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检索条件"机构=College of IoT Engineering Changzhou Key Laboratory of Robotics and Intelligent Technology"

共 46 条记录，以下是11-20 订阅

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Analysis motion imagination EEG signal in spatiotemporal-energy domain 3

Analysis motion imagination EEG signal in spatiotemporal-ene...

引用

3rd International Conference on Computer Science and Artificial Intelligence, CSAI 2019 and its Workshop - The 11th International Conference on Information and Multimedia technology, ICIMT 2019

作者： Sheng, Zhengyan Yao, Xiao Chen, Ruixuan Diao, Wenyu Li, Weiliang Li, Yao College of IoT Engineering Hohai University China Changzhou Key Laboratory of Robotics and Intelligent Technology China

ISBN: (纸本)9781450376273

Brain is the most advanced part of the nervous system. As an emerging neighborhood exploring the brain, the brain-computer interface (BCI) may completely influence people's current communication and lifestyle in the future. We propose an architecture for feature extraction and classification model in brain-computer interface (BCI). Three features of EEG signal are extracted and combined in an attempt to describe the EEG signal more comprehensively including Wavelet packet decomposition, Information entropy and Co-space pattern (CSP). We construct the C-LSTM model combining the Convolutional Neural Networks (CNN) and the Long Short-Term Memory (LSTM) to perform the classification. Comparison was made with traditional approaches, and results show the method has a better performance for classification of motor imagery. © 2019 Association for Computing Machinery.

关键词： Brain computer interface

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Tactile-Based Object Pose Estimation Employing Extended Kalman Filter

Tactile-Based Object Pose Estimation Employing Extended Kalm...

引用

International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Qiguang Lin Chaojie Yan Qiang Li Yonggen Ling Yu Zheng Wangwei Lee Zhaoliang Wan Bidan Huang Xiaofeng Liu Jiangsu Key laboratory of Special Robotic Technology College of IoT Engineering Hohai University Changzhou Jiangsu P.R. China State Key Laboratory of Industrial Control and Technology Zhejiang University Institute of Cyber-System and Control Hangzhou P.R. China Neuroinformatics Group Center for Cognitive Interaction Technology (CITEC) Bielefeld University Bielefeld Germany Tencent Robotics X Shenzhen China School of Computer Science and Engineering Sun Yat-sen University Guangzhou P.R.China

In this paper, we present a new approach to estimate the pose of an object being manipulated by a multi-fingered robotic hand. The method utilizes advanced tactile sensors with high spatial resolution to optimize the estimation of the object's pose using an Extended Kalman Filter (EKF) based approach. We defined and derived the state and measurement equations, as well as evaluated the estimation accuracy in grasping tasks. The approach is able to effectively account for the pose transition caused by tactile pushing, and the mapping from the object's pose to the contact position and normal direction as measured by the tactile sensor. The method was evaluated in multiple grasping experiments in simulation scenarios. Results show that the estimation can converge towards the ground truth in a relatively short period of time, with displacement and rotation errors remaining within acceptable levels. This new method has the potential to improve the accuracy and reliability of robotic grasping and manipulation tasks.

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Validity of deriving low order photometry parameters from light solid distribution 19

Validity of deriving low order photometry parameters from li...

引用

2019 Conference on Research in Adaptive and Convergent Systems, RACS 2019

作者： Xia, Ling Zhang, Tingting Liu, Xiaofeng Changzhou Key Laboratory of Robotics and Intelligent Technology College of IoT Engineering Hohai University Jiangsu Key Laboratory of Special Robot Technology Changzhou China

ISBN: (纸本)9781450368438

The interaction between light and its surroundings (i.e. the geometry and materials) shapes the lighting distribution and determines the appearance of scenes and its visual experiences. In this study, we introduced the concept of light distribution solids by distinguishing luminance distribution solids and illuminance distribution solids. It is helpful to understand the spatial and form-giving lighting effects on objects' appearance. Furthermore, this study together with our previous study [1, 2] provide theoretical basis for the exploration of extracting photometry parameters out of HDR panoramic photographs of scenes. © 2019 Association for Computing Machinery.

关键词： Photometry

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Analysis Motion Imagination EEG Signal in Spatiotemporal-energy domain 2019

Analysis Motion Imagination EEG Signal in Spatiotemporal-ene...

