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• Cognitive and motor compliance in intentional human-robot interaction
  Embodiment and subjective experience in human-robot interaction are important aspects to consider when studying both natural cognition and adaptive robotics to human environments. Although several researches have focused on nonverbal communication and collabor…
  datacite Chame, Hendry Ferreira, Tani, Jun 2019 置信度 0.66 Robotics (cs.RO)Human-Computer Interaction (cs.HC)Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• Event-based Robotic Grasping Detection with Neuromorphic Vision Sensor and Event-Stream Dataset
  Robotic grasping plays an important role in the field of robotics. The current state-of-the-art robotic grasping detection systems are usually built on the conventional vision, such as RGB-D camera. Compared to traditional frame-based computer vision, neuromor…
  datacite Li, Bin, Cao, Hu, Qu, Zhongnan, Hu, Yingbai 等 2020 置信度 0.66 Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciencesFOS: Computer and information sciences
• Embodied Synaptic Plasticity with Online Reinforcement learning
  The endeavor to understand the brain involves multiple collaborating research fields. Classically, synaptic plasticity rules derived by theoretical neuroscientists are evaluated in isolation on pattern classification tasks. This contrasts with the biological b…
  datacite Kaiser, Jacques, Hoff, Michael, Konle, Andreas, Tieck, J. Camilo Vasquez 等 2020 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Artificial Intelligence (cs.AI)Machine Learning (cs.LG)Robotics (cs.RO)FOS: Computer and information sciences
• Nengo and low-power AI hardware for robust, embedded neurorobotics
  In this paper we demonstrate how the Nengo neural modeling and simulation libraries enable users to quickly develop robotic perception and action neural networks for simulation on neuromorphic hardware using familiar tools, such as Keras and Python. We identif…
  datacite DeWolf, Travis, Jaworski, Pawel, Eliasmith, Chris 2020 置信度 0.66 Robotics (cs.RO)Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• Integrating Intrinsic and Extrinsic Explainability: The Relevance of Understanding Neural Networks for Human-Robot Interaction
  Explainable artificial intelligence (XAI) can help foster trust in and\nacceptance of intelligent and autonomous systems. Moreover, understanding the\nmotivation for an agent's behavior results in better and more successful\ncollaborations between robots and h…
  openalex Weber, Tom, Wermter, Stefan, Tom Weber, Stefan Wermter 2020 置信度 0.72 Robotics (cs.RO)Artificial Intelligence (cs.AI)FOS: Computer and information sciencesRelevance (law)Robot
• A Predictive Coding Account for Chaotic Itinerancy
  As a phenomenon in dynamical systems allowing autonomous switching between stable behaviors, chaotic itinerancy has gained interest in neurorobotics research. In this study, we draw a connection between this phenomenon and the predictive coding theory by showi…
  datacite Annabi, Louis, Pitti, Alexandre, Quoy, Mathias 2021 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Machine Learning (cs.LG)Chaotic Dynamics (nlin.CD)FOS: Computer and information sciencesFOS: Computer and information sciences
• The Importance of Models in Data Analysis with Small Human Movement Datasets -- Inspirations from Neurorobotics Applied to Posture Control of Humanoids and Humans
  This work presents a system identification procedure based on Convolutional Neural Networks (CNN) for human posture control using the DEC (Disturbance Estimation and Compensation) parametric model. The modular structure of the proposed control model inspired t…
  datacite Lippi, Vittorio, Maurer, Christoph, Mergner, Thomas 2021 置信度 0.66 Robotics (cs.RO)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• SpikePropamine: Meta-Learning Synaptic Plasticity for Spiking Neural Networks
  This presentation is an overview of the recently developed SpikePropamine meta-learning framework submitted for publication in the Frontiers In Neurorobotics journal. Material from the original paper as well as more recent developments will be presented. Our g…
  datacite The Fifth Annual Workshop on Naval Applications of Machine Learning 2021, Ashkanazy, Julia, Hays, Joe, Lawson, Ed 等 2021 置信度 0.66 Military ScienceMachine LearningNeural Network
• ExoNet Database: Wearable Camera Images of Human Locomotion Environments
  Abstract: Recent advances in computer vision and deep learning have allowed researchers to develop environment recognition systems for robotic leg prostheses and exoskeletons. However, small-scale and private training datasets have impeded the widespread …
  datacite Laschowski, Brokoslaw, McNally, William, Wong, Alexander, McPhee, John 2022 置信度 0.66
• Motion representation with spiking neural networks for grasping and manipulation
  Die Natur bedient sich Millionen von Jahren der Evolution, um adaptive physikalische Systeme mit effizienten Steuerungsstrategien zu erzeugen. Im Gegensatz zur konventionellen Robotik plant der Mensch nicht einfach eine Bewegung und führt sie aus, sondern es g…
