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A Comparison of Global Optimizers Applied to Point Cloud Registration

A Comparison of Global Optimizers Applied to Point Cloud Reg...

引用

international conference on Control, automation and Information Sciences (ICCAIS)

作者： Pablo Barrios Vicente Guzman Martin Adams Martin Rudorfer Dept. Electrical Eng. & AMTC Universidad de Chile Santiago Chile Dept. Electrical Eng. Universidad de Chile Santiago Chile Dept. Applied AI & Robotics Aston University Birmingham UK

ISBN: (数字)9798331542047

ISBN: (纸本)9798331542054

Ahstract- The registration of point cloud data is essential in various applications, such as computer vision and robotics. The Iterative Closest Point (ICP) algorithm offered a solution to this problem, with several subsequent methods addressing problems including occlusions and variable point data overlap. To also account for detection errors, the Particle Swarm Optimization - Cardinalized Optimal Linear Assignment (PSO-COLA) point data registration algorithm was introduced. This algorithm offers robust registration solutions in the presence of data miss-detections and false alarms, but being based on a Particle Swarm Optimization (PSO) concept is susceptible to local minima problems. To address this problem, we propose the use of two additional meta-heuristic algorithms, namely Artificial Rabbit Optimisation (ARO) and Artificial Bee Colony (ABC), in combination with the Cardinalized Optimal Linear Assignment (COLA) metric. Our experiments show that the resulting ARO-COLA algorithm reduces the execution time compared with the former PSO-COLA algorithm while maintaining high registration accuracy, especially in scenarios with cardinality and spatial errors. The results indicate that the ARO-COLA algorithm is a promising alternative for efficient and accurate point cloud registration.

关键词： Point cloud compression Measurement Rabbits Computer vision Accuracy automation Iterative closest point algorithm Metaheuristics Iterative methods Particle swarm optimization

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Compensatory Movement Detection in Upper Limb Rehabilitation With Deep Learning methods 9

Compensatory Movement Detection in Upper Limb Rehabilitation...

引用

9th RSI international conference on robotics and Mechatronics (ICRoM)

作者： Khoramdel, J. Moori, A. Moghaddam, M. M. Najafi, E. Tarbiat Modares Univ Dept Mech Engn Tehran Iran KN Toosi Univ Technol Fac Mech Engn Tehran Iran

ISBN: (纸本)9781665420945

Stroke risk increases with age. After the stroke, the patients are likely to develop some inappropriate compensatory movements. These movements disrupt normal activities and reduce the effectiveness of the rehabilitation. This paper applies deep learning algorithms like RNN, GRU, LSTM, and Transformer to detect the compensatory movements based on the Microsoft Kinect data from the Toronto rehab stroke pose dataset. The models are trained with focal loss to decrease the effect of the imbalanced data distribution. The trained models have achieved higher accuracy than works done in the literature on this dataset.

关键词： Deep Learning Transformer RNN LSTM GRU Rehabilitation

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Modeling and Data Analysis of Strip Steel Edge Tracking Efficiency Based on ABAQUS

Modeling and Data Analysis of Strip Steel Edge Tracking Effi...

引用

Advanced Information, Mechanical Engineering, robotics and automation (AIMERA), IEEE international conference on

作者： Jijie Ding Xihua Xu Qing Yang Hainan He Xiaochen Wang Quan Yang National Engineering Technology Research Center of Flat Rolling Equipment University of Science and Technology Beijing Beijing China Silicon Steel Sheet Division Xinyu Iron & Steel Group Co. Ltd. China Hot Rolled Plate Plant Hunan Hualing Lianyuan Iron and Steel Co. Ltd China

ISBN: (数字)9798350343335

ISBN: (纸本)9798350343342

In order to address the issue of low control efficiency in strip steel edge tracking during precision rolling, this study developed a dynamic coupling finite element model of the rolling mill rolls and the strip using the ABAQUS software. The aim is to investigate the functional relationship between the roll gap tilt and the strip steel edge deviation at the exit. The research primarily analyzes the influence of strip width, strip thickness, and steel grade on strip steel edge deviation, and under different roll gap tilt conditions, it outputs the variation in deviation and obtains the control coefficient for strip steel edge tracking through interpolation fitting. The results indicate that the influence of steel grade on control efficiency is significantly higher than that of width and thickness, with width being secondary and thickness having the smallest impact. Through interpolating the data, the control coefficient for strip steel edge tracking can be obtained under different operating conditions, higher control efficiency is achieved with a greater roll gap tilt and a smaller control coefficient. This study provides a theoretical foundation for the control of strip steel edge tracking in industrial precision rolling processes.

