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IEEE International Conference on robotics and Automation (ICRA)

作者： Hanjing Ye Jieting Zhao Yaling Pan Weinan Cherr Li He Hong Zhang Department of Electronic and Electrical Engineering Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology (SUSTech) SUSTech Biomimetic and Intelligent Robotics Lab Guangdong University of Technology

Robot person following (RPF) is a capability that supports many useful human-robot-interaction (HRI) applications. However, existing solutions to person following often as-sume full observation of the tracked person. As a consequence, they cannot track the person reliably under partial occlusion where the assumption of full observation is not satisfied. In this paper, we focus on the problem of robot person following under partial occlusion caused by a limited field of view of a monocular camera. Based on the key insight that it is possible to locate the target person when one or more of hislher joints are visible, we propose a method in which each visible joint contributes a location estimate of the followed person. Experiments on a public person-following dataset show that, even under partial occlusion, the proposed method can still locate the person more reliably than the existing SOTA methods. As well, the application of our method is demonstrated in real experiments on a mobile robot.

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Lateral control of an aerial unmanned robot using visual servoing techniques

Lateral control of an aerial unmanned robot using visual ser...

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International Workshop on Robot Motion and Control (RoMoCo)

作者： G.F. Silveira J. Reginaldo H. Carvalho M.K. Madrid S.S. Bueno P. Rives Robotics and Computer Vision Laboratory/ITI Campinas SP Brazil the State University of Campinas (UNICAMP) Robotics Lab Campinas SP Brazil Patrick Rives is with INRIA Sophia-Antipolis France

This work addresses the issue of the lateral control of an outdoor robotic airship while following a predefined path using visual servoing techniques. The vision-based control application is based on an interaction matrix related to line features extracted from an on-board camera as feedback signals. An output LQR controller for the visual servo control is designed using the lateral dynamic model of the airship. The proposed approach is validated using a realistic simulator of the AS-800 unmanned airship.

关键词： Visual servoing Aerodynamics Vehicle dynamics Robot vision systems Automatic control Servosystems Robot sensing systems robotics and automation Unmanned aerial vehicles Cameras

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Hardware-Agnostic Behavior Trees:Towards Generic Robot Behavior Design

SSRN

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SSRN 2022年

作者： El-Ariss, Wafic Daher, Naseem Elhajj, Imad H. Logistics Robotics BMW Group Petuelring 130 Munich80809 Germany Vision and Robotics Lab Department of Mechanical Engineering American University of Beirut Riad El-Solh Beirut1107 Lebanon Vision and Robotics Lab Department of Electrical and Computer Engineering American University of Beirut Riad El-Solh Beirut1107 Lebanon

Decision-Making (DM) algorithms are an essential component of autonomous agents that control the behavior of Non-Player Characters (NPCs) in computer games, as well as the behavior of autonomous robots. Behavior Trees (BTs) have gained significant traction in recent years for having facilitated the development of complex behaviors for autonomous robots and NPCs, by offering a simple, yet powerful, task-switching architecture that relies on composing modular and reusable unit behaviors to achieve the overall desired *** is well understood how to design BT leaves, the unit behavior of BTs, for them to be reused across the behavior of a single robot system, however, there is a need for these leaves to generalize across systems of differing hardware, thus achieving hardware abstraction, and producing what we call Hardware-Agnostic Behavior Tree Leaves that would reduce the development time and costs of new *** this paper, we address this goal by first presenting a new formulation for BTs that incorporates parameterization. Subsequently, we propose a method to specify DM behaviors in a hardware-agnostic manner. Then, we apply object-oriented design methods to specify BTs. We combine the three techniques to define Hardware-Agnostic Behavior Tree Leaves , and propose a method to design them so that these unit behaviors can be reused across systems of differing hardware. We demonstrate the applicability of our proposed method by designing a completely hardware-agnostic, and thus reusable, BT software that we then apply on two real robotic systems with differing hardware used at the BMW Group, and we show that the BT software developed using our methods leads to higher reusability (as per Chidamber and Kemerer metrics) by conducting a comparison against a benchmark BT software built using state-of-the-art methods. Four out of the five used Chidamber and Kemerer metrics indicated that our method increased reusability, it resulted in software that is 7.7% shorter

关键词： Industrial robots

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Object recognition using saliency maps and HTM learning

Object recognition using saliency maps and HTM learning

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2012 IEEE International Conference on Imaging Systems and Techniques, IST 2012

作者： Kostavelis, Ioannis Nalpantidis, Lazaros Gasteratos, Antonios Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Vas. Sofias 12 GR-67100 Xanthi Greece Computer Vision and Active Perception Lab. Centre for Autonomous Systems Royal Institute of Technology - KTH SE-100 44 Stockholm Sweden

ISBN: (纸本)9781457717741

In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations. In accordance with HTM's biological inspiration, human vision mechanisms can be used to preprocess the input images. Therefore, the input images undergo a saliency computation step, revealing the plausible information of the scene, where a human might fixate. The adoption of the saliency detection module releases the HTM network from memorizing redundant information and augments the classification accuracy. The efficiency of the proposed framework has been experimentally evaluated in the ETH-80 dataset, and the classification accuracy has been found to be greater than other HTM systems. © 2012 IEEE.

