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arXiv 2022年

作者： Kennedy, Justin M. Heinovski, Julian Quevedo, Daniel E. Dressler, Falko The School of Electrical Engineering and Robotics Queensland University of Technology Australia The School of Electrical Engineering and Computer Science TU Berlin Germany

Cooperative adaptive cruise control presents an opportunity to improve road transportation through increase in road capacity and reduction in energy use and accidents. Clever design of control algorithms and communication systems is required to ensure that the vehicle platoon is stable and meets desired safety requirements. In this paper, we propose a centralized model predictive controller for a heterogeneous platoon of vehicles to reach a desired platoon velocity and individual inter-vehicle distances with driver-selected headway time. As a novel concept, we allow for interruption from a human driver in the platoon that temporarily takes control of their vehicle with the assumption that the driver will, at minimum, obey legal velocity limits and the physical performance constraints of their vehicle. The finite horizon cost function of our proposed platoon controller is inspired from the infinite horizon design. To the best of our knowledge, this is the first platoon controller that integrates human-driven vehicles. We illustrate the performance of our proposed design with a numerical study, demonstrating that the safety distance, velocity, and actuation constraints are obeyed. Additionally, in simulation we illustrate a key property of string stability where the impact of a disturbance is reduced through the platoon. Copyright © 2022, The Authors. All rights reserved.

关键词： Controllers

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Development of a navigation performance evaluation system

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science China(Information sciences) 2020年第12期63卷 263-265页

作者： Fangfang ZHAO Wei ZHANG Shuzhi Sam GE School of Computer Science and Engineering Center for RoboticsUniversity of Electronic Science and Technology of China Department of Electrical and Computer Engineering National University of Singapore Institute for Future (IFF) Qingdao University

Dear editor,Owing to little exploration experience and great technical difficulty of deep space exploration autonomous navigation, the corresponding navigation performance evaluation system is seldom perfected [1].

关键词： Autonomous navigation Performance evaluation Evaluation system Evaluation indicator Evaluation method

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Choosing a Suitable Requirement Prioritization Method: A Survey

SSRN

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SSRN 2023年

作者： Mahmoud Alhenawi, Esra'a Awawdeh, Shatha Khurma, Ruba Abu Castillo, Pedro A. Department of Computer Science King Abdullah II School of Information Technology The University of Jordan Amman Jordan Applied Science Private University Jordan Faculty of Information Technology Computer Science department Al-Ahliyya Amman University Amman Jordan Department of Computer Engineering Automation and Robotics University of Granada Granada Spain

Software requirements prioritization plays a crucial role in software development. It can be viewed as the process of ordering requirements by determining which requirements must be done first and which can be done later. Powerful requirements prioritization techniques are of paramount importance to finish the implementation on time and budget. Many factors affect requirement prioritization such as stakeholder expectations, complexity, dependency, scalability, risk and cost. Therefore, finding the proper order of requirements is a challenging process. Hence, different types of requirements prioritization techniques have been developed to support this task. In this survey we propose a novel classification that can classify the prioritization techniques under two major classes: relative and exact prioritization techniques class where each class is divided into two subclasses. We also provide an overview about fifteen different requirements prioritization techniques that are classified under our proposed classification. Moreover, we make a comparison between methods that are related to the same subclass to analyze their strengths and weakness. Based on the comparison results, the properties for each proposed subclass of techniques are identified. Depending on these properties, we present some recommendations to help project managers in the process of selection the most suitable technique to prioritize requirements based on their projects characteristics. © 2023, The Authors. All rights reserved.

关键词： Requirements engineering

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Research on Natural Environment Protection Based on Blockchain technology to Facilitate Ecological Balance and Regional Revitalization

Research on Natural Environment Protection Based on Blockcha...

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Industrial IoT, Big Data and Supply Chain (IIoTBDSC), International Conference on

作者： Chenye Wan Taoran Fu Haochen Wang Xing Wang Junyou Luo Ziqian Wang School of Information Science and Technology Nantong University Nantong China School of Computer and Communication Hunan Institute of Engineering Xiangtan China School of Computational Science and Electronics Hunan Institute of Engineering Xiangtan China School of Robotics Hunan University Changsha China

ISBN: (数字)9798350341690

ISBN: (纸本)9798350341706

Now the Masai Mara population continues to expand, the wildlife in the reserve is facing serious threats to their survival. The purpose of this report is to establish a management strategy model for local protected areas that balances the mutual interests between local people and wildlife in ***, Masai Mara divides the protected area into three parts, planting area, protected area, and livestock area, and then conducts correlation analysis on different areas, and concludes that the reduction in the number of wild animals is closely related to the degree of population density, and the area of cultivated land and forest area is highly correlated. So a nonlinear programming model of multiple strategies is established to plan the planting area. Then establish a comprehensive evaluation model based on the entropy weight method, quantify various strategies, and use gray correlation prediction to obtain solutions. This article introduces blockchain related technologies and uses its decentralization, security and transparency to build an architecture that contributes to the actual government protection of wild animals.

