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检索条件"任意字段=International Symposium on Computational Intelligence in Robotics and Automation"

共 3101 条记录，以下是281-290 订阅

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Exploring Large and Complex Environments Fast and Efficiently

Exploring Large and Complex Environments Fast and Efficientl...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Cao, Chao Zhu, Hongbiao Choset, Howie Zhang, Ji Carnegie Mellon Univ Robot Inst Pittsburgh PA 15213 USA

ISBN: (纸本)9781728190778

This paper describes a novel framework for autonomous exploration in large and complex environments. We show that the framework is efficient as a result of its hierarchical structure, where at one level it maintains a sparse representation of the environment and at another level, a dense representation is used within a local planning horizon around the robot. The exploration path is computed at the two levels, coarsely at the global scale and finely around the robot. Such a framework produces detailed paths in the vicinity of the robot, while trades off data resolution far away from the robot for computational efficiency. In experiments, we evaluate our method with a real robot exploring large and complex indoor and outdoor environments. Results show that our method is twice as efficient in covering spaces while using less than one-fifth of processing in comparison to state-of-the-art methods.

关键词： Runtime automation Electric breakdown Conferences Planning computational efficiency Robots

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Attention-Guided Lightweight Network for Real-Time Segmentation of Robotic Surgical Instruments

Attention-Guided Lightweight Network for Real-Time Segmentat...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Ni, Zhen-Liang Bian, Gui-Bin Hou, Zeng-Guang Zhou, Xiao-Hu Xie, Xiao-Liang Li, Zhen Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China CAS Ctr Excellence Brain Sci & Intelligence Techn Beijing 100190 Peoples R China

ISBN: (纸本)9781728173955

The real-time segmentation of surgical instruments plays a crucial role in robot-assisted surgery. However, it is still a challenging task to implement deep learning models to do real-time segmentation for surgical instruments due to their high computational costs and slow inference speed. In this paper, we propose an attention-guided lightweight network (LWANet), which can segment surgical instruments in real-time. LWANet adopts encoder-decoder architecture, where the encoder is the lightweight network MobileNetV2, and the decoder consists of depthwise separable convolution, attention fusion block, and transposed convolution. Depthwise separable convolution is used as the basic unit to construct the decoder, which can reduce the model size and computational costs. Attention fusion block captures global contexts and encodes semantic dependencies between channels to emphasize target regions, contributing to locating the surgical instrument. Transposed convolution is performed to upsample feature maps for acquiring refined edges. LWANet can segment surgical instruments in real-time while takes little computational costs. Based on 960x544 inputs, its inference speed can reach 39 fps with only 3.39 GFLOPs. Also, it has a small model size and the number of parameters is only 2.06 M. The proposed network is evaluated on two datasets. It achieves state-of-the-art performance 94.10% mean IOU on Cata7 and obtains a new record on EndoVis 2017 with a 4.10% increase on mean IOU.

关键词： Instruments Convolution Semantics computational efficiency Decoding Surgery Real-time systems

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High-Speed Planning in Unknown Environments for Multirotors Considering Drag

High-Speed Planning in Unknown Environments for Multirotors ...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Toumieh, Charbel Lambert, Alain Univ Paris Saclay CNRS Lab Rech Informat F-91405 Orsay France

ISBN: (纸本)9781728190778

In this paper, we propose a new planning scheme for high-speed flight in an unknown environment while taking into account drag forces. Drag forces become non-negligible at high speeds and may lead to unfeasible trajectories. The method leverages a new Mixed-Integer Quadratic Program/Model Predictive Control formulation that allows to easily account for drag forces. This formulation makes use of a state-of-the-art Safe Corridors generator to guarantee safety. It uses state-ofthe-art mapping algorithms and solvers to achieve a higher computational efficiency than similar state-of-the-art methods. To the best of our knowledge, our method is the first high-speed planner that generates safe trajectories while accounting for drag. The proposed method is tested in simulation and compared to similar state-of-the-art methods for planning in unknown environments in terms of quality and computation time.

关键词： automation Conferences computational modeling Prediction algorithms Generators Planning Trajectory

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A 2-Dimensional Branch-and-Bound Algorithm for Hand-Eye Self-Calibration of SCARA Robots

A 2-Dimensional Branch-and-Bound Algorithm for Hand-Eye Self...

