.5% wall-clock pretraining time, exhibiting state-of-the-art pretraining performance with greatly improved pretraining efficiency.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3601-3613"},"PeriodicalIF":8.6,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual Event-Triggered-Based Fault-Tolerant Attitude Flexible Performance Tracking Control for Satellite","authors":"Baomin Li;Mou Chen;Jianwei Xia","doi":"10.1109/TSMC.2025.3540280","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3540280","url":null,"abstract":"In this article, a dual event-triggered (ET)-based fault-tolerant attitude flexible performance tracking control problem is studied for the satellite with input saturation, actuator fault and external disturbance. To make the prescribed performance function (PPF) be adjusted only when the attitude tracking error of the satellite violates the PPF, a predictive tracking error-based ET mechanism is designed. With the designed mechanism, the fault factor adaptive law and saturation difference are updated only when the tracking error violates the PPF. In addition, an ET command regulation scheme is designed, taking into account the performance of the system and the saving of communication resources. It is proved that the closed-loop system is stable by the Lyapunov method. Finally, the simulation results demonstrate the availability of the proposed tracking control scheme.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3480-3491"},"PeriodicalIF":8.6,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive Prescribed Finite-Time Bipartite Consensus Control for Nonaffine Nonlinear MASs Under Structurally Unbalanced Topology","authors":"Xiaomei Wang;Yongduan Song;Xudong Zhao;Huanqing Wang;Ding Wang;Ben Niu","doi":"10.1109/TSMC.2025.3540897","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3540897","url":null,"abstract":"This article investigates an adaptive bipartite consensus tracking control algorithm for a class of heterogeneous nonaffine nonlinear multiagent systems (MASs) with prescribed finite-time tracking performance under an unbalanced communication topology. In the case of an unbalanced digraph, a novel locally optimal bipartition strategy is proposed to transform the unbalanced communication topology into a structurally balanced one, thereby enabling the implementation of bipartite consensus tracking control. To achieve the expected tracking performance, the design philosophy focuses on developing a prescribed finite-time performance function (PFTPF), capable of preassigning the convergence time and accuracy precisely beforehand. The explored adaptive control algorithm can ensure that the whole signals concerning the closed-loop MASs remain bounded while the bipartite consensus errors converge to a predetermined range around zero within the prescribed finite time. Ultimately, the simulation results on robotic systems prove the availability of the developed design solution.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3532-3541"},"PeriodicalIF":8.6,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}