  datacite Tieck, Juan Camilo Vásquez 2021 置信度 0.66 motor controlgraspingmanipulationspiking neural networksneurorobotics
• Benchmarking Highly Parallel Hardware for Spiking Neural Networks in Robotics
  Animal brains still outperform even the most performant machines with significantly lower speed. Nonetheless, impressive progress has been made in robotics in the areas of vision, motion- and path planning in the last decades. Brain-inspired Spiking Neural Net…
  datacite Steffen, Lea, Koch, Robin, , Stefan, , Sven 等 2021 置信度 0.66 spiking neural networksparallel hardware architecturesbenchmarkrobotic motion controlneurorobotics
• Benchmarking Highly Parallel Hardware for Spiking Neural Networks in Robotics
  Animal brains still outperform even the most performant machines with significantly lower speed. Nonetheless, impressive progress has been made in robotics in the areas of vision, motion- and path planning in the last decades. Brain-inspired Spiking Neural Net…
  datacite Steffen, Lea, Koch, Robin, , Stefan, , Sven 等 2021 置信度 0.66 spiking neural networksparallel hardware architecturesbenchmarkrobotic motion controlneurorobotics
• Multimodal Predictive Coding Network with WhiskEye and the NRP
  Datasets gathered from the NeuroRobotics Platform (NRP) for use with the MultiPredNet Predictive Coding algorithm. The data is used to create useful representations of the local environment. These representations have their usefulness quantified via Representa…
  datacite Pearson, M., Knowles, T. 2020 置信度 0.66 Neuroscience
• ROS-Neuro: A common middleware for neurorobotics
  Recent years have seen a growing interest for the neurorobotics field, a new interdisciplinary research topic that aims at studying neuro-inspired approaches in robotics and at developing innovative human–machine interfaces. However, in most cases, evidence of…
  datacite Tonin, Luca, Beraldo, Gloria, Tortora, Stefano, Menegatti, Emanuele 2020 置信度 0.66 ROS-Neuroneuroroboticsbrain-machine interface
• ROS-Neuro: A common middleware for neurorobotics
  Recent years have seen a growing interest for the neurorobotics field, a new interdisciplinary research topic that aims at studying neuro-inspired approaches in robotics and at developing innovative human–machine interfaces. However, in most cases, evidence of…
  datacite Tonin, Luca, Beraldo, Gloria, Tortora, Stefano, Menegatti, Emanuele 2020 置信度 0.66 ROS-Neuroneuroroboticsbrain-machine interface
• Experiences in Neurorobotics for intelligent assistive robots
  The last few years have seen the birth of a new interdisciplinary research field: the neurorobotics. The main objective of neurorobotics is the development of techniques and technologies to provide robotic devices, such as robots, prosthesis or exoskeletons, w…
  datacite Tortora, Stefano, Beraldo, Gloria, Tonin, Luca, Michieletto, Stefano 等 2019 置信度 0.66 Keywords—Neuroroboticsintelligent assistive robotsbrain- computer interface
• Experiences in Neurorobotics for intelligent assistive robots
  The last few years have seen the birth of a new interdisciplinary research field: the neurorobotics. The main objective of neurorobotics is the development of techniques and technologies to provide robotic devices, such as robots, prosthesis or exoskeletons, w…
  datacite Tortora, Stefano, Beraldo, Gloria, Tonin, Luca, Michieletto, Stefano 等 2019 置信度 0.66 Keywords—Neuroroboticsintelligent assistive robotsbrain- computer interface
• Spatial navigation via deep reinforcement learning in the Neurorobotics Platform
  This paper presents a spatial navigation task on a mobile robot by employing a deep reinforcement learning algorithm (DQN) in the Neurorobotics Platform (NRP). The navigation task carried out with a Husky robot equipped with camera and laser sensors. The robot…
  datacite Priorelli, Matteo, Kirtay, Murat, Albanese, Ugo, Vannucci, Lorenzo 等 2019 置信度 0.66 deep reinforcement learningsimulationneuroroboticsspatial navigation
• Spatial navigation via deep reinforcement learning in the Neurorobotics Platform
  This paper presents a spatial navigation task on a mobile robot by employing a deep reinforcement learning algorithm (DQN) in the Neurorobotics Platform (NRP). The navigation task carried out with a Husky robot equipped with camera and laser sensors. The robot…
  datacite Priorelli, Matteo, Kirtay, Murat, Albanese, Ugo, Vannucci, Lorenzo 等 2019 置信度 0.66 deep reinforcement learningsimulationneuroroboticsspatial navigation
• The Neurorobotics Platform: virtual bodies for biologically realistic brain models and vice versa
  The Neurorobotics Platform is a simulation software aimed at facilitating mutual interactions between robotics and neuroscientific studies. This tool allows roboticists and neuroscientists to fill the gap between the two disciplines by easing the job of connec…
  datacite Vannucci, Lorenzo, Albanese, Ugo, Kirtay, Murat, Massi, Elisa 等 2019 置信度 0.66 neuroroboticssimulationspiking neural networks
• The Neurorobotics Platform: virtual bodies for biologically realistic brain models and vice versa
