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Three-Dimensional Flexible Tactile Sensor Arrays for Perceptual Grasping: Towards Enhanced Perceptual robotics

IEEE Sensors Journal 2025年

作者： Xu, Naijia Liu, Shaoyu Zhang, Daohui Fu, Xin Han, Baisong Hou, Xudong Zhao, Xingang Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Huazhong University of Science and Technology Flexible Electronics Research Center State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and Engineering Hubei Wuhan430074 China University of Shenyang University of Technology Shenyang110016 China

Recent advancements in intelligent robotics have substantially heightened the demand for multidimensional haptic sensors. Traditional haptic sensors are constrained by their sensitivity, anti-interference capabilities, and measurement range, thereby limiting their application in complex environments. Inspired by the structure of human skin, a three-dimensional arrayed magnetic sensor (MCE) was developed, exhibiting high sensitivity (57.625N-1), a wide force measurement range, low hysteresis (1.04%), and high stability. The sensor comprises a three-layer design: the top layer includes a flexible square magnet that deforms under external forces to detect normal and tangential forces;the middle layer incorporates a flexible elastomer (Ecoflex 00-30) combined with a spring to achieve a broad range of force measurements;and the bottom layer consists of a flexible circuit board (FPCB) embedded with an array of Hall sensors to convert magnetic field variations into electrical signals. The normal force measurement range of the MCE sensor spans from 0 to 16 N, with a minimum resolution of 10 mN, enabling the accurate detection of minor force variations. The tangential force is measured within a range of –7 N to 7 N. Experimental findings indicate that the MCE sensor enables real-time slip detection and, when integrated with deep learning algorithms, attains a remarkable object recognition accuracy of 96.36%. This technological progression significantly augments tactile sensing functionalities, thereby facilitating advancements in intelligent robotics, such as precision grasping, and enhancing human-machine interaction, particularly in the realm of medical rehabilitation devices. © 2001-2012 IEEE.

关键词： Intelligent robots

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A Novel Construction Method for 1-Dof Multi-Loop Kirigami Mechanisms

SSRN

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SSRN 2024年

作者： Lv, Weilin Nie, Wansui Wei, Jun Zhang, Jianjun Meng, Chuizhou Liu, Teng Sui, Jin Guo, Shijie Engineering Research Center The Ministry of Education for Intelligent Rehabilitation Equipment and Detection Technologies Hebei University of Technology Tianjin300401 China Hebei Provincial Key Laboratory of Robot Perception and Human-Machine Fusion Hebei University of Technology Tianjin300401 China School of Mechanical Engineering Hebei University of Technology Tianjin300401 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

Kirigami has been utilized in designing deployable mechanisms for various engineering applications. This paper presents a novel construction method for one-degree-of-freedom (1-DOF) multi-loop kirigami mechanisms whose folding motions are kinematically equivalent to their original degree-4 rigid origami. Firstly, we introduce a family of single-loop kirigami (SLK) as the main loop of 1-DOF multi-loop kirigami. Secondly, the coupling-constraint properties of multi-DOF SLKs are clarified, and the structural characteristics of the 1-DOF multi-loop kirigami are defined, based on which, the construction method for the 1-DOF multi-loop kirigami is proposed. Thirdly, the representative models are selected and their kinematics are presented to demonstrate their capability to achieve folding motion equivalent to their origami prototypes, thus verifying the validity of our proposed methodology. Fourthly, the non-constraint condition of the 1-DOF multi-loop kirigami is presented. Finally, we propose extended configurations of 1-DOF multi-loop kirigami and provide the forward and inverse design methods for constructing kirigami meshes. The proposed methodology facilitates the design of large-scale deployable structures. © 2024, The Authors. All rights reserved.

关键词： Degrees of freedom (mechanics)

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A Space Crawling Robotic Bio-Paw (Scrbp) Enabled by Triboelectric Sensors for Surface Identification

SSRN

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SSRN 2022年

作者： Hou, Xuyan Zhang, Li Gao, Guowei Liu, Yuhui Na, Zhonglai Xu, QingZhang Ding, Tianxiang Li, Long Chen, Tao Research Center of Aerospace Mechanism and Control School of Mechatronics Engineering Harbin Institute of Technology Harbin150080 China Department of MECHANICAL ENGINEERING FACULTY OF ENGINEERING Hong Kong Polytechnic University Hong Kong Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electric Engineering Soochow University Suzhou215123 China