关键词： Employee welfare Couplings Strips Interpolation Analytical models Fitting Data models Stability analysis Finite element analysis Steel

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Development and Implementation of An Autonomous Smart Seed Sowing Robot With A Precise Closed-Loop Control System

Development and Implementation of An Autonomous Smart Seed S...

引用

robotics, automation, Artificial-intelligence and Internet-of-Things (RAAICON), 2019 IEEE international conference on

作者： Ammar Bin Mohshin Shoaib Rufsun Jannatul Mubasshara Oyshi Fatema Bintay Noor Liza Mithila Sunjana Promi Shaira Tahsin Haque Tanisha Department of EEE National Institute of Textile Engineering and Research Dhaka Bangladesh Department of EECE Military Institute of Science and Technology Dhaka Bangladesh

ISBN: (数字)9798331534400

ISBN: (纸本)9798331534417

This paper investigates the development of a modern seed sowing robot whose main aim is to introduce efficiency in the practice of agriculture to improve accuracy with low cost. This automated seed sowing robot tackles some key problems of existing methods such as labor intensity, environmental impacts, and inefficiency. It’s an autonomous movement machine which works automatically by calculating spacing of seeds with proper depth of planting through a micro-controller. The robot can plant a variety of seed types, both with one and multiple seeds per hole while executing provisions to create optimal directions row-wise as well as column depending on pre-programmed instructions. GPS navigation is fitted to the robot to ensure seeds are placed correctly each time, thereby improving uniformity and decreasing overlap. The achieved accuracy rate is 94.75% and the coverage efficiency is improved by comparison to conventional methods. Additionally, consistent performance results were confirmed in different soil types (sandy, loamy, clay) to show that the system can be used more widely. The key to this study is that robotic technology can be used as a basis for expanding and modifying the way agriculture is done in this industry, providing an inexpensive and accurate method for small farms.

关键词： Accuracy automation Costs Service robots Navigation Soil Agriculture Seeds (agriculture) Robots Farming

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Data-driven Reinforcement Learning for Linear Quadratic Control of Unknown Systems over Lossy Channels 5

Data-driven Reinforcement Learning for Linear Quadratic Cont...

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5th IEEE international conference on automation, Electronics and Electrical Engineering, AUTEEE 2022

作者： Zhang, Liangyin Xiao, Lanqi Wang, Jiepeng Chen, Michael Z. Q. School of Automation Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9781665471978

This research deals with the linear quadratic (LQ) optimal control and suboptimal control of networked systems with packet losses and unknown system dynamics. Three system models including two kinds of Transmission Control protocol (TCP) and one User Datagram protocol (UDP) are discussed. The LQ control problems corresponding to these cases are solved respectively by the model-free methods. In the infinite time domain optimal regulation problem, the model-free method only uses the input and output data to design the controller. A numerical example illustrates the validity of the theoretical results. © 2022 IEEE.

关键词： Reinforcement learning

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Vehicle Motion Control with Jerk Constraint by Nonlinear Model Predictive Control

Vehicle Motion Control with Jerk Constraint by Nonlinear Mod...

引用

international conference on Autonomous Robots and Agents, ICARA

作者： Kyoshiro Itakura European R&D Centre Hitachi Europe Munich Germany

In this paper, a nonlinear model predictive control considering vehicle jerk dynamics is proposed for improving ride comfort of passengers. Since the vehicle model in prediction phase requires high accuracy dynamics in order to handle the jerk motion, the approximated wheel load transfer dynamics is introduced. Also, to obtain the control capability for not only jerk but also acceleration, velocity and position, the expanded state space model including these dimensions into the one has been developed. It improves the utility as autonomous vehicle controller. By numerical simulation in assuming cornering driving scene, the effectiveness that jerk and other vehicle states enable to constraint simultaneously by individual torque distribution by electric power train is validated. Further, the principle of the optimized torque distribution by proposed method is analyzed.

关键词： Torque Heuristic algorithms Dynamics Predictive models Prediction algorithms Nonlinear dynamical systems Vehicle dynamics

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Bringing WALL-E out of the Silver Screen: Understanding How Transformative Robot Sound Affects Human Perception

Bringing WALL-E out of the Silver Screen: Understanding How ...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Zhang, Brian J. Stargu, Nick Brimhall, Samuel Chan, Lilian Fick, Jason Fitter, Naomi T. Oregon State Univ Collaborat Robot & Intelligent Syst CoRIS Inst Corvallis OR 97331 USA Oregon State Univ Mus Dept Corvallis OR 97331 USA

