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检索条件"任意字段=27th Conference on Intelligent Robots and Computer Vision: Algorithms and Techniques"

共 120 条记录，以下是31-40 订阅

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Revolutionizing Tree Management via intelligent Spatial techniques 19

Revolutionizing Tree Management via Intelligent Spatial Tech...

引用

27th ACM SIGSPATIAL International conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS)

作者： Xie, Yiqun Shekhar, Shashi Feiock, Richard Knight, Joseph F. Univ Minnesota Twin Cities Dept Comp Sci & Engn Minneapolis MN 55455 USA Florida State Univ Askew Sch Publ Admin & Policy Tallahassee FL 32306 USA Univ Minnesota Twin Cities Dept Forest Resources Minneapolis MN USA

ISBN: (纸本)9781450369091

Tree management is becoming a big issue in a variety of societal domains. In recent years, historic wildfires and blackouts caused by failures in tree management have increased in both quantity and severity, resulting in many deaths and financial loses in the tens of billions of dollars. Many communities are also suffering from massive tree loss (e.g., in the millions) that affects the health and well-being of citizens. these problems are likely to worsen due to climate change, aging infrastructure and population growth. Tree management needs a revolution to deal with these urgent problems. this opens up new challenges and opportunities for the spatial community. this paper presents some of the open research problems from the perspectives of individual tree mapping and characterization as well as decision making and in-field intervention.

关键词： Tree management Spatial intelligent techniques vision

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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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Scenario-based simulation of intelligent driving functions using neural networks 9

Scenario-based simulation of intelligent driving functions u...

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9th International conference on Computing, Communication and Networking Technologies (ICCCNT)

作者： Kaur, Parampreet Sobti, Rajeev Lovely Profess Univ Sch Comp Sci Engn Jalandhar India

ISBN: (纸本)9781538644300

the modern technological era is witnessing a significant advancement in AI related fields such as machine learning, mobile robots and autonomous vehicles. the success of such systems is immensely dependent on computer vision algorithms. the entirely software enabled intelligent vehicles will soon be hitting the roads in the coming decade. Such self-controlled mobile robots may still be vulnerable to accidents or crashes. therefore, the industry requires some state of the art techniques to substantiate the safety and protection of its passengers as well as other road users. Simulation based testing methods have been in use from a long time, but the newer smart vehicle innovations require better versions of simulation techniques. We thus provide an improved mechanism for simulation testing to validate safe navigation of cars in variety of traffic scenarios. Neural network approach integrated with agent based modelling is described in this paper.

关键词： Agent based modelling intelligent driving SAE autonomy levels simulation ADAS

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Towards Event-driven Object Detection with Off-the-shelf Deep Learning

Towards Event-driven Object Detection with Off-the-shelf Dee...

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25th IEEE/RSJ International conference on intelligent robots and Systems (IROS)

作者： Iacono, Massimiliano Weber, Stefan Glover, Arren Bartolozzi, Chiara Ist Italiano Tecnol ICub Facil Genoa Italy

ISBN: (纸本)9781538680940

Event cameras are an emerging technology in computer vision, offering extremely low latency and bandwidth, as well as a high temporal resolution and dynamic range. Inherent data compression is achieved as pixel data is only produced by contrast changes at the edges of moving objects. However, current trends in state-of-the-art visual algorithms rely on deep-learning with networks designed to process colour and intensity information contained in dense arrays, but are notoriously computationally heavy. While the combination of these visual technologies could lead to fast, efficient, and accurate detection and recognition algorithms, it is uncertain whether the compressed event-camera data actually contain the required information for these techniques to discriminate between objects and a cluttered background. this paper presents a pilot study in which off-the-shelf deep-learning is applied to visual events for object detection on the iCub robotic platform, and analyses the impact of temporal integration of the event data. We also present a novel pipeline that bootstraps event-based dataset annotation from mature frame-based algorithms, in order to more quickly generate the required datasets.

关键词： Cameras Robot vision systems Visualization Training Object detection

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Advances in Service and Industrial Robotics: Proceedings of the 27th International conference on Robotics in Alpe-Adria Danube Region (RAAD 2018)

引用

2018年

作者： Nikos A Aspragathos Panagiotis N Koustoumpardis Vassilis C Moulianitis

ISBN: (纸本)9783030002312

this volume contains the proceedings of the RAAD 2018 conference, covering major areas of research and development in robotics. It provides an overview on the advances in robotics, more specifically in novel design and applications of robotic systems; dexterous grasping, handling and intelligent manipulation; intelligent cooperating and service robots; advanced robot control; human-robot interfaces; robot vision systems and visual serving techniques; mobile robots; humanoid and walking robots; field and agricultural robotics; bio-inspired and swarm robotic systems; developments towards micro and nano-scale robots; aerial, underwater and spatial robots; robot integration in holonic manufacturing; personal robots for ambient assisted living; medical robots and bionic prostheses; intelligent information technologies for cognitive robots etc. the primary audience of the work are researchers as well as engineers in robotics and mechatronics.