引用

Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence

作者： Zhengyan Sheng Xiao Yao Ruixuan Chen Wenyu Diao Weiliang Li Yao Li The College of IoT Engineering Hohai University China The College of IoT Engineering Hohai University China Changzhou Key Laboratory of Robotics and Intelligent Technology China

ISBN: (纸本)9781450376273

关键词： EEG signal LSTM Brain-computer interface Co-space pattern

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Research on capsule network optimization structure by variable route planning

Research on capsule network optimization structure by variab...

引用

2019 IEEE International Conference on Real-Time Computing and robotics, RCAR 2019

作者： Chu, Xin Xu, Ning Liu, Xiaofeng Yao, Xiao College of IoT Engineering Hohai University Changzhou213022 China Changzhou Key Laboratory of Robotics and Intelligent Technology Changzhou213022 China Jiangsu Key Laboratory of Special Robots Changzhou213022 China

ISBN: (纸本)9781728137261

Convolutional Neural Networks (CNN) perform quite good on image classification and object recognition tasks. To solve the problem that CNN is not robust to affine transformation and can not consider the spatial relationship between objects in images, Capsule Network (CapsNet) is proposed and the best accuracy of MNIST dataset has achieved. It shows developability on other datasets and its performance is significantly higher than CNN. However, the data categories in the existing routing algorithms of the CapsNet need to be given in advance, which is very difficult to estimate. In a complex dataset or a small sample dataset, calculating the maximum likelihood solution is more complicated, and it will lead to an inevitable singularity problem. For these shortcomings of the routing algorithm, this paper first proposes a variational routing algorithm. The algorithm does not bring additional computational burden, can automatically determine the most suitable data category, and can effectively avoid over-fitting problems. The algorithm uses the variational distribution to integrate the prior distribution information to increase the regularization limit, maximize the lower bound of the model evidence, and avoid the singularity problem caused by computing the maximum likelihood function. In this paper, the MNIST dataset is classified by a simple CapsNet architecture, and the result is encouraging. © 2019 IEEE.

关键词： Structural optimization

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Effects of depth of field on eye movement

Effects of depth of field on eye movement

引用

7th International Symposium on Test Automation and Instrumentation, ISTAI 2018

作者： Zhang, Tingting Xia, Ling Liu, Xiaofeng Kong, Weijie Wu, Xiaoli Changzhou Key Laboratory of Robotics and Intelligent Technology Jiangsu Key Laboratory of Special Robot Technology College of IoT Engineering Hohai University Changzhou China College of Mechanical and Electrical Engineering Hohai University Changzhou China

Depth of field is an important image feature, which can be used to enhance observers’ perception of stereopsis. To explore how the depth of field influenced observers’ attention in images, a within-subject experiment including two factors, two scenes and six levels of depth of field, was performed. A remote desktop eye tracker, Tobii X120 was used to record participants' eye movement during the experiment. The results showed that the limited depth of field could direct observers' attention on the sharp area. However, manipulating depth of field in the same scene may not influence the distribution of observers’ attention. In addition, it was concluded that depth from focus object influences observers' attention significantly, which means that the closer the object is, more attention the object obtains. © 2019 Institution of engineering and technology. All rights reserved.

关键词： Eye movements

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Lighting effects, light distribution matters

Lighting effects, light distribution matters

引用

International Conference on Display technology, ICDT 2019

作者： Xia, Ling Zhang, Tingting Liu, Xiaofeng Pont, Sylvia C. College of IoT Engineering Hohai University Changzhou Key Laboratory of Robotics and Intelligent Technology Jiangsu Key laboratory of Special Robot Technology Changzhou China Department of Industrial Design Perceptual Intelligence lab Delft University of Technology Delft Netherlands

ISBN: (纸本)9781510896161

The interaction between light and its surroundings (i.e. the geometry and materials) shapes the lighting distribution and determines the appearance of scenes and its visual experiences. In this study, we introduced the concept of light distribution solids by distinguishing luminance distribution solids and illuminance distribution solids. It is helpful to understand the spatial and formgiving lighting effects on objects’ appearance. Furthermore, this study together with our previous study (Xia, Pont et al. 2016, Xia, Pont et al. 2016) provide theoretical basis for the exploration of extracting photometry parameters out of HDR panoramic photographs of scenes. © 2019, John Wiley and Sons Inc. All rights reserved.

