IEEE Transactions on Cognitive and Developmental Systems最新文献_第6页

A Behavioral Decision-Making Model of Learning and Memory for Mobile Robot Triggered by Curiosity 由好奇心触发的移动机器人学习和记忆行为决策模型

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-09-05 DOI: 10.1109/TCDS.2024.3454779

Dongshu Wang;Qi Liu;Xulin Gao;Lei Liu

{"title":"A Behavioral Decision-Making Model of Learning and Memory for Mobile Robot Triggered by Curiosity","authors":"Dongshu Wang;Qi Liu;Xulin Gao;Lei Liu","doi":"10.1109/TCDS.2024.3454779","DOIUrl":"10.1109/TCDS.2024.3454779","url":null,"abstract":"Learning and memorizing behavioral decision in the process of environmental cognition to guide future decision is an important aspect of research and application in mobile robotics. Traditional rule-based behavioral decision approaches have difficulty in adapting to complex and changing environments. The offline decision-making approaches lead to poor adaptability to dynamic environments, while behavioral decision-making based on reinforcement learning relies on data acquisition, and the learned knowledge cannot guide mobile robots to quickly adapt to new environments. To address this issue, this article proposes a brain-inspired behavioral decision model that can perform incremental learning by simulating the logical structure of memory classification in the brain, as well as the memory conversion mechanisms of hippocampus, prefrontal cortex, and anterior cingulate cortex. The model interacts with the environment through semisupervised learning and learns the current decision online, simulating the memory function of humans to enable mobile robots to adapt to changing environments. In addition, an internal reward mechanism driven by curiosity is designed, simulating the reinforcement mechanism of curiosity in human memory, encoding the memory of unfamiliar behavioral decisions for mobile robots, and consolidating the memory of frequently made behavioral decisions, improving the learning and memory capacity of mobile robots in environmental cognition. The feasibility of the proposed model is verified by physical experiments in different environments.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 2","pages":"352-365"},"PeriodicalIF":5.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Brain Compensatory Mechanisms During the Prolonged Cognitive Task: fNIRS and Eye-Tracking Study 长时间认知任务中的大脑补偿机制：fNIRS 和眼动跟踪研究

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-09-04 DOI: 10.1109/TCDS.2024.3453590

A. A. Badarin;V. M. Antipov;V. V. Grubov;A. V. Andreev;E. N. Pitsik;S. A. Kurkin;A. E. Hramov

{"title":"Brain Compensatory Mechanisms During the Prolonged Cognitive Task: fNIRS and Eye-Tracking Study","authors":"A. A. Badarin;V. M. Antipov;V. V. Grubov;A. V. Andreev;E. N. Pitsik;S. A. Kurkin;A. E. Hramov","doi":"10.1109/TCDS.2024.3453590","DOIUrl":"10.1109/TCDS.2024.3453590","url":null,"abstract":"The problem of maintaining cognitive performance under fatigue is crucial in fields requiring high concentration and efficiency to successfully complete critical tasks. In this context, the study of compensatory mechanisms that help the brain overcome fatigue is particularly important. This research investigates the correlations between physiological, behavioral, and subjective measures while considering the impact of fatigue on the performance of working memory tasks. A combined approach of functional near-infrared spectroscopy (fNIRS) and eye-tracking was used to reconstruct brain functional networks based on fNIRS data and analyze them in terms of network characteristics such as global clustering coefficient and global efficiency. Results showed a significant increase in subjective fatigue but no significant change in performance during the experiment. The study confirmed that despite fatigue, subjects can maintain performance through compensatory mechanisms, increasing mental effort, with the level of compensation depending on the task's complexity. Furthermore, the study showed that compensatory effort maintains the efficiency of the frontoparietal network, and the degree of compensatory effort is related to the difference in response times between high- and low-complexity tasks.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 2","pages":"303-314"},"PeriodicalIF":5.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pretrained Dynamics Learning of Numerous Heterogeneous Robots and Gen2Real Transfer 众多异构机器人的预训练动态学习和 Gen2Real 传输

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-09-04 DOI: 10.1109/TCDS.2024.3454240

