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Distributed output-feedback leader-following consensus of nonlinear multiagent systems

IF 4.8 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica

Pub Date : 2025-04-06 DOI: 10.1016/j.automatica.2025.112281

Jixing Lv , Changhong Wang , Lihua Xie

This paper addresses the leader-following consensus problem of a class of strict-feedback nonlinear multiagent systems under undirected follower networks. The leader and the followers are subject to additive input and external disturbances, respectively. A hierarchical output-feedback strategy is proposed, which can be implemented in a fully distributed manner in the sense that neither the Laplacian matrix eigenvalues nor the leader’s input bound are required. Firstly, a novel fully distributed observer is introduced to reconstruct the leader’s state and unknown input in a user-prescribed finite time, requiring only the leader’s output to be available to its neighboring followers. Utilizing the estimated information, a local observer-based output-feedback control protocol is then designed to achieve the state consensus. Subsequently, the robustness of the strategy to measurement noise is analyzed. The proposed strategy advances existing output-feedback fully distributed results in two significant aspects: (1) it is suitable for the scenarios where the leader’s state/observer information is not available to any follower and only the leader’s output can be obtained by its neighboring followers; (2) the state consensus is achieved in a user-prescribed finite time. Finally, simulation results are provided to validate the efficacy of the proposed consensus approach.

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引用次数: 0

An alignment-free secure fingerprint authentication integrated with elliptic curve signcryption scheme

IF 3.8 2区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Journal of Information Security and Applications

Pub Date : 2025-04-06 DOI: 10.1016/j.jisa.2025.104049

Jignesh Kukadiya , Mulagala Sandhya , Dilip Kumar Vallabhadas , I HHNTV Prasad , Rithvik Mooda

Fingerprint authentication is a widely used method to verify someone’s identity by analysing unique fingerprint features, such as ridges and specific points called minutiae. However, there are concerns about its vulnerability to fake fingerprints and privacy issues. Cancellable biometrics is a promising solution to tackle these concerns. It transforms fingerprint features into secure forms that cannot be reversed back to the original, even if someone gets hold of them. This paper proposes an alignment-free secure fingerprint authentication method that integrates minutiae point descriptors and Scale Invariant Feature Transform (SIFT) keypoint descriptors, enhanced with Elliptic Curve signcryption, aiming to fortify security without compromising authentication accuracy. Experimental evaluations were conducted using the Fingerprint Verification Competition (FVC) 2002 dataset, showcasing the efficacy of the proposed approach. Experimental results demonstrate a significant reduction in security risks while upholding authentication accuracy, thus affirming the effectiveness of our methodology in enhancing fingerprint authentication security.

{"title":"An alignment-free secure fingerprint authentication integrated with elliptic curve signcryption scheme","authors":"Jignesh Kukadiya , Mulagala Sandhya , Dilip Kumar Vallabhadas , I HHNTV Prasad , Rithvik Mooda","doi":"10.1016/j.jisa.2025.104049","DOIUrl":"10.1016/j.jisa.2025.104049","url":null,"abstract":"<div><div>Fingerprint authentication is a widely used method to verify someone’s identity by analysing unique fingerprint features, such as ridges and specific points called minutiae. However, there are concerns about its vulnerability to fake fingerprints and privacy issues. Cancellable biometrics is a promising solution to tackle these concerns. It transforms fingerprint features into secure forms that cannot be reversed back to the original, even if someone gets hold of them. This paper proposes an alignment-free secure fingerprint authentication method that integrates minutiae point descriptors and Scale Invariant Feature Transform (SIFT) keypoint descriptors, enhanced with Elliptic Curve signcryption, aiming to fortify security without compromising authentication accuracy. Experimental evaluations were conducted using the Fingerprint Verification Competition (FVC) 2002 dataset, showcasing the efficacy of the proposed approach. Experimental results demonstrate a significant reduction in security risks while upholding authentication accuracy, thus affirming the effectiveness of our methodology in enhancing fingerprint authentication security.</div></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"90 ","pages":"Article 104049"},"PeriodicalIF":3.8,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A numerically stable unscented transformation with optimal tuning parameters for high-dimensional systems

