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An Improvement of Loop Closure Detection Based on BoW for RatSLAM

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An Improvement of Loop Closure Detection Based on BoW for Ra...

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Jianjun Xu Nanya Yan Fengzhen Tang Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781665465373

The visual perception of the original RatSLAM algorithm works directly on the intensities of image pixels and thus is greatly affected by illuminations, weathers, and other factors. The algorithm may result in perception errors and mapping failures in some situations. Therefore, this paper proposes an image sequence matching algorithm based on a visual dictionary model termed as Bag of Words (BoW) and the dynamic island mechanism to realize fast and accurate scene recognition. The feature vector of scene image is generated by the ORB algorithm, and then the image matching is transformed into the calculation of the distance between image feature vectors, improving the efficiency of image matching. The dynamic island mechanism is used as a detection algorithm to realize the sequence matching of the environment, improving the accuracy of loop closure detection. Experiments are performed in different environments, showing that the visual processing performance and mapping performance of the proposed algorithm are significantly better than the existing RatSLAM algorithm.

关键词： Visualization Dictionaries Heuristic algorithms Image matching Image retrieval Lighting Feature extraction

Towards efficiently diversifying dialogue generation via embedding augmentation

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arXiv 2021年

作者： Cao, Yu Ding, Liang Tian, Zhiliang Fang, Meng School of Computer Science The University of Sydney Australia Tencent Robotics X China Department of CSE The Hong Kong University of Science and Technology Hong Kong

Dialogue generation models face the challenge of producing generic and repetitive responses. Unlike previous augmentation methods that mostly focus on token manipulation and ignore the essential variety within a single sample using hard labels, we propose to promote the generation diversity of the neural dialogue models via soft embedding augmentation along with soft labels in this paper. Particularly, we select some key input tokens and fuse their embeddings together with embeddings from their semantic-neighbor tokens. The new embeddings serve as the input of the model to replace the original one. Besides, soft labels are used in loss calculation, resulting in multi-target supervision for a given input. Our experimental results on two datasets illustrate that our proposed method is capable of generating more diverse responses than raw models while remains a similar n-gram accuracy that ensures the quality of generated responses. © 2021, CC BY.

关键词： Embeddings

Jet mixing enhancement with Bayesian optimization, deep learning, and persistent data topology

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arXiv 2023年

作者： Li, Yiqing Noack, Bernd R. Wang, Tianyu Cornejo Maceda, Guy Y. Pickering, Ethan Shaqarin, Tamir Tyliszczak, Artur School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Harbin Institute of Technology Shenzhen518055 China Department of Mechanical Engineering Tafila Technical University Tafila66110 Jordan Faculty of Mechanical Engineering and Computer Science Czestochowa University of Technology Czestochowa42-201 Poland

We optimize the jet mixing using large eddy simulations (LES) at a Reynolds number of 3000. Key methodological enablers consist of Bayesian optimization, a surrogate model enhanced by deep learning, and persistent data topology for physical interpretation. The mixing performance is characterized by an equivalent jet radius (Req) derived from the streamwise velocity in a plane located 8 diameters downstream. The optimization is performed in a 22-dimensional actuation space that comprises most known excitations. The plant benefits from a 22-dimensional actuation space that comprises most known excitations. This search space parameterizes distributed actuation imposed on the bulk flow and at the periphery of the nozzle in the streamwise and radial directions. The momentum flux measures the energy input of the actuation. The optimization quadruples the jet radius Req with a 7-armed blooming jet after around 570 evaluations. The control input requires 2% momentum flux of the main flow, which is one order of magnitude lower than an ad hoc dual-mode excitation. Intriguingly, a pronounced suboptimum in the search space is associated with a double-helix jet, a new flow pattern. This jet pattern results in a mixing improvement comparable to the blooming jet. A state-of-the-art Bayesian optimization converges towards this double helix solution. The learning is accelerated and converges to another better optimum by including surrogate model trained along the optimization. Persistent data topology extracts the global and many local minima in the actuation space. These minima can be identified with flow patterns beneficial to the mixing. © 2023, CC BY-NC-ND.

关键词： Flow patterns

Design and Implementation of IoT Enabled Smart Assistive Systems for Healthcare Applications

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Design and Implementation of IoT Enabled Smart Assistive Sys...

