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SkyvoltRobot: A Novel Rail-Mounted Charging Robot for Electric Vehicles

Procedia Computer Science 2024年 250卷 274-281页

作者： Anjun Hu Shu Ban Yue Hong Ziqi Zhao Fucheng Zhao Jiankun Wang Max Q.-H. Meng Shenzhen Key Laboratory of Robotics Perception and Intelligence Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Jiaxing Research Institute Southern University of Science and Technology Jiaxing China

SkyvoltRobot represents an innovative solution for electric vehicle (EV) charging services. This system achieves higher efficiency and broader coverage by transporting charging units with robots suspended on overhead tracks. The solution relies on the robots’ ability to grasp and transport charging units, utilizing a specially designed two-stage telescopic mechanism to complete the task accurately. Compared to existing fixed-point charging solutions, this system covers a much larger area with the same number of charging units. It significantly reduces economic costs for the same coverage area. A single robot can manage multiple charging units’ transportation, allowing for future multi-area track transfers. Notably, we have innovatively designed a SkyVoltRobot and experimentally demonstrated the effectiveness of this solution.

关键词： Rail-Mounted Robot Charging service Electric vehicle

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A Novel Surface Electromyography Signals Denoising Method for Gait Phase Classification 42

A Novel Surface Electromyography Signals Denoising Method fo...

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42nd Chinese Control Conference, CCC 2023

作者： Sun, Yubo Guo, Zhenhui Feng, Yuxin Yu, Ningbo College of Artificial Intelligence Nankai University Tianjin300350 China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin300350 China Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute Nankai University Shenzhen518083 China

ISBN: (纸本)9789887581543

Surface electromyography (sEMG) is a non-invasive technique for recording electrical activity and is extensively employed in gait phase classification. However, the measurement process of the sEMG signal inevitably introduces noise. Consequently, denoising is required for gait analysis from the collected sEMG signal. A novel denoising method ICEEMDAN-DFA-WD has been proposed in this paper. The sEMG signals were decomposed into several intrinsic mode functions (IMF) through an improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN). The Hurst exponents were simulated by detrended fluctuation analysis (DFA) to distinguish noisy IMF and desired IMF. During the walking process, the lower limbs' sEMG exhibits strong periodicity, and the desired IMF yields higher Hurst exponents than the noisy IMF. For the noisy IMF, noise removal was performed through further decomposition by wavelet transform, followed by a hard threshold. The processed IMFs were reconstructed to denoise sEMG. In this study, experiments were conducted to compare with the existing denoising methods WD, EMD-IIT, EEMD-IWT, VMD-SIT. The proposed method can obtain better denoising effect and gait phase classification accuracy. The proposed method provides a more effective way for sEMG denoising. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Empirical mode decomposition

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Functional Connectivity Analysis Revealed Abnormal Brain Network Pattern in Parkinson's Disease with Freezing of Gait 42

Functional Connectivity Analysis Revealed Abnormal Brain Net...

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42nd Chinese Control Conference, CCC 2023

作者： Shu, Zhilin Liu, Jinrui Song, Ting Han, Jianda Yu, Ningbo College of Artificial Intelligence Nankai University Tianjin300350 China Nankai University Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Tianjin300350 China Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

ISBN: (纸本)9789887581543

Patients with Parkinson's disease (PD) commonly have deficits in lower-limb movements. Freezing of gait (FOG), a type of gait disturbance of PD, is a complex motor symptom exhibited as inability to generate an effective gait. The mechanism of lower-limb dysfunction of PD, especially FOG, remains to be explored. To investigate the neural mechanisms related to FOG in PD, we evaluated 39 subjects (13 PD patients with FOG, 13 PD patients without FOG, and 13 healthy subjects) based on electroencephalogram (EEG) signals while they performed the pedaling task. We conducted functional connectivity analysis using Magnitude Squared Coherence (MSC) and calculated the metrics to investigate the characteristics of the brain network among the three groups. The results indicated that PD patients were associated with reduced functional integration and segregation of brain network, subserving both motor and cognitive abilities. The reduced functional integration and segregation of cognitive processes were correlated with the severity of FOG. This study revealed the differences in brain networks between PD patients and healthy controls and provided insights into the neural mechanism of FOG. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Electroencephalography

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Augmented Reality-Based Digital-Physical Space Registration and Projection for Cognitive Enhancement and Assessment

Augmented Reality-Based Digital-Physical Space Registration ...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Wang, Hongpeng Fei, Yue Zhang, Qinghao Deng, Kun Liang, Jun Sun, Chuanyu Xu, Li Civil Aviation University of China The Key Laboratory of Civil Aviation Smart Airport Theory and System China College of Artificial Intelligence Nankai University Tianjin300071 China National University of Defense Technology Laboratory of Science and Technology on Integrated Logistics Support Changsha410073 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China China Nuclear Power Technology Research Institute Co. Ltd. Shenzhen518000 China

ISBN: (纸本)9781665481090

Driven by information technology, mod-ern warfare is more diverse and intelligent than traditional warfare, in which intelligent unmanned system plays an increasingly important role. To defend against distant threat of unmanned military arma-ments, it's essential to deploy radars, sonars, satellites, and other long-range detection equipment to build a multidimensional national defense monitoring system. Due to the unpredictable nature of battlefield, radar-based reconnaissance missions require operators to have extensive experience and maintain a high level of focus. However, prolonged radar operations may impose a heavy psychological burden on operators and even affect their mental functions. To address these challenges, this paper proposes a cognitive en-hancement and assessment system that projects virtual 3D battlefield scenarios onto the real world based on augmented reality and evaluates operators' mental state through eye-tracking technology. © 2024 IEEE.