ISBN: (纸本)9781728190778

Lovable robots in movies regularly beep, chirp, and whirr, yet robots in the real world rarely deploy such sounds. Despite preliminary work supporting the perceptual and objective benefits of intentionally-produced robot sound, relatively little research is ongoing in this area. In this paper, we systematically evaluate transformative robot sound across multiple robot archetypes and behaviors. We conducted a series of five online video-based surveys, each with N approximate to 100 participants, to better understand the effects of musician-designed transformative sounds on perceptions of personal, service, and industrial robots. Participants rated robot videos with transformative sound as significantly happier, warmer, and more competent in all five studies, as more energetic in four studies, and as less discomforting in one study. Overall, results confirmed that transformative sounds consistently improve subjective ratings but may convey affect contrary to the intent of affective robot behaviors. In future work, we will investigate the repeatability of these results through in-person studies and develop methods to automatically generate transformative robot sound. This work may benefit researchers and designers who aim to make robots more favorable to human users.

关键词： Silver automation Service robots Chirp conferences Audio systems Motion pictures

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Artificial Neural Network models of Multimodal Biometric Authentication System

Artificial Neural Network Models of Multimodal Biometric Aut...

引用

international conference on Control Systems, Mathematical Modelling, automation and Energy Efficiency (SUMMA)

作者： Albina Sabiryanovna Ismagilova Nikita Dmitrievich Lushnikov Department of Information Security Management Institute of Informatics Mathematics and Robotics Ufa University of Science and Technology Ufa Russian Federation

As part of this research, software for multimodal biometric authentication using neural networks is developed to improve the efficiency of information system user authorization. The architectures of artificial neural networks, which are involved in the processes of recognizing a person by facial image and voice, are given. The internationally used databases (DataSet) of images and audio recordings for training of neural networks are considered. The process of training neural networks, the formed database of biometric personal data and the results obtained by the authors are described.

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ParametricNet: 6DoF Pose Estimation Network for Parametric Shapes in Stacked Scenarios

ParametricNet: 6DoF Pose Estimation Network for Parametric S...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Zeng, Long Lv, Wei Jie Zhang, Xin Yu Liu, Yong Jin Tsinghua Univ Shenzhen Int Grad Sch Dept Adv Mfg Shenzhen Peoples R China Tsinghua Univ Dept Comp Sci & Technol MOE Key Lab Pervas Comp BNRist Beijing Peoples R China

ISBN: (纸本)9781728190778

Most industrial parts are parametric and their special properties are not fully explored yet. This paper proposes a new 6DoF pose estimation network for parametric shapes in stacked scenarios (ParametricNet). It treats a parametric shape, instead of a part object, as a category. The keypoints of individual instances are learned with pointwise regression and Hough voting scheme, from which specific parameter values are calculated. Then, the template keypoints are obtained based on the computed parameter values and the parametric shape templates. Finally, the 6DoF pose is estimated by least-square fitting between the individual instance's and the template's keypoints & centroid. On the public Silt ane dataset, the average of APs of ParametricNet is 96%, compared with 82% for the state-of-the-art method. In addition, a new parametric dataset with four shape templates is constructed, in which the evaluated learning and generalization abilities of ParametricNet outperform the state-of-the-art methods. In particular, for the less symmetric shape, the mAP is improved by over 20%, which is an obvious improvement. Real-world experiments show that our method can grasp parametric shapes with unknown parameter values in slacked scenarios.

关键词： Codes automation Shape Design methodology conferences Pose estimation Fitting

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Research on Intelligent Monitoring and Irrigation System for Farmland Based on IoT and 5GTechnology

Research on Intelligent Monitoring and Irrigation System for...

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automation, Control and robotics Engineering (CACRE), international conference on

作者： Guangda Lu Jianyi Dai Zhuanpin Qin Tinghang Guo Yu Han Mingzhi Wei Tianjin Key Laboratory of Information Sensing & Intelligent Control Automation and Electrical Engineering College Tianjin University of Technology and Education Tianjin China

A farmland intelligent monitoring and irrigation system based on the Internet of Things and 5G technology is designed. The system mainly includes two templates: intelligent monitoring system and intelligent control system, in which the intelligent monitoring system is mainly responsible for detecting soil temperature and humidity and trace elements such as nitrogen, phosphorus and potassium, and the intelligent control system is mainly responsible for remote operation of intelligent irrigation. The system measures soil temperature, humidity and trace elements such as nitrogen, phosphorus and potassium through the sensors in the intelligent monitoring section, and uses 5G wireless transmission technology to send the data collected by the sensors to the Internet of Things, which then transmits the collected information to a mobile app. The system can solve the shortcomings of traditional irrigation methods which are cumbersome and seriously inefficient in irrigating agricultural facilities.

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