  The Neurorobotics Platform is a simulation software aimed at facilitating mutual interactions between robotics and neuroscientific studies. This tool allows roboticists and neuroscientists to fill the gap between the two disciplines by easing the job of connec…
  datacite Vannucci, Lorenzo, Albanese, Ugo, Kirtay, Murat, Massi, Elisa 等 2019 置信度 0.66 neuroroboticssimulationspiking neural networks
• Investigation of cerebro-cerebellar reward-based mechanisms on a virtual neurorobot
  Combining computational neuroscience tools with robotic devices allows to reproduce and investigate the interactions between embodied functional brain models and sensoryrich environments, integrating neural activity and behavioral data. As these models seldom …
  datacite Sheiban, Francesco Jamal, Trapani, Alessandra, Geminiani, Alice, D'Angelo, Egidio 等 2020 置信度 0.66 Neuroroboticsreward-based learningcomputational neuroscience
• Investigation of cerebro-cerebellar reward-based mechanisms on a virtual neurorobot
  Combining computational neuroscience tools with robotic devices allows to reproduce and investigate the interactions between embodied functional brain models and sensoryrich environments, integrating neural activity and behavioral data. As these models seldom …
  datacite Sheiban, Francesco Jamal, Trapani, Alessandra, Geminiani, Alice, D'Angelo, Egidio 等 2020 置信度 0.66 Neuroroboticsreward-based learningcomputational neuroscience
• Towards an Embodied Understanding of Neural Computation
  Information processing systems (IPSs) that behave in the real-world are constantly bombarded with noise from the environment. Although the real-world offers noise for free, this extrinsic noise source has a cost associated to it. The problem is related to the …
  datacite Berberian, Nareg 2021 置信度 0.66 NeuroroboticsSpiking neural networksShort-term plasticityLong-term plasticityLearning and memory
• HHI_raw_data.zip
  This repo contains all of the data used for: Trends in Haptic Communication of Human-Human Dyads: Towards Natural Human-Robot Co-manipulationAuthors: Spencer W. Jensen, John Salmon, and Marc D. KillpackPublished in Frontiers in Neurorobotics Contents:- Sensor_…
  datacite Jensen, Spencer, Killpack, Marc 2021 置信度 0.66 90602 Control Systems, Robotics and AutomationFOS: Electrical engineering, electronic engineering, information engineeringFOS: Electrical engineering, electronic engineering, information engineering80101 Adaptive Agents and Intelligent RoboticsFOS: Computer and information sciences
• HHI_raw_data.zip
  This repo contains all of the data used for: Trends in Haptic Communication of Human-Human Dyads: Towards Natural Human-Robot Co-manipulationAuthors: Spencer W. Jensen, John Salmon, and Marc D. KillpackPublished in Frontiers in Neurorobotics Contents:- Sensor_…
  datacite Jensen, Spencer, Killpack, Marc 2021 置信度 0.66 90602 Control Systems, Robotics and AutomationFOS: Electrical engineering, electronic engineering, information engineeringFOS: Electrical engineering, electronic engineering, information engineering80101 Adaptive Agents and Intelligent RoboticsFOS: Computer and information sciences
• Multisensory posture control in hip and ankle joints
  Human control of upright stance is highly complex, involving the integration of several sensory systems and the stabilization of several body segments. An experimental simplification is to apply moderate external disturbances and to model the human biomechanic…
  datacite Hettich, Georg 2015 置信度 0.66 796
• 02: Kognitive Systeme, Vorlesung, SS 2018, 25.04.2018
  02 | 0:00:00 Start 0:00:05 Kognitive Systeme 0:00:58 TechTalk der Fakultät für Informatik 0:03:13 Wiederholung 0:07:33 Elements for Cognition in Neurorobotics 0:10:37 Reference Model Cognition 0:13:17 Consideration of Cognition 0:15:45 Elemente eines Kognitive…
  datacite Prof. Dr.-Ing. Rüdiger Dillmann 2018 置信度 0.66
• 01: Kognitive Systeme, Vorlesung, SS 2018, 23.04.2018
  01 | 0:00:00 Start 0:03:34 Vorlesungskoordination 0:04:18 Organisatorisches 0:06:32 Opportunities 0:08:53 The Human Brain Project 0:10:31 Al, 1956: the birth of a new discipline 0:11:35 with an Inflated Promise 0:12:03 and Doubtful Prophets 0:13:24 Where are w…
  datacite Prof. Dr.-Ing. Rüdiger Dillmann 2018 置信度 0.66
• Neuron-Based Control Mechanisms For A Robotic Arm And Hand
  A robotic arm and hand controlled by simulated neurons is presented. The robot makes use of a biological neuron simulator using a point neural model. The neurons and synapses are organised to create a finite state automaton including neural inputs from sensors…
  datacite Nishant Singh, Huyck, Christian, Vaibhav Gandhi, Jones, Alexander 2017 置信度 0.66 Robotneuroncell assemblyspiking neuronforce sensitive resistor.
• Neuron-Based Control Mechanisms For A Robotic Arm And Hand
  A robotic arm and hand controlled by simulated neurons is presented. The robot makes use of a biological neuron simulator using a point neural model. The neurons and synapses are organised to create a finite state automaton including neural inputs from sensors…
  datacite Nishant Singh, Huyck, Christian, Vaibhav Gandhi, Jones, Alexander 2017 置信度 0.66 Robotneuroncell assemblyspiking neuronforce sensitive resistor.