关键词： Object recognition

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Submapping SLAM based on acoustic data from a 6-DOF AUV

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IFAC Proceedings Volumes 2010年第20期43卷 16-21页

作者： Josep Aulinas Chee Sing Lee Joaquim Salvi Yvan R. Petillot Computer Vision and Robotics group (ViCoRob) University of Girona 17071 Girona Spain Oceans Systems Lab School of EPS Heriot-Watt University EH144AS Edinburgh United Kindgom

Autonomous Underwater Vehicles (AUVs) need positioning systems besides the Global Positioning System (GPS), since GPS does not work in underwater scenarios. Possible solutions are the Simultaneous Localization and Mapping (SLAM) algorithms. SLAM algorithms aim to build a map while simultaneously localizing the vehicle within this map. However, they offer limited performance when faced with large scale scenarios. For instance, they do not create consistent maps for large areas, mainly because uncertainties increase with the scale of the scenario. In addition, the computational cost increases with the map size. The use of local maps reduces computational cost and improves map consistency. Following this idea, in this paper we propose a new SLAM approach that uses independent local maps together with a global level stochastic map. The global level contains the relative transformations between local maps. These local maps are updated once a new loop is detected. Local maps that are sharing a high number of features are updated through fusion, maintaining the correlation between landmarks and vehicle. Experimental results on real data obtained from the REMUS-100 AUV show that our approach is able to obtain large map areas consistently.

关键词： Autnonomous vehicles robotics navigation

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SESAME: Semantic editing of scenes by adding, manipulating or erasing objects

arXiv

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arXiv 2020年

作者： Ntavelis, Evangelos Romero, Andrés Kastanis, Iason van Gool, Luc Timofte, Radu Computer Vision Lab. ETH Zurich Switzerland Robotics and Machine Learning CSEM SA Switzerland PSI ESAT KU Leuven Belgium

Recent advances in image generation gave rise to powerful tools for semantic image editing. However, existing approaches can either operate on a single image or require an abundance of additional information. They are not capable of handling the complete set of editing operations, that is addition, manipulation or removal of semantic concepts. To address these limitations, we propose SESAME, a novel generator-discriminator pair for Semantic Editing of Scenes by Adding, Manipulating or Erasing objects. In our setup, the user provides the semantic labels of the areas to be edited and the generator synthesizes the corresponding pixels. In contrast to previous methods that employ a discriminator that trivially concatenates semantics and image as an input, the SESAME discriminator is composed of two input streams that independently process the image and its semantics, using the latter to manipulate the results of the former. We evaluate our model on a diverse set of datasets and report state-of-the-art performance on two tasks: (a) image manipulation and (b) image generation conditioned on semantic labels. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Accurate mapping and planning for autonomous racing

arXiv

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arXiv 2020年

作者： Andresen, Leiv Brandemuehl, Adrian Hönger, Alex Kuan, Benson Vödisch, Niclas Blum, Hermann Reijgwart, Victor Bernreiter, Lukas Schaupp, Lukas Chung, Jen Jen Bürki, Mathias Oswald, Martin R. Siegwart, Roland Gawel, Abel Autonomous Systems Lab Eth Zürich Switzerland Computer Vision and Geometry Group Eth Zürich Switzerland Sevensense Robotics Ag

This paper presents the perception, mapping, and planning pipeline implemented on an autonomous race car. It was developed by the 2019 AMZ driverless team for the Formula Student Germany (FSG) 2019 driverless competition, where it won 1st place overall. The presented solution combines early fusion of camera and LiDAR data, a layered mapping approach, and a planning approach that uses Bayesian filtering to achieve high-speed driving on unknown race tracks while creating accurate maps. We benchmark the method against our team's previous solution, which won FSG 2018, and show improved accuracy when driving at the same speeds. Furthermore, the new pipeline makes it possible to reliably raise the maximum driving speed in unknown environments from 3 m/s to 12 m/s while still mapping with an acceptable RMSE of 0.29 m. Copyright © 2020, The Authors. All rights reserved.

关键词： Pipelines

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What programmable vector fields can (and cannot) do: force field algorithms for MEMS and vibratory plate parts feeders

What programmable vector fields can (and cannot) do: force f...

