The cover image is based on the Article Unearthing the history with A-RHex: Leveraging articulated hexapod robots for archeological pre-exploration by Qi Shao et al., https://doi.org/10.1002/rob.22410
{"title":"Back Cover, Volume 42, Number 1, January 2025","authors":"Qi Shao, Qixing Xia, Zhonghan Lin, Xuguang Dong, Xin An, Haoqi Zhao, Zhangyi Li, Xin-Jun Liu, Wenqiang Dong, Huichan Zhao","doi":"10.1002/rob.22497","DOIUrl":"https://doi.org/10.1002/rob.22497","url":null,"abstract":"<p>The cover image is based on the Article <i>Unearthing the history with A-RHex: Leveraging articulated hexapod robots for archeological pre-exploration</i> by Qi Shao et al., https://doi.org/10.1002/rob.22410\u0000 \u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 1","pages":"ii"},"PeriodicalIF":4.2,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rob.22497","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
The cover image is based on the Article From muscular to dexterous: A systematic review to understand the robotic taxonomy in construction and effectiveness by Yifan Gao et al., https://doi.org/10.1002/rob.22409
{"title":"Cover Image, Volume 42, Number 1, January 2025","authors":"Yifan Gao, Jiangpeng Shu, Zhe Xia, Yaozhi Luo","doi":"10.1002/rob.22496","DOIUrl":"https://doi.org/10.1002/rob.22496","url":null,"abstract":"<p>The cover image is based on the Article <i>From muscular to dexterous: A systematic review to understand the robotic taxonomy in construction and effectiveness</i> by Yifan Gao et al., https://doi.org/10.1002/rob.22409\u0000 \u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 1","pages":"i"},"PeriodicalIF":4.2,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rob.22496","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
The cover image is based on the Article Three-dimensional kinematics-based real-time localization method using two robots by Guy Elmakis et al., https://doi.org/10.1002/rob.22383
{"title":"Cover Image, Volume 41, Number 8, December 2024","authors":"Guy Elmakis, Matan Coronel, David Zarrouk","doi":"10.1002/rob.22467","DOIUrl":"https://doi.org/10.1002/rob.22467","url":null,"abstract":"<p>The cover image is based on the Article <i>Three-dimensional kinematics-based real-time localization method using two robots</i> by Guy Elmakis et al., https://doi.org/10.1002/rob.22383\u0000 \u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"41 8","pages":"i"},"PeriodicalIF":4.2,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rob.22467","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142588084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
Nicolas Baumann, Edoardo Ghignone, Jonas Kühne, Niklas Bastuck, Jonathan Becker, Nadine Imholz, Tobias Kränzlin, Tian Yi Lim, Michael Lötscher, Luca Schwarzenbach, Luca Tognoni, Christian Vogt, Andrea Carron, Michele Magno
Autonomous racing in robotics combines high‐speed dynamics with the necessity for reliability and real‐time decision‐making. While such racing pushes software and hardware to their limits, many existing full‐system solutions necessitate complex, custom hardware and software, and usually focus on Time‐TrIals rather than full unrestricted Head‐to‐head racing, due to financial and safety constraints. This limits their reproducibility, making advancements and replication feasible mostly for well‐resourced laboratories with comprehensive expertise in mechanical, electrical, and robotics fields. Researchers interested in the autonomy domain but with only partial experience in one of these fields, need to spend significant time with familiarization and integration. The ForzaETH Race Stack addresses this gap by providing an autonomous racing software platform designed for F1TENTH, a 1:10 scaled Head‐to‐Head autonomous racing competition, which simplifies replication by using commercial off‐the‐shelf hardware. This approach enhances the competitive aspect of autonomous racing and provides an accessible platform for research and development in the field. The ForzaETH Race Stack is designed with modularity and operational ease of use in mind, allowing customization and adaptability to various environmental conditions, such as track friction and layout, which is exemplified by the various modularly implemented state estimation and control systems. Capable of handling both Time‐Trials and Head‐to‐Head racing, the stack has demonstrated its effectiveness, robustness, and adaptability in the field by winning the official F1TENTH international competition multiple times. Furthermore, the stack demonstrated its reliability and performance at unprecedented scales, up to over on tracks up to 150 m in length.