• The Neurorobotics Platform: A simulation environment for brain-inspired robotics
  datacite Akl, Mahmoud, Neurorobotics Team, HBP 2017 置信度 0.66 Computational NeuroscienceOther
• 16: Kognitive Systeme, Vorlesung, SS 2017, 24.07.2017
  16 | 0:00:00 Starten 0:02:06 Überblick 0:02:12 Interaktion in der Merkmalsauswahl 0:06:59 Ausblick Aktivitätserkennung 0:07:53 Prinzip: Programmieren durch Demonstration 0:08:35 Sensoren zur Handlungsbeobachtung 0:09:56 Zyklus- Programmieren durch Vormachen 0:…
  datacite Prof. Dr. Rüdiger Dillmann 2017 置信度 0.66
• Supplementary Material for "Improving Robot Motor Learning with Negatively Valenced Reinforcement Signals"
  The Training and Testing sets were used to train, test the solutions of the genetic algorithm used for hyperparameter optimisation. The Validation set was used to run 10 random initializations for the best 4 hyperparameter sets. Results for the 10 random initi…
  datacite Navarro-Guerrero, Nicolás, Lowe, Robert, Wermter, Stefan 2017 置信度 0.66 80101 Adaptive Agents and Intelligent RoboticsFOS: Computer and information sciencesFOS: Computer and information sciences
• Supplementary Material for "Improving Robot Motor Learning with Negatively Valenced Reinforcement Signals"
  The Training and Testing sets were used to train, test the solutions of the genetic algorithm used for hyperparameter optimisation. The Validation set was used to run 10 random initializations for the best 4 hyperparameter sets. Results for the 10 random initi…
  datacite Navarro-Guerrero, Nicolás, Lowe, Robert, Wermter, Stefan 2017 置信度 0.66 80101 Adaptive Agents and Intelligent RoboticsFOS: Computer and information sciencesFOS: Computer and information sciences
• Supplementary Material for "The Effects on Adaptive Behaviour of Negatively Valenced Signals in Reinforcement Learning"
  zip files with raw data from the 10 random initializations of the 4 best hyperparameter sets per condition and per activation function. Organized by function and per condition. pdf file containing the pair-wise comparison of the three tested conditions against…
  datacite Navarro-Guerrero, Nicolás, Lowe, Robert, Wermter, Stefan 2018 置信度 0.66 170203 Knowledge Representation and Machine LearningFOS: PsychologyFOS: Psychology
• Supplementary Material for "The Effects on Adaptive Behaviour of Negatively Valenced Signals in Reinforcement Learning"
  zip files with raw data from the 10 random initializations of the 4 best hyperparameter sets per condition and per activation function. Organized by function and per condition. pdf file containing the pair-wise comparison of the three tested conditions against…
  datacite Navarro-Guerrero, Nicolás, Lowe, Robert, Wermter, Stefan 2018 置信度 0.66 170203 Knowledge Representation and Machine LearningFOS: PsychologyFOS: Psychology
• A spiking network classifies human sEMG signals and triggers finger reflexes on a robotic hand
  The interaction between robots and humans is of great relevance for the field of neurorobotics as it can provide insights on how humans perform motor control and sensor processing and on how it can be applied to robotics. We propose a spiking neural network (S…
  datacite Tieck, J. C. V., Weber, S., Stewart, T. C., Kaiser, J. 等 2020 置信度 0.66 NeuroroboticsHuman–robot-interactionNeural control systemHumanoid robotMotion representation
• HBP Neurorobotics Platform
  Use the Neurorobotics Platform (NRP) developed in the HBP to connect spiking or tensorflow neural networks to virtual and real robots. This enables you to conduct embodiment experiments online or on your computer. We use Gazebo, OpenSim, ODE, SPlisHSPlasH as p…
  datacite Albanese, Ugo, Sharma, Kenny, Feldotto, Benedikt, Akl, Mahmoud 等 2020 置信度 0.66 neuroroboticsspiking neural networksartificial intelligenceroboticsneuroscience
• HBP Neurorobotics Platform
  Use the Neurorobotics Platform (NRP) developed in the HBP to connect spiking neural networks to virtual and real robots. This enables you to conduct embodiment experiments on our High Performance Computing (HPC) clusters. All this can be either done through an…
  datacite Albanese, Ugo, Sharma, Kenny, Feldotto, Benedikt, Akl, Mahmoud 等 2019 置信度 0.66 neuroroboticsspiking neural networksartificial intelligenceroboticsneuroscience
• A Framework for Coupled Simulations of Robots and Spiking Neuronal Networks
  Bio-inspired robots still rely on classic robot control although advances in neurophysiology allow adaptation to control as well. However, the connection of a robot to spiking neuronal networks needs adjustments for each purpose and requires frequent adaptatio…
  datacite Hinkel, Georg, Groenda, Henning, Krach, Sebastian, Vannucci, Lorenzo 等 2016 置信度 0.66 NeuroroboticsHuman brainSpiking neuronal networksDomain-specific languagesModel-driven engineering
• Cardioid oscillator-based pattern generator for imitating the time-ratio-asymmetrical behavior of the lower limb exoskeleton.
  Periodicity, self-excitation, and time ratio asymmetry are the fundamental characteristics of the human gait. In order to imitate these mentioned characteristics, a pattern generator with four degrees of freedom is proposed based on cardioid oscillators develo…
  pubmed Fu Q, Luo T, Cui T, Ma X 等 2024 置信度 0.82
• Closing the loop: High-speed robotics with accelerated neuromorphic hardware.
  The BrainScaleS-2 system is an established analog neuromorphic platform with versatile applications in the diverse fields of computational neuroscience and spike-based machine learning. In this work, we extend the system with a configurable realtime event inte…
  pubmed Stradmann Y, Schemmel J 2024 置信度 0.82
• Resolving uncertainty on the fly: modeling adaptive driving behavior as active inference.
  Understanding adaptive human driving behavior, in particular how drivers manage uncertainty, is of key importance for developing simulated human driver models that can be used in the evaluation and development of autonomous vehicles. However, existing traffic …
  pubmed Engström J, Wei R, McDonald AD, Garcia A 等 2024 置信度 0.82
• A data-driven acceleration-level scheme for image-based visual servoing of manipulators with unknown structure.
  The research on acceleration-level visual servoing of manipulators is crucial yet insufficient, which restricts the potential application range of visual servoing. To address this issue, this paper proposes a quadratic programming-based acceleration-level imag…
  pubmed Wen L, Xie Z, Liuyi Wen, Zhengtai Xie 2024 置信度 0.82
• Human skill knowledge guided global trajectory policy reinforcement learning method.