Communications and Information Technologies (GCCIT), Global Conference on

作者： Dankan Gowda V Srinivas D Rachakonda Srinivas Balaji Shesharao Ingole Priya Dongare Jadhav KDV Prasad Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka India School of Business SR University Warangal Telangana India Department of Computer Science & Engineering Aditya Institute of Technology and Management Srikakulam Andhra Pradesh India Department of Robotics and Automation Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune Maharashtra India (Research) Symbiosis Institute of Business Management Hyderabad Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798350388916

ISBN: (纸本)9798350388923

The use of IoT technology in healthcare systems has been adopted in patient monitoring because IoT technology has been adopted rapidly in the systems. This paper discusses on design and implementation of an IoT integrated smart assistive health care system to enhance the precision and speed of patient health assessment. In the proposed system, wearable sensors are used to capture respiratory rate, pulse rate, blood pressure, oxygen saturation, and body temperature with data to be sent to the cloud server as and when it is received. Some of the features are, however, small data transmission delays, high accuracy in the physiological signals and long durations of monitoring due to the low power consumption. The simulations showed that the response time falls below 500ms, and physicians retain up to a 2 % variance to clinical grade devices, which actualized robust and effective patient care. The incorporation of predicting capacities, thus providing ways of early identification of health complications, makes the system applicable in chronic disease treatments and telemedicine.

关键词： Temperature sensors Temperature measurement Patient monitoring Accuracy Power demand Medical services Blood pressure Time factors Biomedical monitoring Wearable sensors

Semantics for robotic mapping, perception and interaction: A survey

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arXiv 2021年

作者： Garg, Sourav Sünderhauf, Niko Dayoub, Feras Morrison, Douglas Cosgun, Akansel Carneiro, Gustavo Wu, Qi Chin, Tat-Jun Reid, Ian Gould, Stephen Corke, Peter Milford, Michael QUT Centre for Robotics School of Electrical Engineering and Robotics Queensland University of Technology Brisbane Australia Department of Electrical and Computer Systems Engineering Monash University Melbourne Australia School of Computer Science University of Adelaide Adelaide Australia College of Engineering and Computer Science Australian National University Canberra Australia

GenMapping: Unleashing the Potential of Inverse Perspective Mapping for Robust Online HD Map Construction

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arXiv 2024年

作者： Li, Siyu Yang, Kailun Shi, Hao Wang, Song Yao, You Li, Zhiyong The School of Robotics The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China The State Key Laboratory of Extreme Photonics and Instrumentation Zhejiang University Hangzhou310027 China The College of Computer Science Zhejiang University Hangzhou310027 China Shanghai Supremind Technology Company Ltd. Shanghai201210 China The USC Viterbi School of Engineering The University of Southern California Los AngelesCA90089 United States

Online High-Definition (HD) maps have emerged as the preferred option for autonomous driving, overshadowing the counterpart offline HD maps due to flexible update capability and lower maintenance costs. However, contemporary online HD map models embed parameters of visual sensors into training, resulting in a significant decrease in generalization performance when applied to visual sensors with different parameters. Inspired by the inherent potential of Inverse Perspective Mapping (IPM), where camera parameters are decoupled from the training process, we have designed a universal map generation framework, GenMapping. The framework is established with a triadic synergy architecture, including principal and dual auxiliary branches. When faced with a coarse road image with local distortion translated via IPM, the principal branch learns robust global features under the state space models. The two auxiliary branches are a dense perspective branch and a sparse prior branch. The former exploits the correlation information between static and moving objects, whereas the latter introduces the prior knowledge of OpenStreetMap (OSM). The triple-enhanced merging module is crafted to synergistically integrate the unique spatial features from all three branches. To further improve generalization capabilities, a Cross-View Map Learning (CVML) scheme is leveraged to realize joint learning within the common space. Additionally, a Bidirectional Data Augmentation (BiDA) module is introduced to mitigate reliance on datasets concurrently. A thorough array of experimental results shows that the proposed model surpasses current state-of-the-art methods in both semantic mapping and vectorized mapping, while also maintaining a rapid inference speed. Moreover, in cross-dataset experiments, the generalization of semantic mapping is improved by 17.3% in mIoU, while vectorized mapping is improved by 12.1% in mAP. The source code will be publicly available at https://***/lynn-yu/GenMappin

关键词： Photomapping

Physics-Model-Regulated Deep Reinforcement Learning Towards Safety & Stability Guarantees

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Physics-Model-Regulated Deep Reinforcement Learning Towards ...

