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检索条件"任意字段=2024 International Conference on Intelligent Robotics and Automatic Control"

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VRSO: Visual-Centric Reconstruction for Static Object Annotation

VRSO: Visual-Centric Reconstruction for Static Object Annota...

引用

2024 international conference on intelligent Robots and Systems

作者： Yu, Chenyao Cai, Yingfeng Zh, Jiaxin Kong, Hui Sui, Wei Yang, Cong Soochow Univ Ecol & Innovat Ctr Intelligent Driving BeeLab Sch Future Sci & Engn Suzhou Peoples R China Univ Macau Fac Sci & Technol Taipa Macao Peoples R China

ISBN: (纸本)9798350377712;9798350377705

As a part of the perception results of intelligent driving systems, static object detection (SOD) in 3D space provides crucial cues for driving environment understanding. With the rapid deployment of deep neural networks for SOD tasks, the demand for high-quality training samples soars. The traditional, also reliable, way is manual labelling over the dense LiDAR point clouds and reference images. Though most public driving datasets adopt this strategy to provide SOD ground truth (GT), it is still expensive and time-consuming in practice. This paper introduces VRSO, a visual-centric approach for static object annotation. Experiments on the Waymo Open Dataset show that the mean reprojection error from VRSO annotation is only 2.6 pixels, around four times lower than the Waymo Open Dataset labels (10.6 pixels). VRSO is distinguished in low cost, high efficiency, and high quality: (1) It recovers static objects in 3D space with only camera images as input, and (2) manual annotation is barely involved since GT for SOD tasks is generated based on an automatic reconstruction and annotation pipeline.

关键词： Deep neural networks

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intelligent tracking system based on composite algorithm fusion 6

Intelligent tracking system based on composite algorithm fus...

引用

6th international conference on robotics, intelligent control and Artificial Intelligence, RICAI 2024

作者： Zhan, Jiajie Xu, Peixuan Lin, Yuying Lin, Yuannan The Higher Educational Key Laboratory for Flexible Manufacturing Equipment Integration of Fujian Province Xiamen Institute of Technology Xiamen Xiamen361021 China

ISBN: (纸本)9798331541699

In today's social rapid development of science and technology environment, for autonomy and efficiency of artificial intelligence has become very important, in order to promote the future more people for the convenience of artificial intelligence on the tracking, and with the complexity of the application scenario and variability, especially in the dynamic obstacle and unknown environment path tracking, in the autonomous tracking algorithm needs a highly flexible, fast general algorithm. At this time, the memory enhancement path optimization algorithm (memory enhancement path finding algorithm, MEPA) can provide a convenient process and idea. Compared with the traditional tracking algorithm, this algorithm is more adaptable to the environment, and the simulation experiment shows that the algorithm can reach a reuse rate of more than 70% after increasing the complexity of the environment. This greatly reduces the time consumption of repeated pathway calculations. © 2024 IEEE.

关键词： Adversarial machine learning

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Observability of Two-Time-Scale Multi-Agent Systems with Antagonistic Interactions 6

Observability of Two-Time-Scale Multi-Agent Systems with Ant...

引用

6th international conference on robotics, intelligent control and Artificial Intelligence, RICAI 2024

作者： Gu, Mengqi Li, Qingbo Zhou, Kaijie Chen, Jing Yang, Jin Huaian Key Laboratory of Millimeter-Wave Communication Technology Huaiyin Normal University Huaian223300 China College of Automation Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Provincial Key Laboratory of Intelligent Electromagnetic Sensing and Communication Huaiyin Normal University Huaian223300 China

ISBN: (纸本)9798331541699

This paper investigates the observability of two-time-scale multi-agent systems (MASs), with particular attention to antagonistic interactions among agents. The study begins by modeling the systems, followed by defining observability and establishing its conditions using singular perturbation theory. Numerical simulations are conducted to demonstrate the effectiveness of the proposed conditions. © 2024 IEEE.

关键词： Multi agent systems

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A NOA-AP based Typical Process Route automatic Discovery Approach for intelligent Manufacturing 7

A NOA-AP based Typical Process Route Automatic Discovery App...

引用

7th international conference on robotics, control and Automation Engineering, RCAE 2024

作者： Cao, Xinyu Xu, Binzi Huang, Dengchao Wang, Chun Anhui Polytechnic University School of Electrical Engineering Wuhu241000 China Huaibei Normal University School of Computer Science and Technology Huaibei235000 China

ISBN: (纸本)9798350355642

With the continuous advancement of intelligent manufacturing, the efficient extraction of reusable typical process routes based on artificial intelligence for computer-aided process planning (CAPP) has emerged as a critical necessity. Because a good process route can not only effectively improve the efficiency of process planning, but also promote the transformation of traditional manufacturing to intelligent manufacturing. To address this situation, this paper proposes a Nutcracker Optimization Algorithm (NOA) enhanced Affinity Propagation (AP) algorithm under the consideration of clustering effectiveness to automatic discover the typical process routes from the massive historical data. First, two soft constraints (i.e., quantity constraint and size constraint) are introduced simultaneously in the clustering process to ensure the quality and validity of the obtained typical process routes according to the actual demand. In addition, previous research has emphasized that the selection of preference value and damping factor in the AP algorithm significantly influences clustering outcomes. Hence, NOA is implemented to identify the optimal individual within the search space to determine suitable preference values and damping factors, thereby enhancing the clustering quality of the AP algorithm. The numerical illustration shows that the proposed NOA-AP could improve the clustering quality and discover more representative and effective typical process routes. © 2024 IEEE.