  Traditional trajectory learning methods based on Imitation Learning (IL) only learn the existing trajectory knowledge from human demonstration. In this way, it can not adapt the trajectory knowledge to the task environment by interacting with the environment a…
  pubmed Zang Y, Wang P, Zha F, Guo W 等 2024 置信度 0.82
• HiDeS: a higher-order-derivative-supervised neural ordinary differential equation for multi-robot systems and opinion dynamics.
  This paper addresses the limitations of current neural ordinary differential equations (NODEs) in modeling and predicting complex dynamics by introducing a novel framework called higher-order-derivative-supervised (HiDeS) NODE. This method extends traditional …
  pubmed Li M, Bian W, Chen L, Liu M 2024 置信度 0.82
• Multimodal audio-visual robot fusing 3D CNN and CRNN for player behavior recognition and prediction in basketball matches.
  Introduction Intelligent robots play a crucial role in enhancing efficiency, reducing costs, and improving safety in the logistics industry. However, traditional path planning methods often struggle to adapt to dynamic environments, leading to issues such as c…
  pubmed Wang H, Haiyan Wang 2024 置信度 0.82
• Assessment and analysis of accents in air traffic control speech: a fusion of deep learning and information theory.
  Enhancing the generalization and reliability of speech recognition models in the field of air traffic control (ATC) is a challenging task. This is due to the limited storage, difficulty in acquisition, and high labeling costs of ATC speech data, which may resu…
  pubmed Pan W, Zhang J, Zhang Y, Jiang P 等 2024 置信度 0.82
• SR-TTS: a rhyme-based end-to-end speech synthesis system.
  Deep learning has significantly advanced text-to-speech (TTS) systems. These neural network-based systems have enhanced speech synthesis quality and are increasingly vital in applications like human-computer interaction. However, conventional TTS models still …
  pubmed Yao Y, Liang T, Feng R, Shi K 等 2024 置信度 0.82
• Motion planning framework based on dual-agent DDPG method for dual-arm robots guided by human joint angle constraints.
  Reinforcement learning has been widely used in robot motion planning. However, for multi-step complex tasks of dual-arm robots, the trajectory planning method based on reinforcement learning still has some problems, such as ample exploration space, long traini…
  pubmed Liang K, Zha F, Guo W, Liu S 等 2024 置信度 0.82
• Metastability indexes global changes in the dynamic working point of the brain following brain stimulation.
  Several studies have shown that coordination among neural ensembles is a key to understand human cognition. A well charted path is to identify coordination states associated with cognitive functions from spectral changes in the oscillations of EEG or MEG. A gr…
  pubmed Bapat R, Pathak A, Banerjee A 2024 置信度 0.82
• Keeping social distance in a classroom while interacting via a telepresence robot: a pilot study.
  The use of various telecommunication tools has grown significantly. However, many of these tools (e.g., computer-based teleconferencing) are problematic in relaying non-verbal human communication. Telepresence robots (TPRs) are seen as telecommunication tools …
  pubmed Marmor K, Leoste J, Heidmets M, Kangur K 等 2024 置信度 0.82
• Design and assessment of a reconfigurable behavioral assistive robot: a pilot study.
  For patients with functional motor disorders of the lower limbs due to brain damage or accidental injury, restoring the ability to stand and walk plays an important role in clinical rehabilitation. Lower limb exoskeleton robots generally require patients to co…
  pubmed Shi E, Zhi W, Chen W, Han Y 等 2024 置信度 0.82
• Human-robot planar co-manipulation of extended objects: data-driven models and control from human-human dyads.
  Human teams are able to easily perform collaborative manipulation tasks. However, simultaneously manipulating a large extended object for a robot and human is a difficult task due to the inherent ambiguity in the desired motion. Our approach in this paper is t…
  pubmed Mielke E, Townsend E, Wingate D, Salmon JL 等 2024 置信度 0.82
• ADAM: a robotic companion for enhanced quality of life in aging populations.
  One of the major problems of today's society is the rapid aging of its population. Life expectancy is increasing, but the quality of life is not. Faced with the growing number of people who require cognitive or physical assistance, new technological tools are …
  pubmed Mora A, Prados A, Mendez A, Espinoza G 等 2024 置信度 0.82
• Velocity-aware spatial-temporal attention LSTM model for inverse dynamic model learning of manipulators.
  Introduction An accurate inverse dynamics model of manipulators can be effectively learned using neural networks. However, further research is required to investigate the impact of spatiotemporal variations in manipulator motion sequences on network learning. …
  pubmed Huang W, Lin Y, Liu M, Min H 等 2024 置信度 0.82
• NeoSLAM: Long-Term SLAM Using Computational Models of the Brain.
  Simultaneous Localization and Mapping (SLAM) is a fundamental problem in the field of robotics, enabling autonomous robots to navigate and create maps of unknown environments. Nevertheless, the SLAM methods that use cameras face problems in maintaining accurat…
  pubmed Pizzino CAP, Costa RR, Mitchell D, Vargas PA 2024 Feb 9 置信度 0.82
• Identifying the characteristics of patients with stroke who have difficulty benefiting from gait training with the hybrid assistive limb: a retrospective cohort study.