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IEEE international Conference on robotics and automation (ICRA)

作者： Tao, Chengyu Lv, Na Chen, Shanben Shanghai Jiao Tong Univ Sch Mat Sci & Engn Shanghai Peoples R China Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China

ISBN: (纸本)9781728190778

Due to the high positioning accuracy and relatively low prices, SCARA robots are widely used in industrial fields. The objective of this paper is to propose a hand-eye self-calibration algorithm for SCARA robots which could consider both accuracy and computational cost. The previous global optimal hand-eye calibration algorithms based on branch-and-bound (BnB) optimization is limited by their expensive computational cost. The speed of these algorithms depends on the volume of the search space to a large extent, which is the main concern in this paper. Instead of searching over the 3-dimensional parameter space corresponding to the rotation component of hand-eye pose, a new 2-dimensional search space is defined by separating and coupling some calibration parameters by means of the special structure of SCARA robots, which have 4 degrees of freedom (DoFs) including three translation DoFs and only one rotation DoF. The simulation and real experiments show the similar accuracy but much faster speed of the proposed algorithm compared with previous optimal algorithms based on BnB.

关键词： Couplings automation Service robots Conferences Real-time systems computational efficiency Calibration

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CABiNet: Efficient Context Aggregation Network for Low-Latency Semantic Segmentation

CABiNet: Efficient Context Aggregation Network for Low-Laten...

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IEEE international Conference on robotics and automation (ICRA)

作者： Kumaar, Saumya Lyu, Ye Nex, Francesco Yang, Michael Ying Univ Twente Enschede Netherlands

ISBN: (纸本)9781728190778

With the increasing demand of autonomous machines, pixel-wise semantic segmentation for visual scene understanding needs to be not only accurate but also efficient for any potential real-time applications. In this paper, we propose CABiNet (Context Aggregated Bi-lateral Network), a dual branch convolutional neural network (CNN), with significantly lower computational costs as compared to the state-of-the-art, while maintaining a competitive prediction accuracy. Building upon the existing multi-branch architectures for high-speed semantic segmentation, we design a cheap high resolution branch for effective spatial detailing and a context branch with light-weight versions of global aggregation and local distribution blocks, potent to capture both long-range and local contextual dependencies required for accurate semantic segmentation, with low computational overheads. Specifically, we achieve 76.6% and 75.9% mIOU on Cityscapes validation and test sets respectively, at 76 FPS on an NVIDIA RTX 2080Ti and 8 FPS on a Jetson Xavier NX.

关键词： Visualization Conferences Semantics Buildings Computer architecture Real-time systems computational efficiency

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Soft Robot Optimal Control Via Reduced Order Finite Element Models

Soft Robot Optimal Control Via Reduced Order Finite Element ...

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IEEE international Conference on robotics and automation (ICRA)

作者： Tonkens, Sander Lorenzett, Joseph Pavone, Marco Stanford Univ Dept Mech Engn Stanford CA 94305 USA Stanford Univ Dept Aeronaut & Astronaut Stanford CA 94305 USA

ISBN: (纸本)9781728190778

Finite element methods have been successfully used to develop physics-basixl models of soft robots that capture the nonlinear dynamic behavior induced by continuous deformation. These high-fidelity models are therefore ideal for designing controllers for complex dynamic tasks such as trajectory optimization and trajectory tracking. However, finite element models are also typically very high-dimensional, which makes real-time control challenging. In this work we propose an approach for finite element model-based control of soft robots that leverages model order reduction techniques to significantly increase computational efficiency. In particular, a constrained optimal control problem is formulated based on a nonlinear reduced order finite element model and is solved via sequential convex programming. This approach is demonstrated through simulation of a cable-driven soft robot for a constrained trajectory tracking task, where a 9768-dimensional finite element model is used for controller design.

关键词： Trajectory tracking computational modeling Optimal control Soft robotics Stability analysis Finite element analysis computational efficiency

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Behavioral Repertoires for Soft Tensegrity Robots

Behavioral Repertoires for Soft Tensegrity Robots

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IEEE symposium Series on computational intelligence (IEEE SSCI)

作者： Doney, Kyle Petridou, Aikaterini Karaul, Jacob Khan, Ali Liu, Geoffrey Rieffel, John Union Coll Comp Sci Dept Schenectady NY 12308 USA

ISBN: (纸本)9781728125473

Mobile soft robots offer compelling applications in fields ranging from urban search and rescue to planetary exploration. A critical challenge of soft robotic control is that the nonlinear dynamics imposed by soft materials often result in complex behaviors that are counter-intuitive and hard to model or predict. As a consequence, most behaviors for mobile soft robots are discovered through empirical trial and error and hand-tuning. A second challenge is that soft materials are difficult to simulate with high fidelity - leading to a significant reality gap when trying to discover or optimize new behaviors. In this work we employ a Quality Diversity Algorithm running model-free on a physical soft tensegrity robot that autonomously generates a behavioral repertoire with no a priori knowledge of the robot's dynamics, and minimal human intervention. The resulting behavior repertoire displays a diversity of unique locomotive gaits useful for a variety of tasks. These results help provide a road map for increasing the behavioral capabilities of mobile soft robots through real-world automation.

