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3D Visibility Graph based Motion Planning and control 19

3D Visibility Graph based Motion Planning and Control

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Proceedings of the 5th international conference on robotics and Artificial Intelligence

作者： Yangwei You Caixia Cai Yan Wu Institute for Infocomm Research Singapore

ISBN: (纸本)9781450372350

this paper proposed a motion planning and control approach for real-time collision avoidance of high degree-of-freedom (DoF) robots. It constructs a 3D visibility graph by representing external obstacles with discrete polyhedrons and searches for the shortest path on it. To consider the complex internal structure of high DoF robots and take full advantage of redundancy, inverse kinematics is solved as an optimization problem which allows for flexible cost functions and constraints. the distance between the robot and external obstacles is treated as an extra constraint in the optimization which works together with visibility graph for collision avoidance. At the end, a pick-place task was successfully performed among obstacles by a simulated dual-arm quadrupedal robot considering the whole-body kinematics and stability, which demonstrated the feasibility of the proposed method.

关键词： robotics Motion Planning Collision Avoidance Visibility Graph

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Intelligent classification of point clouds for indoor components based on dimensionality reduction

Intelligent classification of point clouds for indoor compon...

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international conference on Computational Intelligence and Applications (ICCIA)

作者： Huimin Yang Hangbin Wu College of Surveying and geo-informatics Tongji University Shanghai China

ISBN: (数字)9781728160429

ISBN: (纸本)9781728160436

With the wide application of LiDAR, RGBD cameras and other sensors in computer vision, intelligent robotics, indoor positioning and navigation, the processing of point clouds of indoor scene components has been a difficult problem in these fields. Due to the disorder, sparsity, and limited information of point clouds, it is a challenge to consume point cloud directly. this paper proposes an intelligent classification method based on the disordered point clouds of indoor components. First, a deep learning network is employed to extract high-dimensional features. then the features are divided into different clusters using two algorithms: t-distributed stochastic neighbor embedding (t-SNE) and density-based spatial clustering with applications of noises (DBSCAN). Finally, the classical iterative closest point (ICP) is used to match the laser point clouds with the model point clouds whose semantic labels are known in the model dataset. As a result, the method has a good performance on the classification of indoor point clouds, and the accuracy of classification is 98.6%, which can realize the intelligent classification of indoor components point clouds.

关键词： three-dimensional displays Feature extraction Clustering algorithms Semantics Dimensionality reduction Iterative closest point algorithm

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Automatic detection of awake state during sleep based on the approximate entropy of EMG

Automatic detection of awake state during sleep based on the...

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international conference on Intelligent informatics and Biomedical Sciences (ICIIBMS)

作者： Qihui Ai Bei Wang Jing Jin Xingyu Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai China

ISBN: (数字)9781728180229

ISBN: (纸本)9781728180236

Sleep is important to human beings. A good sleep can bring sufficient energy and keep healthy. Sleep process contains several sleep stages. there are also several short-duration awake states appeared in sleep process. the amount of those awake states during sleep would be related to evaluate the sleep quality. In this study, the automatic detection method of awake state is investigated on the sleep recording of patient with sleep disorder. Two nonlinear features of ApEN and Mc-ApEN are calculated based on the EMG signal recorded during one's overnight sleep process. the detection performance is analyzed and compared. the obtained results showed that the presented method is feasible for awake state detection during sleep, where Mc-ApEN is slightly better than ApEN. It can be an assistant tool for sleep evaluation.

关键词： Tools Electromyography Entropy informatics

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Fuzzy Adaptive control-based Real-time Obstacle Avoidance under Uncertain Perturbations

Fuzzy Adaptive Control-based Real-time Obstacle Avoidance un...

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international conference on Advanced robotics and Mechatronics (ICARM)

作者： Yingbai Hu Guang Chen Longbin Zhang Hang Su Mengyao Li Yunus Schmirander Hu Cao Alois Knoll Chair of Robotics Artificial Intelligence and Realtime Systems Technical University of Munich Munich Germany College of Automotive Engineering Tongji University Shanghai China KTH MoveAbility Lab KTH Royal Institute of Technology Stockholm Sweden Politecnico di Milano Milano Italy Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (数字)9781728164793

