IET Cybersystems and Robotics最新文献_第2页

Real-World Deployment of a Dynamic Selective LASER Weeding System Using Multispectral Imagery 使用多光谱图像的动态选择性激光除草系统的实际部署

IF 1.2

IET Cybersystems and Robotics Pub Date : 2026-06-27 DOI: 10.1049/csy2.70059

Sam Wane, Mingfeng Wang, Matthew Butler, Fernando Auat Cheein

{"title":"Real-World Deployment of a Dynamic Selective LASER Weeding System Using Multispectral Imagery","authors":"Sam Wane, Mingfeng Wang, Matthew Butler, Fernando Auat Cheein","doi":"10.1049/csy2.70059","DOIUrl":"https://doi.org/10.1049/csy2.70059","url":null,"abstract":"The use of chemical treatments for weed control is increasingly challenged by weed resistance, regulatory restrictions on chemicals and the risk of soil and water contamination that can pose health hazards. Chemical weed treatments are unsustainable, prompting exploration of alternative methods such as boiling water, electrocution and directed fire. However, these approaches are limited: water-based treatments require a reliable water supply in the field, and electric or fire-based methods pose additional environmental risks. This work proposes a targeted light amplified stimulation of emission by radiation (LASER) treatment and selective spraying system integrated with automatic weed identification. The system, mounted on the rear of a tractor, utilises a bispectral imaging setup to distinguish weeds from crops. Close-to-crop weeds are automatically selected for LASER treatment, whereas a selective sprayer targets other weeds with a glyphosate globule. This integrated system approach is named ‘Hyperweeding’. The results demonstrate successful separation of row crops from weeds, achieving a contamination-free crop with a significant reduction in glyphosate usage, and effectively treating weeds at speeds of 0.1 m<math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>⋅</mo>\u0000 <msup>\u0000 <mi>s</mi>\u0000 <mrow>\u0000 <mo>−</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 </msup>\u0000 </mrow>\u0000 <annotation> $cdot {mathrm{s}}^{-1}$</annotation>\u0000 </semantics></math>.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"8 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.70059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Differentially Flat Trajectory Planning Approach for UAV Swarms With Energy Efficiency and Spatiotemporal Consistency 基于能量效率和时空一致性的无人机群差分平面轨迹规划方法

IF 1.2

IET Cybersystems and Robotics Pub Date : 2026-06-14 DOI: 10.1049/csy2.70055

Linqing He, Weifeng Liu

{"title":"A Differentially Flat Trajectory Planning Approach for UAV Swarms With Energy Efficiency and Spatiotemporal Consistency","authors":"Linqing He, Weifeng Liu","doi":"10.1049/csy2.70055","DOIUrl":"https://doi.org/10.1049/csy2.70055","url":null,"abstract":"Unmanned aerial vehicle (UAV) swarms hold significant promise for scalable environment exploration, cooperative transportation and urban air mobility. Nevertheless, trajectory planning for swarms remains challenging due to high computational complexity, stringent spatiotemporal constraints and limited attention to energy efficiency. In this work, we present a unified trajectory planning framework that simultaneously promotes energy efficiency and ensures spatiotemporal consistency. Building upon the minimum control (MINCO) trajectory representation, we extend the differentially flat parameterisation from single-UAV settings to multiagent systems, enabling efficient representation of swarm trajectories through sparse spatiotemporal parameters. Differentiable cost functions are designed to explicitly capture synchronised arrivals, temporal logic of tasks and collision-avoidance constraints, whereas analytical gradients are derived to facilitate scalable optimisation. Extensive simulations with swarms of up to 15 UAVs demonstrate the scalability of our method in generating smooth and dynamically feasible trajectories. Compared to state-of-the-art baselines, the proposed framework significantly improves the interagent safety margin (by 35%) and achieves substantial energy efficiency, reducing physical energy consumption by over 10% and control effort by up to 22%.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"8 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.70055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148282044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Climbing Motion Planning of Inchworm Robot Based on Improved Particle Swarm Optimisation Algorithm 基于改进粒子群优化算法的尺蠖机器人攀爬运动规划

IF 1.2

IET Cybersystems and Robotics Pub Date : 2026-06-12 DOI: 10.1049/csy2.70050

Xiaohong Cui, Shaoling Liu, Jiaxian Deng, Binrui Wang

{"title":"Climbing Motion Planning of Inchworm Robot Based on Improved Particle Swarm Optimisation Algorithm","authors":"Xiaohong Cui, Shaoling Liu, Jiaxian Deng, Binrui Wang","doi":"10.1049/csy2.70050","DOIUrl":"https://doi.org/10.1049/csy2.70050","url":null,"abstract":"Climbing robots have broad potential for various practical applications. In this study, a five-degree-of-freedom inchworm robotic platform is developed using modular T/I joints and its kinematic model is derived based on the Denavit–Hartenberg approach. Multiple gait modes, including creeping, rotation, flipping and obstacle negotiation, are investigated. To address the high energy consumption during the creeping gait, an optimisation framework constrained by both kinematic and dynamic factors is established. This framework adopts a deviation-tracking strategy that combines cubic polynomials in the Cartesian space with 7th-order polynomials in the joint space. Mathematical models for energy evaluation, trajectory formulation and spatial curve similarity are also developed. Additionally, an improved adaptive particle swarm optimisation algorithm is proposed, integrating three enhancements: a Sigmoid-based update rule, a position-updating scheme inspired by the golden sine algorithm and a tabu-region constraint mechanism. These modifications result in faster convergence and higher precision. Finally, a complete control system is designed, and experimental tests conducted under the creeping and rotating gaits verify the practicality and effectiveness of the proposed motion-planning method.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"8 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.70050","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148238227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 1.2

IET Cybersystems and Robotics Pub Date : 2026-05-27