关键词： Soft robotics Quality Diversity Algorithms Tensegrity Evolutionary robotics

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Intelligent vehicle systems - Applications and new trends

Intelligent vehicle systems - Applications and new trends

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3rd international Conference on Informatics in Control, automation and robotics

作者： Gusikhin, Oleg Filev, Dimitar Rychtyckyj, Nestor Ford Res & Adv Engn 2101 Village Rd Dearborn MI 48121 USA Ford Motor Co Global Mfg Engn Syst Dearborn MI 48121 USA

ISBN: (纸本)9728865600

A person usually does not consider the car sitting in their driveway to be on the leading edge of new technology. However, for most people, the personal automobile has now become their initial exposure to new intelligent computational technologies such as fuzzy logic, neural networks, adaptive computing, voice recognition and others. In this paper we will discuss the various intelligent vehicle systems that are now being deployed into motor vehicles. These intelligent system applications impact every facet of the driver experience and improve both vehicle safety and performance. We will also describe recent developments in autonomous vehicle design and demonstrate that this type of technology is not that far away from deployment. Other applications of intelligent system design apply to adapting the vehicle to the driver's preferences and helping the driver stay aware. The automobile industry is very competitive and there are many other new advances in vehicle technology that cannot be discussed yet. However, this paper provides an introduction into those technologies that have already been announced or deployed and shows how the automobile has evolved from a basic transportation device into an advanced vehicle with a host of on-board computational technologies.

关键词： computational intelligence vehicle systems

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Smart Homes (Conceptual Views) 2

Smart Homes (Conceptual Views)

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2nd international symposium on computational and Business intelligence (ISCBI)

作者： Madakam, Somayya Ramaswamy, R. Natl Inst Ind Engn NITIE IT Applicat Grp Vihar Lake Mumbai India

ISBN: (纸本)9781479975525

Smart Homes (Intelligent Homes) are homes with technologically advanced systems to enable domestic task automation, easier communication and higher security. The applications that can be supported by a Smart Home are very wide and their degree of sophistication depends on the underlying technology used. Some of the application areas include automation, monitoring and control of appliances, security, telemedicine, entertainment, location based services, care for children and the elderly etc. This paper explores the concept of Smart Home paradigms and process. Moreover this study is a systematic review of Smart Homes and different academic projects handled by institutions across the world.

关键词： Smart Home Intelligent Home Automated Home Internet of Things IoT Projects Ambient intelligence

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Road map for implementing AI-driven Oulu Smart excavator 38

Road map for implementing AI-driven Oulu Smart excavator

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38th international symposium on automation and robotics in Construction, ISARC 2021

作者： Mehmood, Hassan Hiltunen, Mikko Makkonen, Tomi Immonen, Matti Pirttikangas, Susanna Heikkilä, Rauno Center for Ubiquitous Computing University of Oulu Finland Construction Automation Research Center in Civil Engineering University of Oulu Finland

ISBN: (纸本)9789526952413

Machine control systems are advancing side by side with the adoption of 5G and growing trends of the internet of things (IoT) has made autonomous excavators more ubiquitous. The autonomous excavators have gained significant interest in the earthworks area, due to their enhanced productivity for long hours, safety, space exploration, mining and construction work. However, A great amount of effort is required to address many existing challenges such as adaptive movement and control, task planning (digging, moving debris, etc.), collaborative work with other machines and humans. In this study, we review the state of the art and provide artificial intelligence (AI-) driven road map for implementing a complete autonomous framework for the earth-moving machine to our test platform ‘Smart Excavator’. Furthermore, the challenges and required effort to implement the framework are also discussed in comparison with existing literature. © 2021 Proceedings of the international symposium on automation and robotics in Construction. All rights reserved.

关键词： artificial intelligence construction engineering data collection excavation excavator machine learning mining smart excavation

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