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IEEE International Conference on robotics and Automation (ICRA)

作者： K.-F. Bohringer B.R. Donald N.C. MacDonald Robotics & Vision Lab. Cornell Univ. Ithaca NY USA Robotics & Vision Laboratory Department of Computer Science Cornell University Ithaca NY USA School of Electrical Engineering and Cornell Nanofabrication Facility Cornell University Ithaca NY USA

Programmable vector fields can be used to control a variety of flexible planar parts feeders. When a part is placed on our devices, the programmed vector field induces a force and moment upon it. Over time, the part may come to rest in a dynamic equilibrium state. We demonstrate lower bounds on what the devices cannot do, and results on a classification of control strategies. We suggest sufficient conditions for programmable fields to induce well-behaved equilibria on every part placed on our devices. We define composition operators to build complex strategies from simple ones, and show the resulting fields are also well-behaved. We discuss whether fields outside this class can be useful and free of pathology. Using these tools, we describe new manipulation algorithms, and improve existing planning algorithms by a quadratic factor, and the plan-length by a linear factor. We relax earlier dynamic and mechanical assumptions to obtain more robust and flexible strategies. Finally, we consider parts feeders that can only implement a very limited "vocabulary" of vector fields. We discuss the trade-off between mechanical complexity and planning complexity.

关键词： Micromechanical devices Automatic control Force control Feeds Assembly Robot vision systems laboratories computer science Nanofabrication Uniform resource locators

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SLAM based Selective Submap Joining for the Victoria Park Dataset

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IFAC Proceedings Volumes 2010年第16期43卷 557-562页

作者： Josep Aulinas Xavier Lladó Joaquim Salvi Yvan R. Petillot Computer Vision and Robotics group (ViCoRob) University of Girona Girona 17071 Spain Ocean Systems Lab Heriot Watt University Edinburgh EH14 4AS United Kingdom

One of the main drawbacks of current SLAM algorithms is that they do not result in consistent maps of large areas, mainly because the uncertainties increase with the scenario. In addition, as the map size grows the computational costs increase, making SLAM solutions unsuitable for on-line applications. The use of local maps has been demonstrated to be useful in these situations, reducing computational cost and improving map consistency. Following this idea, this paper proposes a technique based on using independent local maps together with a global stochastic map. The global level contains the relative transformations between local maps, which are updated once a new loop is detected. In addition, the information within the local maps is also corrected. Thus, maps sharing a high number of features are updated through fusion and the correlation between landmarks and vehicle is maintained. Results on synthetic data and on the Victoria Park Dataset show that our approach is able to consistently map large areas and the computational costs are lower.

关键词： Localization mapping Extended Kalman Filter data association mobile robots

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Maize EfficientNet Fusion: Advancing Maize Disease Detection with MF-NET 25

Maize EfficientNet Fusion: Advancing Maize Disease Detection...

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25th International Conference on Digital Image Computing: Techniques and Applications, DICTA 2024

作者： Khalid, Fatima Hanif, Muhammad Ul Ain, Qurat Ghulam Ishaq Khan Institute of Engineering Sciences and Engineering Faculty of Computer Science and Engineering KPK Topi Pakistan Ghulam Ishaq Khan Institute of Engineering Sciences and Engineering Aerial Robotics and Vision Lab KPK Topi Pakistan Shifa Tameer-E-Millat University Department of Computing Islamabad Pakistan

ISBN: (纸本)9798350379037

Maize is a vital global crop, essential for food security but highly susceptible to diseases that threaten yield and quality. Traditional methods for detecting these diseases are computationally intensive and rely on high-quality images, limiting their practical use in diverse field conditions. This research addresses these challenges by proposing MF-Net, a novel model that leverages two EfficientNet-b0 architectures with ReLU and Swish activation functions. Our approach involves partially training Model R with frozen early layers using ReLU, and fully training Model S with Swish activation for enhanced optimization and robustness. We employ model concatenation and feature fusion techniques to create a lightweight yet powerful model, complemented by additional layers for improved feature extraction and regularization. Experimental results on the Corn Disease and Severity (CD&S) dataset are compelling: MF-Net achieves a remarkable 95.7% accuracy and 96% precision in disease classification, and 88.3% accuracy and 88.46% precision in severity level detection. These results highlight the model's effectiveness under challenging conditions such as cluttered backgrounds and variable lighting, significantly reducing computation time without compromising accuracy. Hence, MF-Net presents an innovative and efficient solution for maize disease detection and severity assessment, offering significant advancements for agricultural practices and crop management. © 2024 IEEE.

关键词： CD&S Dataset EffiecientNet-b0 Fused Truncated EfficientNet Maize Disease Maize Severity Level

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