关键词： Correlation Biological system modeling Wildlife Habitats Market research Data models Blockchains

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Insurance Contract for High Renewable Energy Integration

Insurance Contract for High Renewable Energy Integration

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2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2022

作者： Zhao, Dongwei Wang, Hao Huang, Jianwei Lin, Xiaojun Mit Energy Initiative Massachusetts Institute of Technology United States Monash University Department of Data Science and Artificial Intelligence Australia School of Science and Engineering The Chinese University of HongKong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society China Elmore Family School of Electrical and Computer Engineering Purdue University United States

ISBN: (数字)9781665432542

ISBN: (纸本)9781665432542

The increasing penetration of renewable energy poses significant challenges to power grid reliability. There have been increasing interests in utilizing financial tools, such as insurance, to help end-users hedge the potential risk of lost load due to renewable energy variability. With insurance, a user pays a premium fee to the utility, so that he will get compensated in case his demand is not fully satisfied. A proper insurance design needs to resolve the following two challenges: (i) users' reliability preference is private information;and (ii) the insurance design is tightly coupled with the renewable energy investment decision. To address these challenges, we adopt the contract theory to elicit users' private reliability preferences, and we study how the utility can jointly optimize the insurance contract and the planning of renewable energy. A key analytical challenge is that the joint optimization of the insurance design and the planning of renewables is non-convex. We resolve this difficulty by revealing important structural properties of the optimal solution, using the help of two benchmark problems: the no-insurance benchmark and the social-optimum benchmark. Compared with the no-insurance benchmark, we prove that the social cost and users' total energy cost are always no larger under the optimal contract. Simulation results show that the largest benefit of the insurance contract is achieved at a medium electricity-bill price together with a low type heterogeneity and a high renewable uncertainty. © 2022 IEEE.

关键词： Insurance

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Combining Scene Coordinate Regression and Absolute Pose Regression for Visual Relocalization

Combining Scene Coordinate Regression and Absolute Pose Regr...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jiahao Ruan Li He Yisheng Guan Hong Zhang School of Electromechanical Engineering Guangdong University of Technology Guangzhou China Department of Electrical and Electronic Engineering Shenzhen Key - Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen China

Visual relocalization is a fundamental problem in computer vision and robotics. Recently, regression-based methods become popular and they can be categorized into two classes: absolute pose regression and scene coordinate regression. In this work, we present a combined regression network that jointly learns scene coordinate regression and absolute pose regression for single-image visual relocalization. The proposed network composes of a feature encoder and two regression branches with uncertainty modeling. In particular, we design a deep feature conditioning module, aiming at propagating the coarse pose information in absolute pose regression to inform the predictions in scene coordinate regression. The proposed network is trained in an end-to-end fashion to learn both regression tasks. Moreover, we propose an uncertainty-driven RANSAC algorithm that incorporates the predicted scene coordinates and their uncertainties to solve the camera pose during inference. To the best of our knowledge, this work is the first to combine scene coordinate regression and pose regression in a hierarchical framework for visual relocalization. Experiments on indoor and outdoor benchmarks demonstrate the effectiveness and the superiority of the proposed method over the state-of-the-art methods.

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Tracking the Dynamic Neural Connectivity via Conjugate Gradient Optimization*

Tracking the Dynamic Neural Connectivity via Conjugate Gradi...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Mingdong Li Shuhang Chen Zhijia Zhao Yiwen Wang Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology School of Mechanical and Electrical Engineering Guangzhou University Department of Electronic and Computer Engineering The Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology

Neural connectivity describes how neuron populations coordinate and create cognitive and behavioral functions. Neural connectivity performs dynamics where its population spiking responses to stimuli or intention change over time. Brain-machine interface (BMI) provides a framework for studying dynamical neural connectivity. In BMI, point process is a powerful technique in analyzing the single neuronal tuning. And generalized linear mode (GLM) as an encoding model can incorporate the tuning in kinematics and the neural connectivity. Quantification and tracking of dynamic neural connectivity can contribute to the elucidation of the generation of brain functions in a computational way. However, most of the previous work focused on single neuronal adaptation to kinematics. When a neuron is significantly modulated by some other neurons in some tasks, the shape of the log likelihood function for single neuronal observations can be narrowed in some dimensions. And the existing gradient-based methods are not able to reach the optimum in a fast and adaptive searching way. In this work, to maximize the likelihood of observations and obtain the dynamic neural connectivity tuning parameters, we proposed a conjugate gradient-based encoding model (CGE). We illustrate CGE for likelihood function using the real experimental data under manual control and brain control. The results show that the proposed CGE has better performance in tracking the dynamic neural connectivity tuning parameters and modeling neural *** Relevance— Not directly related.