关键词： Augmented reality

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Automated Adherent Cell Injection Method Based on Double-Micropipettes Operation 42

Automated Adherent Cell Injection Method Based on Double-Mic...

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42nd Chinese Control Conference, CCC 2023

作者： Chu, Zhaotong Cai, Linxuan Cui, MaoSheng Wang, Zuqi Zhang, Yidi Li, Minghui Zhao, Qili Sun, Mingzhu Zhao, Xin Liu, Yaowei Institute of Robotics and Automatic Information System Nankai University The Tianjin Key Laboratory of Intelligent Robotics Tianjin300071 China Tianjin Academy of Agriculture Science Tianjin300112 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

ISBN: (纸本)9789887581543

Microinjection of adherent cells is a technique of inserting glass pipette into adherent cells and injecting few exogenous substances into adherent cells, which is widely used in the field of cell biology. Researchers in this field usually inject adherent cells manually, however, the microinjection operation is complicated, which requires a lot of energy and takes a lot of time. The existing automated microinjection method only uses one injection micropipette to inject, compared with the manual injection method, the microinjection process is consistent not optimized, and the injection efficiency cannot be greatly improved. In this paper, an automated adherent cell injection method based on double-micropipettes operation is proposed. Firstly, the adherent cell injection process based on double-micropipettes operation is designed. Secondly, this paper solves the key technologies of automated injection of adherent cells based on double-micropipettes operation were introduced, including adherent cell detection, injection path planning and double-micropipettes operation. Finally, the experiment of adherent cell microinjection based on double-micropipettes operation, the operation of two micropipettes was carried out. The experimental results show that the success rate of injection can reach 60% and the injection speed of this method can reach 35 cells/minute, which is 75% higher than that of manual injection with single pipette (20 cells/minute) and 40% higher than that of automated adherent cell injection with single pipette (25 cells/minute). © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Motion planning

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Binaural sound source localization based on weighted template matching

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CAAI Transactions on intelligence Technology 2021年第2期6卷 214-223页

作者： Hong Liu Yongheng Sun Ge Yang Yang Chen Key Laboratory of Machine Perception Shenzhen Graduate SchoolPeking UniversityShenzhenChina College of Liangjiang Artificial Intelligence Chongqing University of TechnologyChongqingChina Yanka Kupala State University of Grodno GrodnoBelarus

In robot binaural sound source localization(SSL),locating the direction of the sound source accurately in the shortest time is *** refers to the algorithm complexity,but even more to the shortest duration of the required signal.A novel binaural SSL method based on feature and frequency weighting is *** specifically,in the training stage,the direction-related interaural cross-correlation function(CCF)and interaural intensity difference(IID)in each frequency band are calculated under noiseless conditions,which are considered the *** the testing stage,first the cosine similarities between the CCF and IID of the test signal and templates are calculated in all features and frequency ***,the direction likelihood can be obtained by weighting the ***,the direction with maximum likelihood is specified as the direction of the sound *** were carried out on CIPIC dataset subject 003 with different noises in the noisex-92 dataset and demonstrated that the method can accurately locate the sound source with a short signal duration.

关键词： template SSL robot

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EEG-based Objective Quality Assessment of Interrupted Speech

EEG-based Objective Quality Assessment of Interrupted Speech

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Shangdi Liao Zhixing Liu Fei Chen Department of Electrical and Electronic Engineering Shenzhen Key Laboratory of Robotics Perception and Intelligence Southern University of Science and Technology Shenzhen China

As an important dimension of speech degradation, interruption destroys the acoustic waveform information of a speech signal and seriously affects the quality rating in speech perception. Existing studies assessing the quality of interrupted speech mainly focus on subjective methods. This work used event-related potentials (ERPs) to objectively investigate the effects of two interruption factors (i.e., interruption duty cycle and interruption rate) on the perceived quality of the periodically interrupted speech. An oddball-paradigm based ERP experiment was designed, and the periodically interrupted stimuli were presented to participants in the ERP experiment. Meanwhile, participants were instructed to provide their subjective quality ratings of interrupted speech under the same interruption conditions. The experimental results showed that the degree of both interruption duty cycle and interruption rate affected the peak latency of mismatch negativity (MMN) of the collected ERP response, with a smaller MMN peak latency under conditions with a smaller interruption duty cycle or a larger interruption rate. These findings are largely consistent with the subjective quality rating results, suggesting that the peak latency of MMN response can be potentially used as an objective quality indicator of the periodically interrupted speech.