Dengpeng Xing;Yiming Yang;Jiale Li

{"title":"Pretrained Dynamics Learning of Numerous Heterogeneous Robots and Gen2Real Transfer","authors":"Dengpeng Xing;Yiming Yang;Jiale Li","doi":"10.1109/TCDS.2024.3454240","DOIUrl":"10.1109/TCDS.2024.3454240","url":null,"abstract":"Acquiring dynamics is vital for robotic learning and serves as the foundation for planning and control. This article addresses two essential inquiries: How can one develop a model that encompasses a vast array of diverse robotic dynamics? Is it possible to establish a model that alleviates the burdens of data collection and domain expertise necessary for constructing specific robot models? We explore the dynamics present in a dataset containing numerous serial articulated robots and introduce a novel concept, “Gen2Real,” to transfer simulated, generalized models to physical, and specialized robots. By randomizing dynamics parameters, topological configurations, and model dimensions, we generate an extensive dataset that corresponds to varying properties, connections, and quantities of robotic links. A structure adapted from the generative pretrained transformer is employed to approximate the dynamics of a multitude of heterogeneous robots. Within Gen2Real, we transfer the pretrained model to a target robot using distillation to enable real-time computation. The results corroborate the superiority of the proposed method in terms of accurately learning an immense scope of robotic dynamics, managing commonly encountered disturbances, and exhibiting versatility in transferring to distinct robots.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 2","pages":"315-327"},"PeriodicalIF":5.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biomimetic Spiking Neural Network Based on Monolayer 2-D Synapse With Short-Term Plasticity for Auditory Brainstem Processing 基于具有短期可塑性的单层二维突触的仿生尖峰神经网络用于听觉脑干处理

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-08-29 DOI: 10.1109/TCDS.2024.3450915

Jieun Kim;Peng Zhou;Unbok Wi;Bomin Joo;Donguk Choi;Myeong-Lok Seol;Sravya Pulavarthi;Linfeng Sun;Heejun Yang;Woo Jong Yu;Jin-Woo Han;Sung-Mo Kang;Bai-Sun Kong

{"title":"Biomimetic Spiking Neural Network Based on Monolayer 2-D Synapse With Short-Term Plasticity for Auditory Brainstem Processing","authors":"Jieun Kim;Peng Zhou;Unbok Wi;Bomin Joo;Donguk Choi;Myeong-Lok Seol;Sravya Pulavarthi;Linfeng Sun;Heejun Yang;Woo Jong Yu;Jin-Woo Han;Sung-Mo Kang;Bai-Sun Kong","doi":"10.1109/TCDS.2024.3450915","DOIUrl":"10.1109/TCDS.2024.3450915","url":null,"abstract":"In the sound localization of species, short-term depression (STD) plays an important role in maintaining interaural timing difference (ITD) sensitivity. In this article, a biomimetic spiking neural network (SNN) utilizing 2-D synaptic devices for mimicking biological sound localization is presented. A two-terminal monolayer device is used as the artificial synapse, whose temporal conductance change mimics the STD of a synapse. Alpha synaptic current and leaky integrate-and-fire (LIF) neuron models are used for realistic cortical operation. Lateral inhibition and superior olivary nucleus (SON) are adopted to increase the acuteness, to compensate for the interaural level difference (ILD)-induced disturbance, and to enlarge the sound intensity range. By combining solid-state STD synapses and bio-plausible cortical models with an ITD-based coincidence detection mechanism to mimic the auditory brainstem processing, our SNN achieved sound localization with a human-level resolution of 1°.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 2","pages":"247-258"},"PeriodicalIF":5.0,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identifying Longitudinal Intermediate Phenotypes Between Genotypes and Clinical Score via Exclusive Relationship-Induced Association Analysis in Alzheimer's Disease 通过排他性关系诱导关联分析确定阿尔茨海默病基因型与临床评分之间的纵向中间表型

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-08-28 DOI: 10.1109/TCDS.2024.3451232