关键词： Smart manufacturing

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BEV-ODOM: Reducing Scale Drift in Monocular Visual Odometry with BEV Representation

BEV-ODOM: Reducing Scale Drift in Monocular Visual Odometry ...

引用

2024 international conference on intelligent Robots and Systems

作者： Wei, Yufei Lu, Sha Han, Fuzhang Xiong, Rong Wang, Yue Zhejiang Univ Lab Ind Control & Technol Hangzhou 310058 Peoples R China Zhejiang Univ Inst Cyber Syst & Control Hangzhou 310058 Peoples R China

ISBN: (纸本)9798350377712;9798350377705

Monocular visual odometry (MVO) is vital in autonomous navigation and robotics, providing a cost-effective and flexible motion tracking solution, but the inherent scale ambiguity in monocular setups often leads to cumulative errors over time. In this paper, we present BEV-ODOM, a novel MVO framework leveraging the Bird's Eye View (BEV) Representation to address scale drift. Unlike existing approaches, BEVODOM integrates a depth-based perspective-view (PV) to BEV encoder, a correlation feature extraction neck, and a CNNMLP-based decoder, enabling it to estimate motion across three degrees of freedom without the need for depth supervision or complex optimization techniques. Our framework reduces scale drift in long-term sequences and achieves accurate motion estimation across various datasets, including NCLT, Oxford, and KITTI. The results indicate that BEV-ODOM outperforms current MVO methods, demonstrating reduced scale drift and higher accuracy.

关键词： Motion estimation

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Application and Performance Optimization of intelligent control System in Electromechanical Equipment

Application and Performance Optimization of Intelligent Cont...

引用

2024 international conference on Telecommunications and Power Electronics, TELEPE 2024

作者： Wang, Chengtao The Testing and Technology Center for Industrial Products of Shenzhen Customs Guangdong Shenzhen518000 China

ISBN: (纸本)9798350369212

As an advanced control technology, intelligent control system is widely used in the field of mechanical and electrical equipment. This paper aims to discuss the application of intelligent control system in electromechanical equipment and its performance optimization strategy. Firstly, the basic principle and technical characteristics of intelligent control system are introduced and analyzed, including the application of advanced technologies such as deep learning and reinforcement learning in intelligent control. Secondly, aiming at the fields of automatic production equipment, smart home equipment and industrial robot system which are common in electromechanical equipment, the specific application scenarios and optimization methods of intelligent control system are discussed respectively. Then, through case analysis and empirical research, the potential and limitations of intelligent control system in improving the performance of electromechanical equipment and reducing energy consumption are verified. Finally, combined with the current research status and future development trend, the application prospect and development direction of intelligent control system in the field of mechanical and electrical equipment are prospected and discussed. The research results of this paper have important theoretical and practical significance for promoting the intelligent transformation of electromechanical equipment and industrial production. © 2024 IEEE.

关键词： Reinforcement learning

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intelligent Security Q&A System Based on Large Language Model 3

Intelligent Security Q&A System Based on Large Language Mode...

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3rd international conference on robotics, Artificial Intelligence and intelligent control (RAIIC)

作者： Zhou, Youtao Lu, Qiuhong Fan, Haoyu Xiao, Yuntao Hu, Jinwen Zhang, Shimian Univ Elect Power Sch Automat Engn Shanghai 200090 Peoples R China Shanghai HRSTEK Co Ltd Shanghai 201102 Peoples R China

ISBN: (纸本)9798350352634;9798350352627

With the continuous development of artificial intelligence technology, intelligent Q&A systems have been widely used in various fields, including hotels, airports, hospitals and other ***, traditional Q&A systems are often constrained by the limited rule base and stereotypical dialog flow, and are unable to provide a sufficiently intelligent interaction *** system in this paper utilizes Large Language Model (LLM) combined with face recognition technology to build a more intelligent and flexible security Q&A *** combining the local knowledge base with LLM, the system is able to retrieve relevant information from the local knowledge base based on the professional questions provided by the user through text vectorization and then similarity comparison, and generate corresponding responses, thus providing a more humanized and accurate *** system has the following capabilities: (1) specialized Q&A, based on LLM and self-constructed knowledge base to generate Q&A with domain-specific knowledge, compared to model fine-tuning methods, this method can deploy large vertical domain models without re-training;(2) Security welcome, this system face recognition module adopts Python+Dlib method to identify the user and conduct the welcome greeting, if the visitor is an unfamiliar user, it is not possible to conduct the Q&A with the LLM for the sensitive information, e.g., private information, etc.;if the visitor is a known user, then it is possible to communicate with the LLM in all aspects.