ISBN: (纸本)9781728164809

Dynamic Movement Primitives (DMPs) framework is a powerful approach to imitate motor skills, which has outstanding characteristics, such as convergence to the goal position and good imitation performance. Considering complex motion scenes of manipulators, such as changing the goal position or adding obstacles, the original DMPs framework is not sufficient for the requirements. In this paper, we propose a learning control-based hierarchical control strategy to adapt to new goal positions and avoid obstacles: the high-level learning scheme is targeted at imitating the motor skill and generating the optimization trajectory for obstacle avoidance; the lower-level control scheme focuses on the safety and stability of the robot's movement with unknown disturbances. Firstly, the enhanced DMPs framework is presented to imitate the trajectory from human demonstrations, where the novel DMPs can adapt to new goal position with the changing goal, and avoid single or multiple obstacles. then, the fuzzy adaptive control method is employed to control redundant manipulators, where the fuzzy logic system (FLS) is incorporated to approximate an unknown nonlinear function term of the unknown disturbance. Finally, the effectiveness of the proposed learning-control strategy is demonstrated with simulation results. the results show that the developed hierarchical strategy has good performance for new goal adaptation and obstacle avoidance.

关键词： Collision avoidance Trajectory Manipulator dynamics Nonlinear dynamical systems Adaptive control

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A Perception Pipeline for Robotic Harvesting of Green Asparagus 6th

A Perception Pipeline for Robotic Harvesting of Green Aspara...

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6th international-Federation-of-Automatic-control (IFAC) conference on Sensing, control and automation Technologies for Agriculture (AGRIcontrol)

作者： Kennedy, Gerard Ila, Viorela Mahony, Robert Australian Natl Univ Canberra ACT Australia Univ Sydney Sydney NSW Australia

the global population is expected to pass 9 billion by 2050 requiring ongoing improvements in food production methods. Robotic harvesting offers part of the solution to this challenge and has spurred research in the use of agricultural robots (AgBots) for harvesting horticultural crops over the past several decades. While there has been significant progress in automation of harvest of many crops, robotic systems for crops that require selective harvesting remain far from mature. this paper presents the first steps toward a perception pipeline for a selective green asparagus harvesting robot. We show that a novel single-view representation of information from a multi-camera system can be combined with simple temporal filtering to reliably localise asparagus spears in real-time in lab experiments and difficult outdoor conditions. (C) 2019, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： robotics vision automation harvesting agriculture

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Multiple Module Manipulator with control Strategy for Minimally Invasive Surgery

Multiple Module Manipulator with Control Strategy for Minima...

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Recent Advances and Innovations in Engineering (ICRAIE)

作者： Vidhatri Gujela Om Prakash Gujela HMFA Memorial Institute of Engineering & Technology Prayagraj India Bakhtiyarpur College of Engineering Patna India

ISBN: (数字)9781728188676

ISBN: (纸本)9781728188683

this paper introduces the concept of a soft modular manipulator for Minimally Invasive Surgery (MIS). the manipulator is entirely composed of sentimental materials, and it's been designed to supply similar motion capabilities because the octopus's arm so as to succeed in the surgical target while exploiting its whole length to actively interact with the biological structure. the manipulator consists of multiple identical modules, connected serial (each of them are often controlled independently) with flexible fluidic actuator to get multi directional bending and stiffening capabilities supported granular jamming with various controller developed for soft robot as a suggestion for future application in soft robotics. the mixture of application of the manipulator and control strategy of controllers appropriate for his or her particular design.

关键词： Technological innovation Minimally invasive surgery Soft robotics Bending Tools Manipulators Jamming

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Investigation of Optimal Network Architecture for Asparagus Spear Detection in Robotic Harvesting 6th

Investigation of Optimal Network Architecture for Asparagus ...

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6th international-Federation-of-Automatic-control (IFAC) conference on Sensing, control and automation Technologies for Agriculture (AGRIcontrol)

作者： Peebles, M. Lim, S. H. Duke, M. McGuinness, B. Univ Waikato Sch Engn Hamilton New Zealand

the University of Waikato, in collaboration with robotics Plus Limited have developed a robotic asparagus harvester that utilises a convolutional neural network for spear detection. this paper serves as a starting point for selecting an optimal network architecture for this purpose. Specifically, this paper compared the performance of Faster RCNN (FRCNN) and Single Shot Multibox Detector (SSD) on a dataset collected by the harvesters camera systems during field trials in California. Additionally, the effect of labelling the dataset using both a single-class and multi-class paradigm were evaluated. It was found that FRCNN, trained using a single-class paradigm, had the best performance of the tested networks. this was characterized by a F1 score of 0.73, approximately 38% higher other networks tested. Multi-class labelling paradigms were found to result in approximately 27% reduction in F1 score than Single-class labelling paradigms for both FRCNN and SSD. Based on these results we conclude that FRCNN based detectors are better suited for asparagus detection than SSD based detectors. (C) 2019, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： asparagus asparagus harvesting robotics robotic harvesting agricultural automation SSD Faster RCNN neural networks applied neural networks