With the rapid development of space crawling robotics technology, tactile perception, a significant source for the robot to sense the external environment, has become the preferred solution to gather information in space. Sensors embedded in the robotic end-effector unit can collect and encode the large tactile data, allowing the robot to feel and perceive the real surroundings. Therefore, a space crawling robotic bio-paw (SCRBP) inspired by a cat paw, which performs as a compliant device and can flat the impulse force during the robot’s contact process to the target surface, is proposed in this paper. Meanwhile, a touch-sensing system embedded on SCRBP with self-powered sensors based on the triboelectric nanogenerator (TENG) technology is proposed which can provide the multi-dimensional sensation information in real time. By combining with machine learning (ML), the sensory system can be used for surface identification from the footfall process to the robot’s controller hub. In conclusion, SCRBP device proposed in this paper has obvious advantages in surface information acquisition, space adaptability, power consumption, cost, reliable signal and minimized data. Accordingly, SCRBP system shows fabulous potential in space robotics. © 2022, The Authors. All rights reserved.

关键词： End effectors

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Towards Efficient Path Finding and Moving Stability-Focused Trajectory Planning for Mobile Robots

Towards Efficient Path Finding and Moving Stability-Focused ...

引用

IEEE International Conference on robotics and Biomimetics

作者： Muyang Hou Zhenya Lei Haidong Hu Zhong Wang Yong Wang Le Xie Hesheng Wang Department of Automation Shanghai Jiao Tong University Shanghai China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Beijing Institute of Control Engineering Beijing China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant; on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A* which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion.

关键词： Hands Trajectory tracking Trajectory planning Service robots Stability analysis Safety Mobile robots Resource management Splines (mathematics) Trajectory optimization

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Deep Learning EEG Technology Development and Brain Computer Interface Chips Progress

Deep Learning EEG Technology Development and Brain Computer ...

引用

Acoustics, Speech, and Signal Processing Workshops (ICASSPW), IEEE International Conference on

作者： Wenjie Li Lei Chen Bing Lv Xiaobo Li Weijun Wang Kun Xu Xilun Ding School of Mechanical Engineering and Automation Beihang University Beijing BJ P.R.China Beijing Microelectronics Technology Institute Beijing BJ P.R.China China Academy of Aerospace Electronics Technology Beijing BJ P.R.China Robotics Engineering Center The 21ST Research Institute of China Electronic Technology Group Corporation Shanghai China

ISBN: (数字)9798350374513

ISBN: (纸本)9798350374520

Brain Computer Interfaces establishes an interaction mode between the human brain and external devices, and has broad application prospects. With the development of neuroscience and artificial intelligence technology, brain computer interfaces have rapidly evolved from a single perception stage to a multimodal cognition and complex interaction control stage. This article elaborates on the functional zoning of the brain and cerebellum and the latest research on brain signal classification. Afterwards, the latest research progress of deep learning based EEG signal processing technology was analyzed in depth from three key directions: brain network analysis, research on neurological diseases, cognitive analysis, and emotion recognition. This paper provides a detailed description of the typical structure and main functional unit design ideas of Brain Computer Interface chips, and analyzes the core and difficult technologies from the aspects of acquisition, 3D heterogeneous integration, low-power design, software and brain science research. Finally, based on typical Brain Computer Interface design and application cases, the future development trends of Brain Computer Interface chips and deep learning EEG technology are proposed.

关键词： Deep learning Neurological diseases Three-dimensional displays Neuroscience Pattern classification Signal processing Brain-computer interfaces

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

引用

Computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues Bhawani Shankar Chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack ***,recently a Distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of DDoS attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP DDoS attack DRDoS

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PUTN: A Plane-fitting based Uneven Terrain Navigation Framework

arXiv

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arXiv 2022年

作者： Jian, Zhuozhu Lu, Zihong Zhou, Xiao Lan, Bin Xiao, Anxing Wang, Xueqian Liang, Bin The Center for Artificial Intelligence and Robotics Shenzhen International Graduate School Tsinghua University Shenzhen518055 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China

Autonomous navigation of ground robots has been widely used in indoor structured 2D environments, but there are still many challenges in outdoor 3D unstructured environments, especially in rough, uneven terrains. This paper proposed a plane-fitting based uneven terrain navigation framework (PUTN) to solve this problem. The implementation of PUTN is divided into three steps. First, based on Rapidly-exploring Random Trees (RRT), an improved sample-based algorithm called Plane Fitting RRT∗(PF-RRT∗) is proposed to obtain a sparse trajectory. Each sampling point corresponds to a custom traversability index and a fitted plane on the point cloud. These planes are connected in series to form a traversable "strip". Second, Gaussian Process Regression is used to generate traversability of the dense trajectory interpolated from the sparse trajectory, and the sampling tree is used as the training set. Finally, local planning is performed using nonlinear model predictive control (NMPC). By adding the traversability index and uncertainty to the cost function, and adding obstacles generated by the real-time point cloud to the constraint function, a safe motion planning algorithm with smooth speed and strong robustness is available. Experiments in real scenarios are conducted to verify the effectiveness of the method. The source code is released for the reference of the community. Copyright © 2022, The Authors. All rights reserved.

