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检索条件"任意字段=International Conference on Methods and Models in Automation and Robotics"

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Learning to Estimate 3-D States of Deformable Linear Objects from Single-Frame Occluded Point Clouds

Learning to Estimate 3-D States of Deformable Linear Objects...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Kangchen Lv Mingrui Yu Yifan Pu Xin Jiang Gao Huang Xiang Li Department of Automation Tsinghua University China Beijing Academy of Artificial Intelligence Beijing China

Accurately and robustly estimating the state of deformable linear objects (DLOs), such as ropes and wires, is crucial for DLO manipulation and other applications. However, it remains a challenging open issue due to the high dimensionality of the state space, frequent occlusions, and noises. This paper focuses on learning to robustly estimate the states of DLOs from single-frame point clouds in the presence of occlusions using a data-driven method. We propose a novel two-branch network architecture to exploit global and local information of input point cloud respectively and design a fusion module to effectively leverage the advantages of both methods. Simulation and real-world experimental results demonstrate that our method can generate globally smooth and locally precise DLO state estimation results even with heavily occluded point clouds, which can be directly applied to real-world robotic manipulation of DLOs in 3-D space.

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Learning Peg-in-Hole Assembly Skills from Demonstration Based on Geometric Constraints 11

Learning Peg-in-Hole Assembly Skills from Demonstration Base...

引用

11th IEEE Annual international conference on CYBER Technology in automation, Control, and Intelligent Systems, CYBER 2021

作者： Tian, Zhonglai Cheng, Hongtai Zhao, Liang Cao, Shuo School of Mechanical Engineering and Automation Northeastern University Shenyang110819 China

ISBN: (纸本)9781665425278

Existing Learning from Demonstration (LfD) methods that can learn the peg-in-hole assembly skills mainly adopts the impedance control strategy, and generally do not pay attention to the assembly skill segmentation problem. This scheme is susceptible to environmental noise and is difficult to learn stable and effective assembly skills. In this paper, a geometric constraints-based LfD method is proposed and applied to the peg-in-hole assembly task. By identifying geometric constraints from the motion trajectory and considering the contact force information, the demonstration dataset is first segmented into a series of different sub-skills. Hybrid Force/Position Control (HFPC) schema is adopted to model those skills. The selection matrix is identified according to the geometric constraints. The Gaussian Mixture Model (GMM)/Gaussian Mixture Regression(GMR) and quasiperiodic motion models are used to representing the reference trajectories. A switching mechanism is also learned to coordinate those HFPCs with different configurations to accommodate different sub-skills. The experimental results show that the proposed method can accomplish the learning and reproduction of assembly tasks stably and effectively. © 2021 IEEE.

关键词： Demonstrations

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Detection and Classification of Faults in Dynamically Controlled Systems using Gaussian Process Regression with Hidden Markov Model 4

Detection and Classification of Faults in Dynamically Contro...

引用

4th IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Almusawi, Muntadher Muhssan Karuna, Gotlur Suganya, E. Yenugu, Bhanu Chandar Thamizhkani, B. College of Technical Engineering The Islamic University of Al Diwaniyah Department of Computers Techniques Engineering Al Diwaniyah Iraq Gokaraju Rangaraju Institute of Engineering and Technology Department of Artificial Intelligence and Machine Learning Hyderabad India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India Srkr Engineering College Department of Electrical and Electronics Engineering Bhimavaram India New Prince Shri Bhavani College of Engineering and Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350352931

Nowadays, cyber security has evolved over decades in response to increasing complexity and frequency of cyber threats. Traditional protection methods are related to firewalls, anti-virus programs, and intrusion detection systems, rely on pattern matching to counter known attacks. However, these methods are limited in detecting unknown threats, highlighting the need for advanced cyber security measures. In addressing emerging and unknown threats, emphasizing the need for more proactive and adaptive security approaches. To overcome these drawbacks, a Gaussian Process Regression with Hidden Markov Model (GPR-HMM) is proposed for fault detection and classification of faults in dynamically controlled systems using Electrical Fault Detection and Classification (EFDCD) dataset. Initially, for preprocessing, data cleaning, normalization, and scaling are performed using Short-Time Fourier Transform (STFT). Then, for feature extraction Multi Scale Entropy (MSE) is considered to quantify the complexity of time series data at multiple scales. At last, GPR-HMM is employed as classifier for detection and classification of faults. From the results, it clearly shows that the proposed GPR-HMM obtained accuracy value in the context faults detection when compared to existing Data Entry and Office automation (DEOA). © 2024 IEEE.