Meiling Wang;Wei Shao;Shuo Huang;Daoqiang Zhang

{"title":"Identifying Longitudinal Intermediate Phenotypes Between Genotypes and Clinical Score via Exclusive Relationship-Induced Association Analysis in Alzheimer's Disease","authors":"Meiling Wang;Wei Shao;Shuo Huang;Daoqiang Zhang","doi":"10.1109/TCDS.2024.3451232","DOIUrl":"10.1109/TCDS.2024.3451232","url":null,"abstract":"As a widely focused topic, brain imaging genetics has achieved great successes in the diagnosis of complex brain disorders. In clinical application, the imaging phenotypes affected via genetic factors will change over time. A clinical score-relevant exclusive relationship-induced multimodality learning (CS-ERMM) framework is proposed for integrating longitudinal neuroimage, genetics, and clinical score data. Specifically, first, the exclusive lasso term is used to construct the exclusive multimodality learning method, which can convey the unique information at a specific time point. The relationship-induced term is then introduced to automatically learn the relatedness among the multiple time-points from data, which explores the association between genotypes and longitudinal imaging phenotypes to facilitate the understanding of the degenerative process. Finally, the clinical score outcomes are integrated into such association model, which discovers longitudinal phenotypic markers associated with the Alzheimer's disease risk single nucleotide polymorphism that are relevant to clinical score outcomes. We also design a proximal alternating optimization strategy to solve the constructed CS-ERMM model. Extensive experimental results on brain imaging genetic data from the Alzheimer's disease neuroimaging initiative dataset have validated that our method outperforms several competing approaches, which achieve strong associations and identify important consistent markers across longitudinal phenotypes related to genetic risk biomarkers for disease interpretation.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 2","pages":"340-351"},"PeriodicalIF":5.0,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

UAV Coverage Path Planning of Multiple Disconnected Regions Based on Cooperative Optimization Algorithms 基于合作优化算法的多个互不相连区域的无人机覆盖路径规划

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-08-19 DOI: 10.1109/TCDS.2024.3442957

Yang Lyu;Shuyue Wang;Tianmi Hu;Quan Pan

{"title":"UAV Coverage Path Planning of Multiple Disconnected Regions Based on Cooperative Optimization Algorithms","authors":"Yang Lyu;Shuyue Wang;Tianmi Hu;Quan Pan","doi":"10.1109/TCDS.2024.3442957","DOIUrl":"10.1109/TCDS.2024.3442957","url":null,"abstract":"This article addresses the coverage path planning problem when an unmanned aerial vehicle (UAV) surveys an unknown site composed of multiple isolated areas. The problem is typically non-deterministic polynomial-time hard(NP-hard) and cannot be easily solved, especially when considering the scale of each area. By decomposing the problem into two cascaded subproblems—1) covering a specific polygon area; and 2) determining the optimal visiting order of different areas—an approximate solution can be found more efficiently. First, the target areas are approximated as convex polygons, and the coverage pattern is designed based on four control points. Then, the optimal visiting order is determined based on a state defined by area indices and control points. We propose two different optimization methods to solve this problem. The first method is a direct extension of the genetic algorithm, using a customized coding method. The second method is a reinforcement learning-based (RL-based) approach that solves the problem as a variant of the traveling salesman problem (TSP) through end-to-end policy training. The simulation results indicate that the proposed methods can provide solutions to the multiple-area coverage problem with competitive optimality and efficiency.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 2","pages":"259-270"},"PeriodicalIF":5.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Location Reasoning of Target Objects Based on Human Common Sense and Robot Experiences 基于人类常识和机器人经验的目标物体位置推理

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-08-13 DOI: 10.1109/TCDS.2024.3442862

Yueguang Ge;Yinghao Cai;Shuo Wang;Shaolin Zhang;Tao Lu;Haitao Wang;Junhang Wei

{"title":"Location Reasoning of Target Objects Based on Human Common Sense and Robot Experiences","authors":"Yueguang Ge;Yinghao Cai;Shuo Wang;Shaolin Zhang;Tao Lu;Haitao Wang;Junhang Wei","doi":"10.1109/TCDS.2024.3442862","DOIUrl":"10.1109/TCDS.2024.3442862","url":null,"abstract":"The location reasoning of target objects in robot-operated environment is a challenging task. Objects that robots need to interact with are often located at a distance or are contained within containers, making them inaccessible for direct observation by the robot. The uncertainty of the storage location of the target objects and the lack of reasoning ability present considerable challenges. In this article, we propose a method for semantic localization of robot-operated objects based on human common sense and robot experiences. Instead of reasoning the object storage locations solely based on the category of the target object, a probabilistic ontology model is introduced to represent uncertain knowledge in the task of object localization, which combines the expressive power of classical first-order logic and the inference capability of Bayesian inference. The target location is then estimated using the probabilistic ontologies with dynamic integration of human common sense and robot experiences. Experimental results in both simulation and real-world environments demonstrate the effectiveness of the proposed integration of human common sense and robot experiences in the task of semantic localization of robot-operated objects.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 2","pages":"287-302"},"PeriodicalIF":5.0,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multimodal Emotion Fusion Mechanism and Empathetic Responses in Companion Robots 多模态情感融合机制与陪伴机器人的情感反应