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Fault Diagnosis of LLC Converter controlled by Fractional Order $PI^{\lambda}D^{\mu}$ under Fault Tree

Fault Diagnosis of LLC Converter Controlled by Fractional Or...

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international conference on Intelligent informatics and Biomedical Sciences (ICIIBMS)

作者： Ming Li Jianning Lu School of Electrical and Electronic Engineering Shanghai Institute of Technology Shanghai China

ISBN: (数字)9781728180229

ISBN: (纸本)9781728180236

A fault diagnosis method based on fractional order PI D control LLC converter is proposed. the main content is to apply the fault tree meth-od to the converter and analyze its fault. First set the LLC converter fault that may occur, select the top events, intermediate and bottom events, and then establish LLC converter fault tree, using the circuit principle analysis and MATLAB simulation, and with the LLC converter under normal working condition of output voltage value comparison, finally, LLC, fault analysis, fault tree to determine the middle and bottom events, so as to find out the LLC converter failure. the comparison of output voltage value through LLC converter not only has faster diagnostic speed, but also has low false diagnosis rate and strong robustness, which plays a very important role in ensuring the normal operation of LLC converter.

关键词： Bridge circuits Robustness Circuit faults Integrated circuit modeling informatics Fault trees Matlab

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Legs' Trajectory Generation for a Cost-Oriented Humanoid Robot: a Symmetrical Approach 19

Legs' Trajectory Generation for a Cost-Oriented Humanoid Rob...

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19th international-Federation-of-Automatic-control (IFAC) conference on Technology, Culture and international Stability (TECIS)

作者： d'Apolito, F. AIT Ctr Vis Automat & Control Vienna Austria

the research on Cost-Oriented Humanoid Robot (COHR) began in 2011. these robots are designed to be human companions and to help humans in their daily life, in the household or at work and to be available on the market for a reasonable price. At the TU Wien, in the IHRT institute, a COHR named Archie is in development. Currently, the control system of the robot is decentralized but a centralized control approach is in evaluation. One of the tasks of this centralized control approach is the legs' trajectory generation. this paper provides first a short description of the centralized control approach in evaluation and then a detailed description of the algorithm for the legs' trajectory generation. Finally, test results of the described algorithm will be provided. (C) 2019, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Cost-oriented automation (COA) Intelligent Systems and Applications robotics and Handling Devices

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3D Vision for Precision Dairy Farming 6th

3D Vision for Precision Dairy Farming

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6th international-Federation-of-Automatic-control (IFAC) conference on Sensing, control and automation Technologies for Agriculture (AGRIcontrol)

作者： O'Mahony, Niall Campbell, Sean Carvalho, Anderson Krpalkova, Lenka Riordan, Daniel Walsh, Joseph Inst Technol Tralee IMaR Res Ctr Tralee Co Kerry Ireland

3D vision systems will play an important role in next-generation dairy farming due to the sensing capabilities they provide in the automation of animal husbandry tasks such as the monitoring, herding, feeding, milking and bedding of animals this paper will review 3D computer vision systems and techniques that are and may be implemented in Precision Dairy Farming. this review will include evaluations of the applicability of Time of Flight and Streoscopic Vision systems to agricultural applications as well as a breakdown of the categories of computer vision algorithms which are being explored in a variety of use cases. these use cases range from robotic platforms such as milking robots and autonomous vehicles which must interact closely and safely with animals to intelligent systems which can identify dairy cattle and detect deviations in health indicators such as Body Condition Score and Locomotion Score. Upon analysis of each use case, it is apparent that systems which can operate in unconstrained environments and adapt to variations in herd characteristics, weather conditions, farmyard layout and different scenarios in animal-robot interaction are required. Considering this requirement, this paper proposes the application of techniques arising from the emerging field of research in Artificial Intelligence that is Geometric Deep Learning. (C) 2019, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： automation and robotics in Agriculture Sensing and automation in Animal Fanning

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