关键词： Hidden Markov models

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Electrothermal Coupling Model of IGBT Power Module Considering Thermal Coupling 8

Electrothermal Coupling Model of IGBT Power Module Consideri...

引用

8th international conference on Power and Energy Engineering, ICPEE 2024

作者： Song, Shaolin Huangfu, Yigeng Li, Fan Wang, Xiaopeng Tao, Lei Xu, Longzhi School of Automation Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9798331530860

Power device is the core of power electronic system, and its failure is mainly caused by temperature factors. Therefore, in order to predict the junction temperature of the chip as accurately as possible, this paper studies the junction temperature estimation method of IGBT power module. Firstly, considering the influence of temperature, driving resistance, voltage and other factors on the loss, an instantaneous power loss model is established and its results are applied to the thermal model. Then, two kinds of thermal network models are compared and studied, and the steps of extracting parameters from the thermal network model to obtain accurate temperature estimation are given. Finally, the effectiveness of the electrothermal coupling model is verified under different conditions. These two methods are significantly improved compared with the values provided in the data manual, which can reflect the temperature fluctuation under different load conditions and lay a foundation for monitoring the health status of equipment in the future. © 2024 IEEE.

关键词： Outages

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A Haptic Mouse Design with Stiffening Muscle Layer for Simulating Guarding in Abdominal Palpation Training

A Haptic Mouse Design with Stiffening Muscle Layer for Simul...

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IEEE international conference on robotics and automation (ICRA)

作者： He, Liang Leong, Florence Lalitharatne, Thilina Dulantha de Lusignan, Simon Nanayakkara, Thrishantha Imperial Coll London Dyson Sch Design Engn London England Univ Oxford Nuffield Dept Primary Care Hlth Sci Oxford England Univ Oxford Oxford Robot Inst Oxford England

ISBN: (纸本)9781728190778

A patient would contract surface muscles as a reaction called muscle guarding when experiencing discomfort and pain during physical palpation. This reaction carries important information about an affected location. Training physicians to regulate palpation forces to elicit just enough muscle tension is a challenge using real patients. Tunable stiffness mechanisms enabled by soft robotics can be effectively integrated into medical simulator designs for effective clinical education. In this paper, we propose a controllable stiffness muscle layer to simulate guarding for abdominal palpation training. Designs with soft, fine, and rigid granular jamming, stretchable and non-stretchable layer jamming mechanisms were tested and evaluated as methods to create controllable stiffness muscle. User studies have been carried out on 10 naive participants to differentiate the tense and relaxed abdomen with the proposed jamming mechanisms. Muscle samples made of ground coffee (fine granular jamming) and latex layers (stretchable layer jamming) show good usability in simulating abdomen with different stiffness with at least 75% of the user data exhibits more than 70% of decision accuracy for both tested palpation gestures (single finger and multiple fingers) after short pre-training.

关键词： Training Pain Fingers Medical services Muscles Soft robotics Mice

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A Framework for Automated Dissection Along Tissue Boundary

A Framework for Automated Dissection Along Tissue Boundary

引用

IEEE/RAS-EMBS international conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Ki-Hwan Oh Leonardo Borgioli Miloš Žefran Liaohai Chen Pier Cristoforo Giulianotti Department of Electrical and Computer Engineering Robotics Lab College of Engineering University of Illinois Chicago Chicago IL USA Department of Surgery Surgical Innovation and Training Lab College of Medicine University of Illinois Chicago Chicago IL USA