IF 3.3 2区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of Process Control

Pub Date : 2025-04-06 DOI: 10.1016/j.jprocont.2025.103406

H.A. Krog, J. Jäschke

This paper presents a new formulation for an unscented transformation for high-dimensional systems using the optimal tuning parameter for a symmetric random variable. The standard unscented transformation with optimal tuning parameters is known to be numerically unstable for high-dimensional systems. In this contribution, we show how to reformulate a high-dimensional (unstable) unscented transformation to a sum of one-dimensional (stable) unscented transformations. Our reformulation increases estimation accuracy since it allows for using the optimal tuning parameters. These benefits are shown theoretically and on several examples, where one example has a state dimension of

10^{5}

引用次数: 0

RDF-TDAA: Optimizing RDF indexing and querying with a trie based on Directly Addressable Arrays and a path-based strategy

IF 7.5 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Expert Systems with Applications

Pub Date : 2025-04-06 DOI: 10.1016/j.eswa.2025.127384

Yipeng Liu , Yuming Lin , Xinyong Peng , You Li , Jingwei Zhang

The rapid expansion of RDF knowledge graphs in scale and complexity poses significant challenges for optimizing storage efficiency and query performance, with existing solutions often limited by high storage costs or slow retrieval speeds. This study introduces RDF-TDAA, a novel RDF data management engine built on an advanced trie-based index that integrates Directly Addressable Arrays, Characteristic Sets, and integer sequence compression to achieve exceptional data compactness while maintaining high-speed query processing. RDF-TDAA also employs a unique path-based query planning approach, which constructs efficient execution plans based on the paths in query graphs, and integrates a worst-case optimal join algorithm to further streamline query processing. To validate our approach, we conducted extensive experiments using both synthetic and real-world datasets. The results demonstrate that RDF-TDAA surpasses leading RDF management systems in both storage efficiency and query speed. These findings underscore RDF-TDAA’s scalability and effectiveness as a robust solution for managing large-scale RDF knowledge graphs, with valuable implications for improving RDF data handling in both academic and practical applications. The code for RDF-TDAA is available at https://github.com/MKMaS-GUET/RDF-TDAA.

{"title":"RDF-TDAA: Optimizing RDF indexing and querying with a trie based on Directly Addressable Arrays and a path-based strategy","authors":"Yipeng Liu , Yuming Lin , Xinyong Peng , You Li , Jingwei Zhang","doi":"10.1016/j.eswa.2025.127384","DOIUrl":"10.1016/j.eswa.2025.127384","url":null,"abstract":"<div><div>The rapid expansion of RDF knowledge graphs in scale and complexity poses significant challenges for optimizing storage efficiency and query performance, with existing solutions often limited by high storage costs or slow retrieval speeds. This study introduces RDF-TDAA, a novel RDF data management engine built on an advanced trie-based index that integrates Directly Addressable Arrays, Characteristic Sets, and integer sequence compression to achieve exceptional data compactness while maintaining high-speed query processing. RDF-TDAA also employs a unique path-based query planning approach, which constructs efficient execution plans based on the paths in query graphs, and integrates a worst-case optimal join algorithm to further streamline query processing. To validate our approach, we conducted extensive experiments using both synthetic and real-world datasets. The results demonstrate that RDF-TDAA surpasses leading RDF management systems in both storage efficiency and query speed. These findings underscore RDF-TDAA’s scalability and effectiveness as a robust solution for managing large-scale RDF knowledge graphs, with valuable implications for improving RDF data handling in both academic and practical applications. The code for RDF-TDAA is available at <span><span>https://github.com/MKMaS-GUET/RDF-TDAA</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"279 ","pages":"Article 127384"},"PeriodicalIF":7.5,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal decorrelated score subsampling for Cox regression with massive survival data

IF 5.5 2区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Neurocomputing

Pub Date : 2025-04-05 DOI: 10.1016/j.neucom.2025.130090

Yujing Shao , Zhaohan Hou , Lei Wang , Heng Lian

This paper investigates optimal subsampling strategies for the preconceived low-dimensional parameters of main interest in the presence of the nuisance parameters for Cox regression with massive survival data. A general subsampling decorrelated score function based on the log-partial likelihood is constructed to reduce the influence of the less accurate nuisance parameter estimation with a possibly slow convergence rate. The consistency and asymptotic normality of the resultant subsample estimators are established. We derive unified optimal subsampling probabilities based on A- and L-optimality criteria. A two-step algorithm is further proposed to implement practically, and the asymptotic properties of the resultant estimators are also given. The satisfactory performance of our proposed subsample estimators is demonstrated by simulation results and an airline dataset.