  Robot-assisted gait training is effective for walking independence in stroke rehabilitation, the hybrid assistive limb (HAL) is an example. However, gait training with HAL may not be effective for everyone, and it is not clear who is not expected to benefit. T…
  pubmed Taki S, Imura T, Mitsutake T, Iwamoto Y 等 2024 置信度 0.82
• YOLOv8-ACU: improved YOLOv8-pose for facial acupoint detection.
  Acupoint localization is integral to Traditional Chinese Medicine (TCM) acupuncture diagnosis and treatment. Employing intelligent detection models for recognizing facial acupoints can substantially enhance localization accuracy.
  pubmed Yuan Z, Shao P, Li J, Wang Y 等 2024 置信度 0.82
• Enhancing hazardous material vehicle detection with advanced feature enhancement modules using HMV-YOLO.
  The transportation of hazardous chemicals on roadways has raised significant safety concerns. Incidents involving these substances often lead to severe and devastating consequences. Consequently, there is a pressing need for real-time detection systems tailore…
  pubmed Wang L, Liu B, Shao W, Li Z 等 2024 置信度 0.82
• Bidirectional feature pyramid attention-based temporal convolutional network model for motor imagery electroencephalogram classification.
  As an interactive method gaining popularity, brain-computer interfaces (BCIs) aim to facilitate communication between the brain and external devices. Among the various research topics in BCIs, the classification of motor imagery using electroencephalography (E…
  pubmed Xie X, Chen L, Qin S, Zha F 等 2024 置信度 0.82
• A study on robot force control based on the GMM/GMR algorithm fusing different compensation strategies.
  To address traditional impedance control methods' difficulty with obtaining stable forces during robot-skin contact, a force control based on the Gaussian mixture model/Gaussian mixture regression (GMM/GMR) algorithm fusing different compensation strategies is…
  pubmed Xiao M, Zhang X, Zhang T, Chen S 等 2024 置信度 0.82
• Research on multi-robot collaborative operation in logistics and warehousing using A3C optimized YOLOv5-PPO model.
  Introduction In the field of logistics warehousing robots, collaborative operation and coordinated control have always been challenging issues. Although deep learning and reinforcement learning methods have made some progress in solving these problems, however…
  pubmed Wang L, Liu G, Lei Wang, Guangjun Liu 2023 置信度 0.82
• Multi-UAV simultaneous target assignment and path planning based on deep reinforcement learning in dynamic multiple obstacles environments.
  Target assignment and path planning are crucial for the cooperativity of multiple unmanned aerial vehicles (UAV) systems. However, it is a challenge considering the dynamics of environments and the partial observability of UAVs. In this article, the problem of…
  pubmed Kong X, Zhou Y, Li Z, Wang S 2023 置信度 0.82
• Loop closure detection of visual SLAM based on variational autoencoder.
  Loop closure detection is an important module for simultaneous localization and mapping (SLAM). Correct detection of loops can reduce the cumulative drift in positioning. Because traditional detection methods rely on handicraft features, false positive detecti…
  pubmed Song S, Yu F, Jiang X, Zhu J 等 2023 置信度 0.82
• Context-aware SAR image ship detection and recognition network.
  With the development of deep learning, synthetic aperture radar (SAR) ship detection and recognition based on deep learning have gained widespread application and advancement. However, there are still challenging issues, manifesting in two primary facets: firs…
  pubmed Li C, Yue C, Li H, Wang Z 2024 置信度 0.82
• ID-YOLOv7: an efficient method for insulator defect detection in power distribution network.
  Insulators play a pivotal role in the reliability of power distribution networks, necessitating precise defect detection. However, compared with aerial insulator images of transmission network, insulator images of power distribution network contain more comple…
  pubmed Chen B, Zhang W, Wu W, Li Y 等 2023 置信度 0.82
• Integrated Quantitative Evaluation of Spatial Cognition and Motor Function with HoloLens Mixed Reality.
  The steady increase in the aging population worldwide is expected to cause a shortage of doctors and therapists for older people. This demographic shift requires more efficient and automated systems for rehabilitation and physical ability evaluations. Rehabili…
  pubmed Tada K, Sorimachi Y, Kutsuzawa K, Owaki D 等 2024 Jan 15 置信度 0.82
• Vehicle re-identification method based on multi-attribute dense linking network combined with distance control module.
  Vehicle re-identification is a crucial task in intelligent transportation systems, presenting enduring challenges. The primary challenge involves the inefficiency of vehicle re-identification, necessitating substantial time for recognition within extensive dat…
  pubmed Sun X, Chen Y, Duan Y, Wang Y 等 2023 置信度 0.82
• Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol.
  More than 10 million Europeans show signs of mild cognitive impairment (MCI), a transitional stage between normal brain aging and dementia stage memory disorder. The path MCI takes can be divergent; while some maintain stability or even revert to cognitive nor…
  pubmed Haraldsen IH, Hatlestad-Hall C, Marra C, Renvall H 等 2023 置信度 0.82 DementiaCognitionCognitive declineElectroencephalographyComputer science
• Education robot object detection with a brain-inspired approach integrating Faster R-CNN, YOLOv3, and semi-supervised learning.
  The development of education robots has brought tremendous potential and opportunities to the field of education. These intelligent machines can interact with students in classrooms and learning environments, providing personalized educational support. To enab…
  pubmed Hong Q, Dong H, Deng W, Ping Y 2023 置信度 0.82
• A review of rigid point cloud registration based on deep learning.
  With the development of 3D scanning devices, point cloud registration is gradually being applied in various fields. Traditional point cloud registration methods face challenges in noise, low overlap, uneven density, and large data scale, which limits the furth…
  pubmed Chen L, Feng C, Ma Y, Zhao Y 等 2023 置信度 0.82
• EEG-controlled tele-grasping for undefined objects.