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Robotic surgery promises enhanced precision and adaptability over traditional surgical methods. It also offers the possibility of automating surgical interventions, resulting in reduced stress on the surgeon, better surgical outcomes, and lower costs. Cholecystectomy, the removal of the gallbladder, serves as an ideal model procedure for automation due to its distinct and well-contrasted anatomical features between the gallbladder and liver, along with standardized surgical maneu-vers. Dissection is a frequently used subtask in cholecystectomy where the surgeon delivers the energy on the hook to detach the gallbladder from the liver. Hence, dissection along tissue boundaries is a good candidate for surgical automation. For the da Vinci surgical robot to perform the same procedure as a surgeon automatically, it needs to have the ability to (1) recognize and distinguish between the two different tissues (e.g. the liver and the gallbladder), (2) understand where the boundary between the two tissues is located in the 3D workspace, (3) locate the instrument tip relative to the boundary in the 3D space using visual feedback, and (4) move the instrument along the boundary. This paper presents a novel framework that addresses these challenges through AI -assisted image processing and vision-based robot control. We also present the ex-vivo evaluation of the automated procedure on chicken and pork liver specimens that demonstrates the effectiveness of the proposed framework.

关键词： Three-dimensional displays Medical robotics automation Tracking Endoscopes Instruments Surgery Liver Gallbladder Real-time systems

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Versatile Locomotion by Integrating Ankle, Hip, Stepping, and Height Variation Strategies

Versatile Locomotion by Integrating Ankle, Hip, Stepping, an...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Ding, Jiatao Xin, Songyan Lam, Tin Lun Vijayakumar, Sethu Shenzhen Inst Artificial Intelligence & Robot Soc Shenzhen Peoples R China Univ Edinburgh Sch Informat Edinburgh Midlothian Scotland Chinese Univ Hong Kong Shenzhen Peoples R China AIRS Shenzhen Peoples R China

ISBN: (纸本)9781728190778

Stable walking in real-world environments is a challenging task for humanoid robots, especially when considering the dynamic disturbances, e.g., caused by external perturbations that may be encountered during locomotion. The varying nature of disturbance necessitates high adaptability. In this paper, we propose an enhanced Nonlinear Model Predictive Control (NMPC) approach for robust and adaptable walking - we term it versatile locomotion, by limiting both the Center of Pressure (CoP) and Divergent Component of Motion (DCM) movements. Due to utilization of the Nonlinear Inverted Pendulum plus Flywheel model, the robot is endowed with the capabilities of CoP manipulation (if equipped with finite-sized feet), step location adjustment, upper body rotation, and vertical height variation. Considering the feasibility constraints, especially the usage of relaxed CoP constraints, the NMPC scheme is established as a Quadratically Constrained Quadratic Programming problem, which is solved efficiently by Sequential Quadratic Programming with enhanced solvability. Simulation experiments demonstrate the effectiveness of our method to recruit optimal hybrid strategies in order to realize versatile locomotion, for the robot with finite-sized or point feet.

关键词： Legged locomotion Limiting Perturbation methods Humanoid robots Flywheels Quadratic programming Task analysis

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Deep Learning-based Feature Fusion for Action Recognition Using Skeleton Information

Deep Learning-based Feature Fusion for Action Recognition Us...

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international conference on robotics and Artificial Intelligence (ICRAI)

作者： Fahad Ul Hassan Asif Mattoo Umar Shahbaz Khan Tahir Nawaz Nasir Rashid Department of Mechatronics Engineering College of Electrical and Mechanical Engineering National University of Sciences and Technology Islamabad Pakistan

Various action recognition systems have been proposed, but most of them are not feasible to be used in real-time applications. Skeleton-based action recognition has a low computational cost and is not affected by background changes. As the pose estimation models are becoming faster (almost real-time), a model was created with only 1.8M parameters named DD-net, which uses the skeleton information to predict the action. Recently an improved version of the model came out and was named TD-net. The model is very rich with geometric-based features but lacks motion-based features. To overcome this we added two motion features in the model named acceleration and velocity. These features were created using second order Taylor's approximation, in a window around the current frame. The model accuracy was compared with DD-net, TD-net, and state-of-the-art algorithms using three different datasets. An increase in accuracy is observed for all three datasets (i.e 1.1% for SHERC, 1.7% for FPHAB and 2% for JHMDB) when compared with TD-net.