关键词： Trajectories

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Dynamic Control Barrier Function-based Model Predictive Control to Safety-Critical Obstacle-Avoidance of Mobile Robot

arXiv

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arXiv 2022年

作者： Jian, Zhuozhu Yan, Zihong Lei, Xuanang Lu, Zihong Lan, Bin Wang, Xueqian Liang, Bin The Center for Artificial Intelligence and Robotics Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Department of D-MAVT ETH Zurich Zurich8092 Switzerland School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China

This paper presents an efficient and safe method to avoid static and dynamic obstacles based on LiDAR. First, point cloud is used to generate a real-time local grid map for obstacle detection. Then, obstacles are clustered by DBSCAN algorithm and enclosed with minimum bounding ellipses (MBEs). In addition, data association is conducted to match each MBE with the obstacle in the current frame. Considering MBE as an observation, Kalman filter (KF) is used to estimate and predict the motion state of the obstacle. In this way, the trajectory of each obstacle in the forward time domain can be parameterized as a set of ellipses. Due to the uncertainty of the MBE, the semi-major and semi-minor axes of the parameterized ellipse are extended to ensure safety. We extend the traditional Control Barrier Function (CBF) and propose Dynamic Control Barrier Function (D-CBF). We combine D-CBF with Model Predictive Control (MPC) to implement safety-critical dynamic obstacle avoidance. Experiments in simulated and real scenarios are conducted to verify the effectiveness of our algorithm. The source code is released for the reference of the community. Copyright © 2022, The Authors. All rights reserved.

关键词： Model predictive control

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SC-NeRF: Self-Correcting Neural Radiance Field with Sparse Views

arXiv

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arXiv 2023年

作者： Song, Liang Wang, Guangming Liu, Jiuming Fu, Zhenyang Miao, Yanzi Wang, Hesheng Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

In recent studies, the generalization of neural radiance fields for novel view synthesis task has been widely explored. However, existing methods are limited to objects and indoor scenes. In this work, we extend the generalization task to outdoor scenes, trained only on object-level datasets. This approach presents two challenges. Firstly, the significant distributional shift between training and testing scenes leads to black artifacts in rendering results. Secondly, viewpoint changes in outdoor scenes cause ghosting or missing regions in rendered images. To address these challenges, we propose a geometric correction module and an appearance correction module based on multi-head attention mechanisms. We normalize rendered depth and combine it with light direction as query in the attention mechanism. Our network effectively corrects varying scene structures and geometric features in outdoor scenes, generalizing well from object-level to unseen outdoor scenes. Additionally, we use appearance correction module to correct appearance features, preventing rendering artifacts like blank borders and ghosting due to viewpoint changes. By combining these modules, our approach successfully tackles the challenges of outdoor scene generalization, producing high-quality rendering results. When evaluated on four datasets (Blender, DTU, LLFF, Spaces), our network outperforms previous methods. Notably, compared to MVSNeRF, our network improves average PSNR from 19.369 to 25.989, SSIM from 0.838 to 0.889, and reduces LPIPS from 0.265 to 0.224 on Spaces outdoor scenes. © 2023, CC BY.

关键词： Rendering (computer graphics)

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A Real-time Double Emulsion Droplets Detection System using Hough Circle Transform and Color Detection

A Real-time Double Emulsion Droplets Detection System using ...

引用

International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Shuo Zhu Chunxu Li James Rogers Mario Gianni Ian Howard Center for Robotics and Neural Systems Plymouth University UK School of Automation and Electrical Engineering Qingdao University of Science and Technology Qingdao China

ISBN: (纸本)9781665431545

The object detection based on computer vision algorithms has a wide range of applications in many domains. This paper introduces a real-time detection methodology of 3D printed double emulsion droplets. The first step is to directly segment and extract the color of the inner droplets from the current field of view using thresholding operations of inRange functions of OpenCV in YUV space, so that the droplets color and background color can be obtained separately. Secondly, a binary masking has been employed to locate the centre of the mass of droplets and also distinguish the droplets from surroundings. Next, the Hough circle transform is used to fit a circle to extract the true edge when identifying the contour of the external droplet. The droplet size, generated frequency, and determine whether the droplet is successfully formed can also be obtained using Hough circle transform. A series of experiments have been conducted and indicated that our proposed detection system works well on different double emulsion microfluidic devices with different background and droplet colors.

关键词： Time-frequency analysis Three-dimensional displays Image edge detection Color Transforms Production Streaming media

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