IEEE Conference on Decision and Control

作者： Hongpeng Cao Yanbing Mao Lui Sha Marco Caccamo Hongpeng Cao is with School of Engineering and Design Technical University of Munich Munich Germany Yanbing Mao is with Engineering Technology Division Wayne State University Detroit MI USA Department of Computer Science University of Illinois at Urbana-Champaign Urbana IL USA School of Engineering and Design and Institute of Robotics and Machine Intelligence Technical University of Munich Munich Germany

Deep reinforcement learning (DRL) has demonstrated impressive success in solving complex control tasks by synthesizing control policies from data. However, the safety and stability of applying DRL to safety-critical systems remain a primary concern and challenging problem. To address the problem, we propose the Phy-DRL: a novel physics-model-regulated deep reinforcement learning framework. The Phy-DRL is novel in two architectural designs: a physics-model-regulated reward and residual control, which integrates physics-model-based control and data-driven control. The concurrent designs enable the Phy-DRL the mathematically provable safety and stability guarantees. Finally, the effectiveness of the Phy-DRL is validated by an inverted pendulum system. Additionally, the experimental results demonstrate that the Phy-DRL features remarkably accelerated training and enlarged reward.

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A novel channel model and optimal power control schemes for mobile mmWave two-tier networks

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TechRxiv

TechRxiv 2022年

作者： Ghosh, Joydev Haci, Huseyin Kumar, Neeraj Al-Utaibi, Khaled A. Sait, Sadiq M. So-In, Chakchai School of Computer Science and Robotics Tomsk Polytechnic University Tomsk Russia Department of Electrical and Electronics Engineering Near East University Mersin 10 Turkey Department of Computer Science & Engineering Thapar Institute of Engineering & Technology Punjab India Computer Science and Software Engineering Department University of Ha’il Saudi Arabia Department of Computer Engineering King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Department of Computer Science College of Computing Khon Kaen University Thailand

We present a unified system model and framework for the analytical performance study of two heterogeneous and physically-distinct, but coexisting, networks that work harmoniously at the same time, space, and frequency domains. The two-tier network model considered in this paper is an overlaying of femtocells on a macrocell. Overlaying femtocells improves the performance by offloading traffic from macrocells and providing spatial diversity. The mmWave channel model employed considers the number of clusters and rays within each cluster to vary due to the end-user mobility. This is a new and different model compared to the widely used channel models for mmWave two-tier networks. Optimal power control is formulated as a sum-rate maximization problem for downlink and uplink transmissions at two-tier networks and a power allocation scheme is proposed by following Shannon-Hartley theorem. A comprehensive and interesting performance investigation is provided, where it is shown that the upper bound on the number of admitted secondary users has a linear relationship with the outage probability threshold, logarithmic relationship with SINR and exponential relationship with channel gain factors. Simulation results show that the proposed scheme with sub-channel iterative Lagrange multipliers search algorithm is very effective at managing the cross-tier interference and can outperform a competitive scheme from literature that is based on cognitive radio technology. The computational complexity analysis of proposed algorithms are also given, since the complexity of second algorithm can be a performance-complexity trade-off issue for systems with limited computation power and time requirements. © 2022, CC BY.

关键词： Femtocell

Robotic Vision for Human-Robot Interaction and Collaboration: A Survey and Systematic Review

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arXiv 2023年

作者： Robinson, Nicole Tidd, Brendan Campbell, Dylan Kulić, Dana Corke, Peter Australian Research Council Centre of Excellence for Robotic Vision School of Electrical Engineering & Robotics QUT Centre for Robotics Queensland University of Technology Faculty of Engineering Turner Institute for Brain and Mental Health Monash University 18 Alliance Lane ClaytonVIC3800 Australia Australian Research Council Centre of Excellence for Robotic Vision School of Electrical Engineering & Robotics QUT Centre for Robotics Queensland University of Technology 2 George Street BrisbaneQLD4000 Australia Visual Geometry Group Department of Engineering Science University of Oxford 17 Parks Road Oxford OxfordshireOX1 3PJ United Kingdom Australian Research Council Centre of Excellence for Robotic Vision Faculty of Engineering Monash University 18 Alliance Lane ClaytonVIC3800 Australia

Robotic vision for human-robot interaction and collaboration is a critical process for robots to collect and interpret detailed information related to human actions, goals, and preferences, enabling robots to provide more useful services to people. This survey and systematic review presents a comprehensive analysis on robotic vision in human-robot interaction and collaboration over the last 10 years. From a detailed search of 3850 articles, systematic extraction and evaluation was used to identify and explore 310 papers in depth. These papers described robots with some level of autonomy using robotic vision for locomotion, manipulation and/or visual communication to collaborate or interact with people. This paper provides an in-depth analysis of current trends, common domains, methods and procedures, technical processes, data sets and models, experimental testing, sample populations, performance metrics and future challenges. This manuscript found that robotic vision was often used in action and gesture recognition, robot movement in human spaces, object handover and collaborative actions, social communication and learning from demonstration. Few high-impact and novel techniques from the computer vision field had been translated into human-robot interaction and collaboration. Overall, notable advancements have been made on how to develop and deploy robots to assist people. Copyright © 2023, The Authors. All rights reserved.

关键词： Human robot interaction