引用次数: 0

Physical layer security techniques for grant-free massive Machine-Type Communications in 5G and beyond: A survey, challenges, and future directions

IF 4.4 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Networks

Pub Date : 2025-04-05 DOI: 10.1016/j.comnet.2025.111268

Uchenna P. Enwereonye, Ahmad Salehi Shahraki, Hooman Alavizadeh, A.S.M. Kayes

The future of smart cities, industrial automation, and connected vehicles is heavily reliant on advanced communication technologies. These technologies, particularly massive Machine-Type Communication (mMTC), are the backbone of the many connected devices required for these applications. Grant -free access in 5G and beyond, while enhancing transmission efficiency by eliminating the need for permission requests, also introduces significant security risks. These risks, such as unauthorised access, data interception, and interference due to the absence of centralised control, are of paramount importance. Physical layer security (PLS) techniques, with their ability to exploit the unique properties of wireless channels to bolster communication security, offer a promising solution. This paper provides a comprehensive review of PLS techniques for securing grant-free mMTC, comparing different approaches and exploring the challenges of their integration. Our findings lay the groundwork for future research and the practical implementation of advanced security solutions in grant-free mMTC, a development that will also enhance the security of advanced 5G and 6G networks.

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引用次数: 0

Proposal of a complexity model for human-robot collaboration assembly processes

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2025-04-05 DOI: 10.1016/j.rcim.2025.103026

Matteo Capponi, Riccardo Gervasi, Luca Mastrogiacomo, Fiorenzo Franceschini

Assembly complexity in manual processes has been widely addressed over the years in manufacturing-related literature. The concept of complexity indeed is linked to the cognitive and physical effort required on behalf of the human operator in completing the assembly process and is directly linked to the occurrence of process failures and inefficiencies. In the light of the introduction of novel technologies such as collaborative robotics such paradigm should be revised. This paper presents a proposal for a complexity model, i.e., “CHRC model”, for Human-Robot Collaboration assembly processes. CHRC model provides a multidimensional framework and a practical tool for analysing the complexity of collaborative assembly processes performed by humans supported by collaborative robots. In this situation, the collaboration with the robot may require an additional effort from the human operator, resulting in a more complex activity and thus more error prone. In this regard, the CHRC model integrates insights from multiple disciplines to provide an overview of collaborative assembly complexity based on four layers: product complexity, assembly complexity, interaction complexity and collaboration complexity. The conceptual foundation of the CHRC model is thoroughly detailed and supported by a review of the relevant literature. Hence, the paper uses the complexity formulation proposed by Samy and ElMaraghy as a basis to provide a quantitative approach. The model is then applied to practical case studies to demonstrate its application and illustrate how it can enhance the understanding of effective human-robot collaboration. This provides process designers with a practical tool to support design and improve collaborative assembly processes.

{"title":"Proposal of a complexity model for human-robot collaboration assembly processes","authors":"Matteo Capponi, Riccardo Gervasi, Luca Mastrogiacomo, Fiorenzo Franceschini","doi":"10.1016/j.rcim.2025.103026","DOIUrl":"10.1016/j.rcim.2025.103026","url":null,"abstract":"<div><div>Assembly complexity in manual processes has been widely addressed over the years in manufacturing-related literature. The concept of complexity indeed is linked to the cognitive and physical effort required on behalf of the human operator in completing the assembly process and is directly linked to the occurrence of process failures and inefficiencies. In the light of the introduction of novel technologies such as collaborative robotics such paradigm should be revised. This paper presents a proposal for a complexity model, i.e., “C<img>HRC model”, for Human-Robot Collaboration assembly processes. C<img>HRC model provides a multidimensional framework and a practical tool for analysing the complexity of collaborative assembly processes performed by humans supported by collaborative robots. In this situation, the collaboration with the robot may require an additional effort from the human operator, resulting in a more complex activity and thus more error prone. In this regard, the C<img>HRC model integrates insights from multiple disciplines to provide an overview of collaborative assembly complexity based on four layers: product complexity, assembly complexity, interaction complexity and collaboration complexity. The conceptual foundation of the C<img>HRC model is thoroughly detailed and supported by a review of the relevant literature. Hence, the paper uses the complexity formulation proposed by Samy and ElMaraghy as a basis to provide a quantitative approach. The model is then applied to practical case studies to demonstrate its application and illustrate how it can enhance the understanding of effective human-robot collaboration. This provides process designers with a practical tool to support design and improve collaborative assembly processes.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103026"},"PeriodicalIF":9.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Chance constrained programming for sustainable four dimensional fuzzy-rough transportation problem with rest period of drivers and time window constraints