关键词： LLM Face recognition Q&A system text vectorization

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Safeguarding Autonomous Surface Vessels Against Cyber-Attacks on Sensor Systems 15

Safeguarding Autonomous Surface Vessels Against Cyber-Attack...

引用

15th IFAC conference on control Applications in Marine Systems, robotics and Vehicles, CAMS 2024

作者： Kuncara, Ivan Widyotriatmo, Augie Hasan, Agus Department of Mechanical Engineering Chonnam National University Gwangju Korea Republic of Instrumentation and Control Research Group Bandung Institute of Technology Bandung Indonesia Department of ICT and Natural Sciences Norwegian University of Science and Technology Alesund Norway

This paper presents a novel approach to enhance the cybersecurity of autonomous surface vessels (ASVs) by introducing a secure state estimation framework. The proposed methodology focuses on detecting and estimating the magnitude of sensor attacks through the utilization of an adaptive observer. The process involves filtering measurement signals and integrating them into the ASV's state space model. The adaptive observer is then applied to accurately estimate the magnitude of potential attacks. Simulation results illustrate the high accuracy of the proposed observer in both detecting and estimating the attack magnitude. This innovative approach contributes significantly to fortifying the resilience of ASVs against sensor threats, ultimately enhancing their reliability and security in operational scenarios. © 2024 Elsevier B.V.. All rights reserved.

关键词： Cyber attacks

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Admittance control Based Gait Intervention Strategy of Knee Exoskeleton for Stance Phase Support

Admittance Control Based Gait Intervention Strategy of Knee ...

引用

IEEE/ASME international conference on Advanced intelligent Mechatronics (AIM)

作者： Dai, Xiaolin Zhou, Zhihao Wang, Zilu Rong, Xuewen Wang, Qining Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China Univ Hlth & Rehabil Sci Qingdao 266071 Peoples R China Peking Univ Inst Artificial Intelligence Beijing 100871 Peoples R China Beijing Engn Res Ctr Intelligent Rehabil Engn Beijing 100871 Peoples R China Peking Univ Coll Engn Beijing 100871 Peoples R China Minist Edu Engn Res Ctr Intelligent Unmanned Syst Jinan 250061 Peoples R China Peking Univ Dept Adv Mfg & Robot Coll Engn Inst Artificial Intelligence Beijing 100871 Peoples R China Peking Univ Third Hosp Beijing 100191 Peoples R China Zhengzhou Univ Affiliated Hosp 5 Zhengzhou 450052 Henan Peoples R China

ISBN: (纸本)9798350355376;9798350355369

Knee exoskeletons have been utilized for gait rehabilitation in patients after total knee arthroplasty. During the early and middle stance phases of walking gaits, the knee joint activity of these patients is either absent or reduced, which is not conducive to the rehabilitation of normal gaits. Currently, most exoskeletons used for the rehabilitation of patients after TKA correct gait by pre-setting the movement trajectory of the knee joint. However, this method faces challenges in terms of human-machine interaction and safety. This paper proposes a strategy that combines admittance control during the early and middle stance phases with position control during the late stance and swing phases to improve compliance and safety between the wearer and the knee exoskeleton. The exoskeleton can provide support to the knee joint during the early and middle stance phases according to the wearer's actual movement requirements. The performance and safety of the admittance control were verified through test bench and squat-to-stand experiments, while the gait intervention strategy was validated through a downhill walking experiment.

关键词： Exoskeleton (robotics)

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Zero-Shot Transfer of a Tactile-based Continuous Force control Policy from Simulation to Robot

Zero-Shot Transfer of a Tactile-based Continuous Force Contr...

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2024 international conference on intelligent Robots and Systems

作者： Lach, Luca Haschke, Robert Tateo, Davide Peters, Jan Ritter, Helge Borras, Julia Torras, Carme CSIC UPC Inst Robbt & Informat Ind Barcelona Spain Bielefeld Univ Tech Fac Neuroinformat Grp Bielefeld Germany Tech Univ Darmstadt Comp Sci Dept Darmstadt Germany German Res Ctr AI DFKI Res Dept Syst AI Robot Learning Hessian AI Ctr Cognit Sci Kaiserslautern Germany

ISBN: (纸本)9798350377712;9798350377705

The advent of tactile sensors in robotics has sparked many ideas on how robots can leverage direct contact measurements of their environment interactions to improve manipulation tasks. An important line of research in this regard is grasp force control, which aims to manipulate objects safely by limiting the amount of force exerted on the object. While prior works have either hand-modeled their force controllers, employed model-based approaches, or not shown sim-to-real transfer, we propose a model-free deep reinforcement learning approach trained in simulation and then transferred to the robot without further fine-tuning. We, therefore, present a simulation environment that produces realistic normal forces, which we use to train continuous force control policies. A detailed evaluation shows that the learned policy performs similarly or better than a hand-crafted baseline. Ablation studies prove that the proposed inductive bias and domain randomization facilitate sim-to-real transfer. Code, models, and supplementary videos are available on https://***/view/rl-force-ctrl

关键词： Deep reinforcement learning

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