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Efficient Absolute Orientation Revisited

Efficient Absolute Orientation Revisited

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25th IEEE/RSJ International conference on intelligent robots and Systems (IROS)

作者： Lourakis, Manolis Terzakis, George Fdn Res & Technol Hellas Inst Comp Sci Iraklion Greece Univ Portsmouth Fac Technol Portsmouth Hants England

ISBN: (纸本)9781538680940

Absolute orientation estimation is the determination of the similarity transformation between two sets of corresponding 3D points, a task arising frequently in computer vision and robotics. We have recently proposed an absolute orientation algorithm based on the Fast Optimal Attitude Matrix (FOAM) algorithm from astronautics and demonstrated that it is more efficient computationally compared to widely-used approaches involving costly eigen- and singular-value matrix decompositions. In this work, we compare our FOAM-based solution with several more algorithms derived from attitude estimation techniques and show that further computational savings are possible by employing an algorithm grounded on the Optimal Linear Attitude Estimator (OLAE) method.

关键词： Quaternions Estimation Symmetric matrices Eigenvalues and eigenfunctions Matrix decomposition Covariance matrices computer vision

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Teaching robots to Predict Human Motion

Teaching Robots to Predict Human Motion

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25th IEEE/RSJ International conference on intelligent robots and Systems (IROS)

作者： Gui, Liang-Yan Zhang, Kevin Wang, Yu-Xiong Liang, Xiaodan Moura, Jose M. F. Veloso, Manuela Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA Carnegie Mellon Univ Machine Learning Dept Pittsburgh PA 15213 USA

ISBN: (纸本)9781538680940

Teaching a robot to predict and mimic how a human moves or acts in the near future by observing a series of historical human movements is a crucial first step in human-robot interaction and collaboration. In this paper, we instrument a robot with such a prediction ability by leveraging recent deep learning and computer vision techniques. First, our system takes images from the robot camera as input to produce the corresponding human skeleton based on real-time human pose estimation obtained with the OpenPose library. then, conditioning on this historical sequence, the robot forecasts plausible motion through a motion predictor, generating a corresponding demonstration. Because of a lack of high-level fidelity validation, existing forecasting algorithms suffer from error accumulation and inaccurate prediction. Inspired by generative adversarial networks (GANs), we introduce a global discriminator that examines whether the predicted sequence is smooth and realistic. Our resulting motion GAN model achieves superior prediction performance to state-of-the-art approaches when evaluated on the standard H3.6M dataset. Based on this motion GAN model, the robot demonstrates its ability to replay the predicted motion in a human-like manner when interacting with a person.

关键词： robots Gallium nitride Generative adversarial networks Predictive models Cameras Skeleton Decoding

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Scenario-based simulation of intelligent driving functions using neural networks

Scenario-based simulation of intelligent driving functions u...

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International conference on Computing, Communication and Networking Technologies

作者： Parampreet Kaur Rajeev Sobti School of Computer Science Engineering Lovely Professional University Jalandhar India

关键词： Agent based modelling intelligent driving SAE autonomy levels Simulation ADAS

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Particle filter localization and real time obstacle avoidance control based on 3D perception for wheelchair mobile robot

Particle filter localization and real time obstacle avoidanc...

引用

International IEEE conference on intelligent Systems, IS

作者： Emna Baklouti Nader Ben Amor Mohamed Jallouli Ecole Nationale d'Ingénieur de Sfax Université de Sfax Tunisie Computer & Embedded Systems Laboratory (CES)

Obstacle detection and localization behaviours have shown to work robustly in 2D perceived environment. With the progress of proximity sensors, precisely the emergence of 3D vision techniques, it would be interesting to examine these motion controllers whether for 3D perceived environment. 2D basic algorithms for obstacle avoidance or robot location, needs reformulation in order to process data from 3D perception devices. In this work, we introduce a 3D obstacle detection controller, combined with particle filter localization. the obstacle detection control described in this paper address 3D obstacles with different shapes and the particle filter uses 3D environment data to correct the wheelchair localization based on his kinematics model.

关键词： three-dimensional displays Wheelchairs robots Two dimensional displays Kinematics Collision avoidance Sensors

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7th Mexican conference on Pattern Recognition, MCPR 2015

7th Mexican Conference on Pattern Recognition, MCPR 2015

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7th Mexican conference on Pattern Recognition, MCPR 2015

ISBN: (纸本)9783319192635

the proceedings contain 34 papers. the special focus in this conference is on Pattern Recognition, Artificial intelligent techniques, Image Processing, Robotics and computer vision. the topics include: Recommendation of process discovery algorithms through event log classification;a new method based on graph transformation for FAS mining in multi-graph collections;classification of hand movements from non-invasive brain signals using lattice neural networks with dendritic processing;a different approach for pruning micro-clusters in data stream clustering;computing constructs by using typical testor algorithms;multitask reinforcement learning in nondeterministic environments;prototype selection for graph embedding using instance selection;correlation of resampling methods for contrast pattern based classifiers;boosting the permutation based index for proximity searching;similarity analysis of archaeological potsherds using 3D surfaces;automatic detection of clouds from aerial photographs of snowy volcanoes;a comparative study of robust segmentation algorithms for iris verification system of high reliability;vision-based humanoid robot navigation in a featureless environment;evaluation of local descriptors for vision-based localization of humanoid robots;sampled weighted min-hashing for large-scale topic mining;patterns used to identify relations in corpus using formal concept analysis;improving information retrieval through a global term weighting scheme;sentiment groups as features of a classification model using a Spanish sentiment lexicon;modified binary inertial particle swarm optimization for gene selection in DNA microarray data;encoding polysomnographic signals into spike firing rate for sleep staging and patrolling routes optimization using ant colonies.

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