IF 7.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Engineering Applications of Artificial Intelligence

Pub Date : 2025-04-05 DOI: 10.1016/j.engappai.2025.110648

Shivani , Deepika Rani , Gourav Gupta

The rest period of driver plays a critical role in ensuring both safety and efficiency, and hence the success rate of a transportation system. Fatigued drivers are more prone to accidents and errors, making it essential to incorporate their rest time into the transportation planning. Additionally, time window constraints, which define specific time frames for deliveries, play a significant role in the efficiency of transportation systems. Despite their importance, existing research has yet to integrate both driver’s rest period and time window constraints into transportation models. To address these gaps and improve operational performance, this study introduces a novel multi-objective, multi-item four-dimensional green transportation model that incorporates both driver’s rest period and time window constraints. Given the complexities of predicting market demand and other transportation-related parameters within specific time frames, the model’s parameters are represented as trapezoidal fuzzy-rough numbers. A new methodology, “Neutrosophic Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)”, based on neutrosophic programming, is proposed to find an optimal compromise solution. The practicality of this approach is demonstrated by solving a real-world industrial problem. A comparative analysis shows that the Neutrosophic TOPSIS method yields the most effective Pareto-optimal solution. The results reveal a reduction of 10.85 h in transportation time and 21.36 kg in carbon emissions compared to existing methods. Additionally, the findings reveal that excluding the driver’s rest period reduces transportation time by 15.9 h but increases carbon emissions by 591 kg. Lastly, the possible avenues for future research are outlined.

{"title":"Chance constrained programming for sustainable four dimensional fuzzy-rough transportation problem with rest period of drivers and time window constraints","authors":"Shivani , Deepika Rani , Gourav Gupta","doi":"10.1016/j.engappai.2025.110648","DOIUrl":"10.1016/j.engappai.2025.110648","url":null,"abstract":"<div><div>The rest period of driver plays a critical role in ensuring both safety and efficiency, and hence the success rate of a transportation system. Fatigued drivers are more prone to accidents and errors, making it essential to incorporate their rest time into the transportation planning. Additionally, time window constraints, which define specific time frames for deliveries, play a significant role in the efficiency of transportation systems. Despite their importance, existing research has yet to integrate both driver’s rest period and time window constraints into transportation models. To address these gaps and improve operational performance, this study introduces a novel multi-objective, multi-item four-dimensional green transportation model that incorporates both driver’s rest period and time window constraints. Given the complexities of predicting market demand and other transportation-related parameters within specific time frames, the model’s parameters are represented as trapezoidal fuzzy-rough numbers. A new methodology, “Neutrosophic Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)”, based on neutrosophic programming, is proposed to find an optimal compromise solution. The practicality of this approach is demonstrated by solving a real-world industrial problem. A comparative analysis shows that the Neutrosophic TOPSIS method yields the most effective Pareto-optimal solution. The results reveal a reduction of 10.85 h in transportation time and 21.36 kg in carbon emissions compared to existing methods. Additionally, the findings reveal that excluding the driver’s rest period reduces transportation time by 15.9 h but increases carbon emissions by 591 kg. Lastly, the possible avenues for future research are outlined.</div></div>","PeriodicalId":50523,"journal":{"name":"Engineering Applications of Artificial Intelligence","volume":"151 ","pages":""},"PeriodicalIF":7.5,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep reinforcement learning for optimal design of compliant mechanisms based on digitized cell structures

IF 7.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Engineering Applications of Artificial Intelligence