  This paper presents a teleoperation system of robot grasping for undefined objects based on a real-time EEG (Electroencephalography) measurement and shared autonomy. When grasping an undefined object in an unstructured environment, real-time human decision is …
  pubmed Kim M, Choi MS, Jang GR, Bae JH 等 2023 置信度 0.82
• Enhanced YOLOv7 integrated with small target enhancement for rapid detection of objects on water surfaces.
  Unmanned surface vessel (USV) target detection algorithms often face challenges such as misdetection and omission of small targets due to significant variations in target scales and susceptibility to interference from complex environments. To address these iss…
  pubmed Yu J, Zheng H, Xie L, Zhang L 等 2023 置信度 0.82
• Fusion of dual modalities of non-invasive sensory feedback for object profiling with prosthetic hands.
  Either non-invasive somatotopic or substitute sensory feedback is capable of conveying a single modality of sensory information from prosthetic hands to amputees. However, the neurocognitive ability of amputees to integrate multi-modality sensory information f…
  pubmed Zhang J, Chou CH, Hao M, Li Y 等 2023 置信度 0.82
• Recovery of Volitional Motor Control and Overground Walking in Participants With Chronic Clinically Motor Complete Spinal Cord Injury: Restoration of Rehabilitative Function With Epidural Spinal Stimulation (RESTORES) Trial-A Preliminary Study.
  Spinal cord injury (SCI) is damage to any part of the spinal cord resulting in paralysis, bowel and/or bladder incontinence, and loss of sensation and other bodily functions. Current treatments for chronic SCI are focused on managing symptoms and preventing fu…
  pubmed Wan KR, Ng ZYV, Wee SK, Fatimah M 等 2024 May 置信度 0.82
• Safe physical interaction with cobots: a multi-modal fusion approach for health monitoring.
  Health monitoring is a critical aspect of personalized healthcare, enabling early detection, and intervention for various medical conditions. The emergence of cloud-based robot-assisted systems has opened new possibilities for efficient and remote health monit…
  pubmed Guo B, Liu H, Niu L, Bo Guo 等 2023 置信度 0.82
• Neurophysiological mental fatigue assessment for developing user-centered Artificial Intelligence as a solution for autonomous driving.
  The human factor plays a key role in the automotive field since most accidents are due to drivers' unsafe and risky behaviors. The industry is now pursuing two main solutions to deal with this concern: in the short term, there is the development of systems mon…
  pubmed Giorgi A, Ronca V, Vozzi A, Aricò P 等 2023 置信度 0.82
• Social robots as effective language tutors for children: empirical evidence from neuroscience.
  The aim of the current study was to investigate children's brain responses to robot-assisted language learning. EEG brain signals were collected from 41 Japanese children who learned French vocabularies in two groups; half of the children learned new words fro…
  pubmed Alimardani M, Duret J, Jouen AL, Hiraki K 等 2023 置信度 0.82
• Research on system of ultra-flat carrying robot based on improved PSO algorithm.
  Ultra-flat carrying robots (UCR) are used to carry soft targets for functional safety road tests of intelligent driving vehicles and should have superior control performance. For the sake of analyzing and upgrading the motion control performance of the ultra-f…
  pubmed Zhu J, Wu J, Chen Z, Cao L 等 2023 置信度 0.82
• A visual questioning answering approach to enhance robot localization in indoor environments.
  Navigating robots with precision in complex environments remains a significant challenge. In this article, we present an innovative approach to enhance robot localization in dynamic and intricate spaces like homes and offices. We leverage Visual Question Answe…
  pubmed Peña-Narvaez JD, Martín F, Guerrero JM, Pérez-Rodríguez R 2023 置信度 0.82
• Prioritized experience replay in path planning via multi-dimensional transition priority fusion.
  Introduction Deep deterministic policy gradient (DDPG)-based path planning algorithms for intelligent robots struggle to discern the value of experience transitions during training due to their reliance on a random experience replay. This can lead to inappropr…
  pubmed Cheng N, Wang P, Zhang G, Ni C 等 2023 置信度 0.82
• Dense captioning and multidimensional evaluations for indoor robotic scenes.
  The field of human-computer interaction is expanding, especially within the domain of intelligent technologies. Scene understanding, which entails the generation of advanced semantic descriptions from scene content, is crucial for effective interaction. Despit…
  pubmed Wang H, Wang W, Li W, Liu H 2023 置信度 0.82
• A survey of path planning of industrial robots based on rapidly exploring random trees.
  Path planning is an essential part of robot intelligence. In this paper, we summarize the characteristics of path planning of industrial robots. And owing to the probabilistic completeness, we review the rapidly-exploring random tree (RRT) algorithm which is w…
  pubmed Luo S, Zhang M, Zhuang Y, Ma C 等 2023 置信度 0.82
• Fuzzy super twisting mode control of a rigid-flexible robotic arm based on approximate inertial manifold dimensionality reduction.
  Introduction The control of infinite-dimensional rigid-flexible robotic arms presents significant challenges, with direct truncation of first-order modal models resulting in poor control quality and second-order models leading to complex hardware implementatio…
  pubmed Qian X, Xu L, Yuan X, Xiaoshan Qian 等 2023 置信度 0.82
• Peg-in-hole assembly skill imitation learning method based on ProMPs under task geometric representation.