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HRI Wasn’t Built In a Day: A Call To Action For Responsible HRI Research

HRI Wasn’t Built In a Day: A Call To Action For Responsible...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Micol Spitale Rebecca Stower Maria Teresa Parreira Elmira Yadollahi Iolanda Leite Hatice Gunes Department of Computer Science and Technology University of Cambridge UK Department of Electronic Information and Bio-Engineering Politecnico di Milano Italy Division of Robotics Perception and Learning KTH Royal Institute of Technology Information Science Cornell University School of Computing and Communications Lancaster University UK

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

In recent years, the awareness of the academy around responsible research has notably increased. For instance, with advances in machine learning and artificial intelligence, recent efforts have been made to promote ethical, fair, and inclusive AI and robotics. To better understand if and to what extent HRI is incentivizing researchers to engage in responsible research, we conducted an exploratory review of the publishing guidelines for the most popular HRI conference venues. We identified 18 conferences which published at least 7 HRI papers in 2022. From these, we discuss four themes relevant to conducting responsible HRI research in line with the Responsible Research and Innovation framework: ethical and human participant considerations, transparency and reproducibility, accessibility and inclusion, and plagiarism and LLM use. We identify several gaps and room for improvement within HRI regarding responsible research. Finally, we establish a call to action to provoke conversations among HRI researchers about the importance of conducting responsible research within emerging fields like HRI.

关键词： Ethics Technological innovation Reviews Rail to rail inputs Human-robot interaction Oral communication Reproducibility of results Stakeholders Robots Guidelines

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LVOS: A Benchmark for Large-scale Long-term Video Object Segmentation

arXiv

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arXiv 2024年

作者： Hong, Lingyi Liu, Zhongying Chen, Wenchao Tan, Chenzhi Feng, Yuang Zhou, Xinyu Guo, Pinxue Li, Jinglun Chen, Zhaoyu Gao, Shuyong Zhang, Wei Zhang, Wenqiang Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China The Shanghai Engineering Research Center of AI&Robotics Academy for Engineering&Technology Fudan University Shanghai China Engineering Research Center of AI&Robotics Ministry of Education Academy for Engineering&Technology Fudan University Shanghai China The Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai China

Video object segmentation (VOS) aims to distinguish and track target objects in a video. Despite the excellent performance achieved by off-the-shell VOS models, existing VOS benchmarks mainly focus on short-term videos lasting about 5 seconds, where objects remain visible most of the time. However, these benchmarks poorly represent practical applications, and the absence of long-term datasets restricts further investigation of VOS in realistic scenarios. Thus, we propose a novel benchmark named LVOS, comprising 720 videos with 296,401 frames and 407,945 high-quality annotations. Videos in LVOS last 1.14 minutes on average, approximately 5 times longer than videos in existing datasets. Each video includes various attributes, especially challenges deriving from the wild, such as long-term reappearing and cross-temporal similar objects. Compared to previous benchmarks, our LVOS better reflects VOS models' performance in real scenarios. Based on LVOS, we evaluate 20 existing VOS models under 4 different settings and conduct a comprehensive analysis. On LVOS, these models suffer a large performance drop, highlighting the challenge of achieving precise tracking and segmentation in real-world scenarios. Attribute-based analysis indicates that key factor to accuracy decline is the increased video length, emphasizing LVOS's crucial role. We hope our LVOS can advance development of VOS in real scenes. Data and code are available at https://***/lvos. ***/. © 2024, CC BY.

关键词： Benchmarking

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SYNLOCO: Synthesizing Central Pattern Generator and Reinforcement Learning for Quadruped Locomotion

SYNLOCO: Synthesizing Central Pattern Generator and Reinforc...

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IEEE Conference on Decision and Control

作者： Xinyu Zhang Zhiyuan Xiao Qingrui Zhang Wei Pan School of Aeronautics and Astronautics Shenzhen Campus of Sun Yatsen University Shenzhen P.R. China Department of Computer Science The University of Manchester UK Department of Cognitive Robotics Delft University of Technology Netherlands

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

The Central Pattern Generator (CPG) is adept at generating rhythmic gait patterns characterized by consistent timing and adequate foot clearance. Yet, its open-loop configuration often fails to adjust the system’s control performance in response to environmental variations. On the other hand, Reinforcement Learning (RL), celebrated for its model-free properties, has gained significant traction in robotics due to its inherent adaptability and robustness. However, initiating traditional RL approaches from the ground up presents a risk of converging to suboptimal local minima and slow learning convergence. In this paper, we propose a quadruped locomotion framework-called SYNLOCO-by synthesizing CPG and RL, which can ingeniously integrate the strengths of both methods, enabling the development of a locomotion controller that is both stable and natural with partial state observations (e.g., no velocity measurements). To optimize the learning trajectory of SYNLOCO, a two-phase training strategy is presented. Both ablation analysis and experimental comparison are performed using a real quadruped robot under varied conditions, including distinct velocities, terrains, and payload capacities. The experiments showcase SYNLOCO’s efficiency in producing consistent and clear-footed gaits across diverse scenarios, despite no velocity measurements. The developed controller exhibits resilience against substantial parameter variations, underscoring its potential for robust real-world applications.

关键词： Training Reinforcement learning Robot sensing systems Generators Trajectory Timing Quadrupedal robots Velocity measurement Standards Payloads

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