Pub Date : 2025-04-05 DOI: 10.1016/j.engappai.2025.110702

Yejun Choi , Yeoneung Kim , Keun Park

Metamaterial mechanisms are micro-architectured compliant structures that operate through the elastic deformation of specially designed flexible members. This study introduces an efficient design methodology for compliant metamaterial mechanisms using deep reinforcement learning (RL). In this approach, design domains are digitized into finite cells with various hinge connections, reformulating the design problem as a combinatorial optimization problem. To tackle this intricated optimization problem, we unfold the domain to transform the design problem into a Markov decision process where the deformation behaviors of the designed compliant mechanisms are computed through finite element analysis (FEA). The digitized cell structures are modeled using 1-dimensional (1D) beam elements, significantly reducing the computational load of FEA. The FEA results are utilized in the deep RL framework to optimize compliant mechanism designs based on specific functional requirements. This methodology is applied to the design of compliant gripper and door-latch mechanisms, exploring the effects of cell tiling direction and penalization strategies for disconnected hinges. The optimized designs generated by deep RL outperform human-guided designs, achieving a 56.3% improvement in rotational compliance for the gripper mechanism and a 2.7-fold improvement in linear compliance for the door-latch mechanism, compared to human-guided designs. The optimized compliant mechanisms are fabricated using additive manufacturing, and their performance as compliant mechanisms is experimentally validated. These findings highlight the potential of RL-based design optimization using digitized cell structures, demonstrating its capability to efficiently design high-performance compliant metamaterial mechanisms while maintaining computational efficiency.

{"title":"Deep reinforcement learning for optimal design of compliant mechanisms based on digitized cell structures","authors":"Yejun Choi , Yeoneung Kim , Keun Park","doi":"10.1016/j.engappai.2025.110702","DOIUrl":"10.1016/j.engappai.2025.110702","url":null,"abstract":"<div><div>Metamaterial mechanisms are micro-architectured compliant structures that operate through the elastic deformation of specially designed flexible members. This study introduces an efficient design methodology for compliant metamaterial mechanisms using deep reinforcement learning (RL). In this approach, design domains are digitized into finite cells with various hinge connections, reformulating the design problem as a combinatorial optimization problem. To tackle this intricated optimization problem, we unfold the domain to transform the design problem into a Markov decision process where the deformation behaviors of the designed compliant mechanisms are computed through finite element analysis (FEA). The digitized cell structures are modeled using 1-dimensional (1D) beam elements, significantly reducing the computational load of FEA. The FEA results are utilized in the deep RL framework to optimize compliant mechanism designs based on specific functional requirements. This methodology is applied to the design of compliant gripper and door-latch mechanisms, exploring the effects of cell tiling direction and penalization strategies for disconnected hinges. The optimized designs generated by deep RL outperform human-guided designs, achieving a 56.3% improvement in rotational compliance for the gripper mechanism and a 2.7-fold improvement in linear compliance for the door-latch mechanism, compared to human-guided designs. The optimized compliant mechanisms are fabricated using additive manufacturing, and their performance as compliant mechanisms is experimentally validated. These findings highlight the potential of RL-based design optimization using digitized cell structures, demonstrating its capability to efficiently design high-performance compliant metamaterial mechanisms while maintaining computational efficiency.</div></div>","PeriodicalId":50523,"journal":{"name":"Engineering Applications of Artificial Intelligence","volume":"151 ","pages":"Article 110702"},"PeriodicalIF":7.5,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Laser_RobMap: An open source ROS2 compatible tool for 3D mapping using a Mobile Robot and 2D LiDAR

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX

Pub Date : 2025-04-05 DOI: 10.1016/j.softx.2025.102142

Daniel D. Yanyachi, Yamir H. Anco-Agüero, German A. Echaiz, Miguel A. Esquivel, Alfredo Mamani-Saico, Pablo R. Yanyachi

We propose a tool for implementing a low-cost 3D mapping system using a vertically mounted 2D LiDAR sensor on a mobile robot, compatible with ROS2. The tool adapts to any ROS2-enabled robot that provides inertial and odometry data, with configurable parameters to optimize performance on systems with limited computational resources. Its main objective is to deliver a cost-effective 3D mapping solution for autonomous navigation using 3D SLAM. The results can be exported as 3D point clouds in PCD, LAS, and PLY formats, with an optional voxelization feature for efficient data management.

引用次数: 0

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