  Behavioral Cloning (BC) is a common imitation learning method which utilizes neural networks to approximate the demonstration action samples for task manipulation skill learning. However, in the real world, the demonstration trajectories from human are often s…
  pubmed Zang Y, Wang P, Zha F, Guo W 等 2023 置信度 0.82
• Feature fusion network based on few-shot fine-grained classification.
  The objective of few-shot fine-grained learning is to identify subclasses within a primary class using a limited number of labeled samples. However, many current methodologies rely on the metric of singular feature, which is either global or local. In fine-gra…
  pubmed Yang Y, Feng Y, Zhu L, Fu H 等 2023 置信度 0.82
• Learning geometric Jensen-Shannon divergence for tiny object detection in remote sensing images.
  Tiny objects in remote sensing images only have a few pixels, and the detection difficulty is much higher than that of regular objects. General object detectors lack effective extraction of tiny object features, and are sensitive to the Intersection-over-Union…
  pubmed Ni S, Lin C, Wang H, Li Y 等 2023 置信度 0.82
• Leg-body coordination strategies for obstacle avoidance and narrow space navigation of multi-segmented, legged robots.
  Millipedes can avoid obstacle while navigating complex environments with their multi-segmented body. Biological evidence indicates that when the millipede navigates around an obstacle, it first bends the anterior segments of its corresponding anterior segment …
  pubmed Mingchinda N, Jaiton V, Leung B, Manoonpong P 2023 置信度 0.82
• A human-centered safe robot reinforcement learning framework with interactive behaviors.
  Deployment of Reinforcement Learning (RL) algorithms for robotics applications in the real world requires ensuring the safety of the robot and its environment. Safe Robot RL (SRRL) is a crucial step toward achieving human-robot coexistence. In this paper, we e…
  pubmed Gu S, Kshirsagar A, Du Y, Chen G 等 2023 置信度 0.82
• Exploring the EMG transient: the muscular activation sequences used as novel time-domain features for hand gestures classification.
  Muscular activation sequences have been shown to be suitable time-domain features for classification of motion gestures. However, their clinical application in myoelectric prosthesis control was never investigated so far. The aim of the paper is to evaluate th…
  pubmed Mereu F, Morosato F, Cordella F, Zollo L 等 2023 置信度 0.82
• Incremental Learning of Goal-Directed Actions in a Dynamic Environment by a Robot Using Active Inference.
  This study investigated how a physical robot can adapt goal-directed actions in dynamically changing environments, in real-time, using an active inference-based approach with incremental learning from human tutoring examples. Using our active inference-based m…
  pubmed Matsumoto T, Ohata W, Tani J 2023 Oct 31 置信度 0.82
• Sports competition tactical analysis model of cross-modal transfer learning intelligent robot based on Swin Transformer and CLIP.
  Introduction This paper presents an innovative Intelligent Robot Sports Competition Tactical Analysis Model that leverages multimodal perception to tackle the pressing challenge of analyzing opponent tactics in sports competitions. The current landscape of spo…
  pubmed Jiang L, Lu W, Li Jiang, Wang Lu 2023 置信度 0.82
• Bridging Neuroscience and Robotics: Spiking Neural Networks in Action.
  Robots are becoming increasingly sophisticated in the execution of complex tasks. However, an area that requires development is the ability to act in dynamically changing environments. To advance this, developments have turned towards understanding the human b…
  pubmed Jones A, Gandhi V, Mahiddine AY, Huyck C 等 2023 Nov 1 置信度 0.82 Spiking neural networkRoboticsArtificial intelligenceRobotComputer science
• An autonomous mobile robot path planning strategy using an enhanced slime mold algorithm.
  Introduction Autonomous mobile robot encompasses modules such as perception, path planning, decision-making, and control. Among these modules, path planning serves as a prerequisite for mobile robots to accomplish tasks. Enhancing path planning capability of m…
  pubmed Zheng L, Hong C, Song H, Chen R 等 2023 置信度 0.82
• Research on deep reinforcement learning basketball robot shooting skills improvement based on end to end architecture and multi-modal perception.
  In the realm of basketball, refining shooting skills and decision-making levels using intelligent agents has garnered significant interest. This study addresses the challenge by introducing an innovative framework that combines multi-modal perception and deep …
  pubmed Zhang J, Tao D 2023 置信度 0.82
• Simulating human walking: a model-based reinforcement learning approach with musculoskeletal modeling.
  Recent advancements in reinforcement learning algorithms have accelerated the development of control models with high-dimensional inputs and outputs that can reproduce human movement. However, the produced motion tends to be less human-like if algorithms do no…
  pubmed Su B, Gutierrez-Farewik EM 2023 置信度 0.82
• Research on automatic pilot repetition generation method based on deep reinforcement learning.
  Using computers to replace pilot seats in air traffic control (ATC) simulators is an effective way to improve controller training efficiency and reduce training costs. To achieve this, we propose a deep reinforcement learning model, RoBERTa-RL (RoBERTa with Re…
  pubmed Pan W, Jiang P, Li Y, Wang Z 等 2023 置信度 0.82
• Remote sensing traffic scene retrieval based on learning control algorithm for robot multimodal sensing information fusion and human-machine interaction and collaboration.
  In light of advancing socio-economic development and urban infrastructure, urban traffic congestion and accidents have become pressing issues. High-resolution remote sensing images are crucial for supporting urban geographic information systems (GIS), road pla…
  pubmed Peng H, Shi N, Wang G 2023 置信度 0.82