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Collaborative Inference for MEC Services Based on Multimodal Deep Neural Network

Collaborative Inference for MEC Services Based on Multimodal...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Liu, Yu Wang, Chuxuan Xiao, Yilin Lv, Zefang Xiao, Liang Ji, Xiangyang Xiamen University School of Informatics Xiamen China Xiamen University Dept. of Institute of Artificial Intelligence Xiamen China Xiamen University Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China Tsinghua University Department of Automation Beijing China

ISBN: (纸本)9798350345384

Collaborative inference can effectively ease the computational burden imposed on mobile devices by deep neural networks (DNNs), such as employing multimodal DNNs to achieve a comprehensive understanding of the environment. Although reinforcement learning (RL)-based collaborative inference adapts to dynamic environments and enhances inference performance for DNNs, especially those with chain-structured architectures, the policy selection for multimodal DNNs must account for multiple computation-intensive feature encoders. This paper proposes a hierarchical reinforcement learning (RL)-based collaborative inference scheme for multimodal DNNs that concurrently determines the partition point and identifies the appropriate DNN-based feature encoder for each modality within the mobile edge computing system. The hierarchical structure designed for policy selection has alleviated the exponential growth of the modalities. Moreover, the mobile device maintains a confidence score based on probabilities of predefined classes to assess the risk of inference policies that results in low inference accuracy and thus avoids exploring the risk policy. Simulation results demonstrate that our proposed scheme surpasses the Neurosurgeon benchmark in reducing inference latency and energy consumption, all while maintaining a high level of confidence score without significant degradation. © 2023 IEEE.

关键词： Deep neural networks

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Smart Mobility With Agent-Based Foundation Models: Towards Interactive and Collaborative Intelligent Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第7期9卷 5130-5133页

作者： Bingyi Xia Peijia Xie Jiankun Wang Shenzhen Key Laboratory of Robotics Perception and Intelligence Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Jiaxing Research Institute Southern University of Science and Technology Jiaxing China

This letter reports the insights gained during a Distributed/Decentralized Hybrid Workshop on Foundation/Infrastructure intelligence (FII), where we discussed the evolving role of Foundation Models in the field of intelligent vehicles. These models, pre-trained on multimodal data, have emerged as pivotal in the landscape of intelligent vehicles by leveraging their capabilities for high-level reasoning. Ongoing research focuses on these models to further improve scene perception and decision-making, aiming to develop adaptive systems for robot navigation and autonomous driving. However, for smart mobility across the Cyber-Physical-Social space, foundation intelligence should learn human-level knowledge to perform sophisticated interactions and collaborations based on human feedback. Agent-based Foundation Models, as the new training paradigm, can generate cross-domain actions consistent with perception information, paving the way to realize interactive and collaborative agents. This letter discusses the challenges of enhancing and leveraging the scene understanding and spatial reasoning capabilities of the pre-trained foundation model for smart mobility. It also offers insights into the embodied employment of foundation and infrastructure intelligence in enhancing multimodal interactions between robots, environments, and humans.

关键词： Collaboration Adaptation models Transportation Data models Cognition Autonomous vehicles Training

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Design and analysis of a soft bellow-based robot for dysphagia rehabilitation 30

Design and analysis of a soft bellow-based robot for dysphag...

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30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

作者： Guo, Linlin Dang, Yu Wang, Yue Wu, Jinqiao Yu, Yang Wu, Jialing Han, Jianda College of Artificial Intelligence Nankai University Tianjin300350 China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute Nankai University Shenzhen518083 China Department of Rehabilitation Medicine Tianjin Huanhu Hospital Tianjin300350 China Department of Neurology Tianjin Huanhu Hospital Tianjin300350 China

ISBN: (纸本)9798350391916

As the population ages, the incidence of diseases such as stroke is increasing, leading to a growing number of patients with dysphagia or difficulty swallowing. Dysphagia directly affects the hydration and nutritional intake, potentially leading to serious complications such as aspiration pneumonia, severely threatening patients' health and quality of life. Currently, the rehabilitation of swallowing function mainly relies on therapists to conduct swallowing training for patients. However, the high incidence and long duration of swallowing rehabilitation training pose a burden on the patients and medical resources. There remains a gap in the robotic devices for swallowing rehabilitation. To address this gap, this paper proposes a soft bellow-shaped robot for dysphagia rehabilitation. One mode of the rehabilitation training, where the therapist manipulates the throat to move horizontally, is selected to mimic. This robot simulates the force and displacement applied by the therapist's fingertip during dysphagia rehabilitation. First, swallowing training data were collected and analyzed to understand the variations in displacement and force applied by therapists' fingertips on the throat. Based on this analysis, the technical requirements for the swallowing rehabilitation robot were summarized. Following these requirements, we designed a physical prototype of the pneumatic bellow-shaped robot. The robot simulates the fingertip movement on both sides of the throat through the linear elongation and contraction of the bellows. The performance of the soft bellows was then characterized, verifying that its output force and displacement meet the technical requirements. This characterization lays a foundation for the modeling and control of the displacement and force of the robot. © 2024 IEEE.

关键词： Bellows

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