关键词： Industries Computational modeling Pose estimation Predictive models Streaming media Skeleton Real-time systems

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Power Harvesting towards Sustainable Energy Technology through Ambient Vibrations and Capacitive Transducers

Power Harvesting towards Sustainable Energy Technology throu...

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2023 international conference on Emerging Power Technologies, ICEPT 2023

作者： Jamil, Umar Sulaiman, Muhammad Ghafoor, Nouman Malmir, Mostafa Nawaz, Faisal Shakoor, Rana I. University of Texas at San Antonio Department of Electrical Engineering San Antonio United States Air University Department of Electrical Engineering Islamabad Pakistan University of Limerick Department of Science and Engineering Limerick Ireland Ajou University Department of Electrical Engineering Suwon Korea Republic of National Center of Robotics and Automation Air University Mems Sensor Design and Test Lab Islamabad Pakistan

ISBN: (纸本)9798350301014

As part of the fourth industrial revolution, low-power electronic devices require a power harvesting system to provide energy for their operation because energy harvesting technologies are crucial for enabling 90% of wireless sensor networks. While solar and thermal energy harvesting are popular methods, they have limitations such as dependence on sunlight and thermal gradients, which make them unreliable for low-wattage electronic equipment and wireless sensing networks. Power harvesting from ambient vibrations can lead to a sustainable system. Currently, there is a focus on different power harvesting principles such as electromagnetic, piezoelectric, and electrostatic. This research work presents a novel power harvester design that uses three in-plane capacitive transducers - gap-closing, overlap-varying, and pattern-varying - to operate under ambient vibrations as input energy. With low levels of input vibrations, the device moves, leading to changes in capacitance and the harvesting of reliable electrical power. The design analysis includes capacitance, frequency, and electromechanical evaluations to acquire capacitance matrices, natural frequencies for different modes, displacement covered by moving mass, charge distribution, and pressure distribution. © 2023 IEEE.

关键词： Energy harvesting

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Randomized-enhanced Magnitude Channel Pruning for Radar Jamming Detection 7

Randomized-enhanced Magnitude Channel Pruning for Radar Jamm...

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7th IEEE international conference on Electronic Information and Communication Technology, ICEICT 2024

作者： Ni, Xun Wu, Hao Zhu, Xuan Shi, Zhaopeng Huazhong University of Science and Technology School of Computer Science and Technology Wuhan China Naval University of Engineering National Key Laboratory of Electromagnetic Energy Wuhan China Wuhan University School of Electrical Engineering and Automation Wuhan China Huazhong University of Science and Technology School of Electronic Information and Communications Wuhan China

ISBN: (纸本)9798350384437

With the rapid development of radar jamming technology, traditional detection techniques face significant limitations in complex electromagnetic environments. Recent interference detection methods based on deep learning struggle with processing speed and real-time performance. To address this, we propose a new pruning technique called randomized-enhanced magnitude channel pruning (RMP) to achieve faster detection speeds and more lightweight models. This study evaluates the performance of RMP compared to random channel pruning and magnitude channel pruning in radar jamming detection. To verify RMP's generalization, we also tested it on the VOC2007 [16] object detection task. Results show that RMP consistently reduces mAP@50 loss more effectively than other methods. In one iteration pruning, RMP reduced mAP@50 loss by an average of 0.8% and 1% in radar jamming detection, and by 0.4% and 3.1% in the VOC2007 dataset, compared to random and magnitude pruning, respectively. In multi-pass pruning, RMP reduced mAP@50 loss by an average of 0.3% in radar jamming detection, and by 0.7% and 1.6% in the VOC2007 dataset, compared to random and magnitude pruning, respectively. These findings confirm RMP's effectiveness in maintaining model accuracy and its practical value in fast-response scenarios like radar jamming detection. © 2024 IEEE.

关键词： Jamming

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