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-08-13 DOI: 10.1109/TCDS.2024.3442203

Xiaofeng Liu;Qincheng Lv;Jie Li;Siyang Song;Angelo Cangelosi

{"title":"Multimodal Emotion Fusion Mechanism and Empathetic Responses in Companion Robots","authors":"Xiaofeng Liu;Qincheng Lv;Jie Li;Siyang Song;Angelo Cangelosi","doi":"10.1109/TCDS.2024.3442203","DOIUrl":"10.1109/TCDS.2024.3442203","url":null,"abstract":"The ability of humanoid robots to exhibit empathetic facial expressions and provide corresponding responses is essential for natural human–robot interaction. To enhance this, we integrate the GPT3.5 model with a facial expression recognition model, creating a multimodal emotion recognition system. Additionally, we address the challenge of realistically mimicking human facial expressions by designing the physical structure of a humanoid robot. Initially, we develop a humanoid robot capable of adjusting the positions of its facial organs and neck through servo displacement to achieve more natural facial expressions. Subsequently, to overcome the current limitation where emotional interaction robots struggle to accurately recognize user emotions, we introduce a coupled generative pretrained transformer (GPT)-based multimodal emotion recognition method that utilizes both text and images, thereby enhancing the robot's emotion recognition accuracy. Finally, we integrate the GPT-3.5 model to generate empathetic responses based on recognized user emotional states and language text, which are then mapped onto the robot to enable empathetic expressions that can achieve a more comfortable human–machine interaction experience. Experimental results on benchmark databases demonstrate that the performance of the coupled GPT-based multimodal emotion recognition method using text and images outperforms other approaches, and it possesses unique empathetic response capabilities relative to alternative methods.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 2","pages":"271-286"},"PeriodicalIF":5.0,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Impedance Recognition Framework Based on Electromyogram for Physical Human–Robot Interaction 基于肌电图的物理人机交互阻抗识别框架

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-08-13 DOI: 10.1109/TCDS.2024.3442172

Jing Luo;Chaoyi Zhang;Chao Zeng;Yiming Jiang;Chenguang Yang

{"title":"An Impedance Recognition Framework Based on Electromyogram for Physical Human–Robot Interaction","authors":"Jing Luo;Chaoyi Zhang;Chao Zeng;Yiming Jiang;Chenguang Yang","doi":"10.1109/TCDS.2024.3442172","DOIUrl":"10.1109/TCDS.2024.3442172","url":null,"abstract":"In physical human–robot interaction (pHRI), the interaction profiles, such as impedance and interaction force are greatly influenced by the operator's muscle activities, impedance and interaction force between the robot and the operator. Actually, parameters of interaction profiles are easy to be measured, such as position, velocity, acceleration, and muscle activities. However, the impedance cannot be directly measured. In some areas, it is difficult to capture the force information, especially where the force sensor is hard to be attached on the robots. In this sense, it is worth developing a feasible and simple solution to recognize the impedance parameters by exploring the potential relationship among the above mentioned interaction profiles. To this end, a framework of impedance recognition based on different time-based weight membership functions with broad learning system (TWMF-BLS) is developed for stable/unstable pHRI. Specifically, a linear weight membership function and a nonlinear weight membership function are proposed for stable and unstable pHRI by using the hybrid features for estimating the interaction force. And then the human arm impedance can be estimated without a biological model or a robot's model. Experimental results have demonstrated the feasibility and effectiveness of the proposed approach.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 1","pages":"205-218"},"PeriodicalIF":5.0,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Transactions on Cognitive and Developmental Systems Information for Authors 电气和电子工程师学会《认知与发展系统》期刊为作者提供的信息

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-08-12 DOI: 10.1109/TCDS.2024.3436255

引用次数: 0