关键词： Luminance

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Obstacle induced stochastic tree for fast path planning

Obstacle induced stochastic tree for fast path planning

引用

2019 IEEE International Conference on Real-Time Computing and robotics, RCAR 2019

作者： Liu, Xiaofeng Li, Jinming Hu, Fang Yang, Chenguang College of IoT Engineering Hohai University Changzhou213022 China Changzhou Key Laboratory of Robotics and Intelligent Technology Changzhou213022 China Jiangsu Key Laboratory of Special Robots Changzhou213022 China School of Electromechanical and Automobile Engineerng Changzhou Vacational Institue of Engineering Changzhou213164 China Bristol Robotics Laboratory University of the West of England BristolBS16 1QY United Kingdom

ISBN: (纸本)9781728137261

Rapidly-Exploring Random Tree (RRT) has been extensively applied to robot navigation field as a fast and effective path planning method. Rapidly-Exploring Random Tree Star (RRT*), one of the extensions of RRT, outperforms other methods because it can approach the optimal path with the number of iterations increases. Nonetheless, as the number of sampling points increases, it takes too long to get an optimal path and the convergence speed slows dramatically for RRT and all its variants, since the range of sampling is the entire configuration space. In this paper, we propose a novel method of robot path planning in the global knowledge scenario: obstacle induced stochastic tree algorithm. This algorithm regards the center point in obstacles as the sampling point, which significantly reduces the sampling range then shorts the time for path planning. Simulation results demonstrate that our algorithm can find a feasible path at a rapid rate. Compared with RRT and its variants algorithms, the algorithm has better performance in both time and path cost. © 2018 IEEE

关键词： Motion planning

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Intrusion Detection for Marine Meteorological Sensor Network

Intrusion Detection for Marine Meteorological Sensor Network

引用

IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Xin Su Guifu Zhang Minxue Zhang Baoliu Ye Hongyan Xing College of IOT Engineering Hohai University Changzhou Jiangsu China Information Department Hohai University Nanjing Jiangsu China Collaborative Innovation Center for Meteorological Disaster Prediction and Evaluation Nanjing University of Information Science and Technology Nanjing China Jiangsu Key Laboratory of Meteorological Detection and Information Processing Nanjing University of Information Science and Technology Nanjing China

The rapid development of intelligent devices and wireless communication has greatly promoted the intelligence of the maritime Internet of Things (Miot) in recent years, and the marine meteorological sensor network (MMSN) is an essential part of Miot, providing accurate meteorological data for Miot services. However, the frequent information interaction between the device and the external world also causes information leakage risks for MMSN. Intrusion detection technology based on deep learning is an effective defensive mechanism. Thus, we propose a lightweight one-dimensional convolutional neural network (LCNN) intrusion detection model to adapt to the MMSN environment characteristics and device heterogeneity. In addition, an improved supervised adversarial autoencoder (ISAAE) is proposed for synthesizing samples to address the problem that minority class attack samples are difficult to collect and detect. Finally, the simulation experimental results on the NSL-KDD dataset verify the effectiveness of the proposed method.

关键词： Training Wireless communication Adaptation models Convolution Computational modeling Simulation Intrusion detection

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Infer light diffuseness on light probes with different kinds of mesoreliefs

Infer light diffuseness on light probes with different kinds...

引用

16th China International Forum on Solid State Lighting & 2019 International Forum on Wide Bandgap Semiconductors (第十六届中国国际半导体照明论坛暨2019国际第三代半导体论坛)

作者： Yudi Wang Ling Xia Jinfeng Huang Ruipeng Xu Xiaofeng Liu College of IoT Engineering Hohai UniversityJiangsu Key Laboratory of Robotics and Intelligent Technology ChangzhouChina

ISBN: (数字)9781728157566

ISBN: (纸本)9781728157573

The appearance of objects varies enormously depending on light ***,the appearance of objects might be a cue to the light *** would provide a solution for lighting designers to guess-estimate the light diffuseness levels based on the appearance of a light ***,the question remains whether rough probe provides additional cues about light diffuseness comparing with the smooth *** the answer to the last question is yes,whether different kinds of roughness performs the ***,how the estimation of light diffuseness might be influenced by the illumination *** answer these questions,an appearance-matching experiment was performed,within which white spherical probes with four kinds of surface mesoreliefs were adopted and 5 illumination directions were *** results confirmed that observers' abilities to match the light diffuseness were improved by the use of probes with 3D texture,which means that observers can derive light diffuseness from the additional cues provided by the texture over the rough ***,the results showed that the roughness has no obvious effect on diffuseness perception at illumination direction of 90o or 120o owing to the much useful information provided by the terminator of the body shadow.

关键词： Probes Lighting Observers Rough surfaces Surface roughness Three-dimensional displays

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