{"title":"ForzaETH Race Stack—Scaled Autonomous Head‐to‐Head Racing on Fully Commercial Off‐the‐Shelf Hardware","authors":"Nicolas Baumann, Edoardo Ghignone, Jonas Kühne, Niklas Bastuck, Jonathan Becker, Nadine Imholz, Tobias Kränzlin, Tian Yi Lim, Michael Lötscher, Luca Schwarzenbach, Luca Tognoni, Christian Vogt, Andrea Carron, Michele Magno","doi":"10.1002/rob.22429","DOIUrl":"https://doi.org/10.1002/rob.22429","url":null,"abstract":"Autonomous racing in robotics combines high‐speed dynamics with the necessity for reliability and real‐time decision‐making. While such racing pushes software and hardware to their limits, many existing full‐system solutions necessitate complex, custom hardware and software, and usually focus on Time‐TrIals rather than full unrestricted Head‐to‐head racing, due to financial and safety constraints. This limits their reproducibility, making advancements and replication feasible mostly for well‐resourced laboratories with comprehensive expertise in mechanical, electrical, and robotics fields. Researchers interested in the autonomy domain but with only partial experience in one of these fields, need to spend significant time with familiarization and integration. The ForzaETH Race Stack addresses this gap by providing an autonomous racing software platform designed for F1TENTH, a 1:10 scaled Head‐to‐Head autonomous racing competition, which simplifies replication by using commercial off‐the‐shelf hardware. This approach enhances the competitive aspect of autonomous racing and provides an accessible platform for research and development in the field. The ForzaETH Race Stack is designed with modularity and operational ease of use in mind, allowing customization and adaptability to various environmental conditions, such as track friction and layout, which is exemplified by the various modularly implemented state estimation and control systems. Capable of handling both Time‐Trials and Head‐to‐Head racing, the stack has demonstrated its effectiveness, robustness, and adaptability in the field by winning the official F1TENTH international competition multiple times. Furthermore, the stack demonstrated its reliability and performance at unprecedented scales, up to over on tracks up to 150 m in length.","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"2 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254401","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}
Wang Shuai, Wang Huimin, Zhang Haoyan, Mao Yiwei, Fan Jiaxin
The six‐crawler driving mechanism plays a crucial role in the operation of large machines such as bucket‐wheel excavators, dumping machines, and mobile crushing stations, as it serves functions like bearing, movement and steering. The driving characteristics of this mechanism directly influence the safety and efficiency of these machinery systems. To enhance the design methodology for multi‐crawler machinery, improve path controllability, and achieve adaptive driving, a satellite navigation control system for six‐crawler machinery was developed based on the principles of real‐time kinematic (RTK) satellite positioning. This system utilizes the distance deviation and heading angle deviation between the actual path and the predetermined path of the six‐crawler machinery as inputs to a fuzzy proportion integration differentiation (fuzzy PID) controller. This controller regulates the deviation angle of the steering crawler and the driving speeds of each track, thereby ensuring precise path tracking control. To evaluate the path tracking control performance under both straight and curved driving conditions, a virtual prototype model of the six‐crawler mechanical system was established, and co‐simulation analysis was conducted. In addition, an experimental platform for path tracking control of six‐crawler machinery was established to validate the efficacy of the satellite navigation system. The actual tracking data obtained from various driving conditions and initial deviations demonstrated that the RTK satellite navigation path tracking control system exhibited excellent control performance.
{"title":"Research on Satellite Navigation Control of Six‐Crawler Machinery Based on Fuzzy PID Algorithm","authors":"Wang Shuai, Wang Huimin, Zhang Haoyan, Mao Yiwei, Fan Jiaxin","doi":"10.1002/rob.22434","DOIUrl":"https://doi.org/10.1002/rob.22434","url":null,"abstract":"The six‐crawler driving mechanism plays a crucial role in the operation of large machines such as bucket‐wheel excavators, dumping machines, and mobile crushing stations, as it serves functions like bearing, movement and steering. The driving characteristics of this mechanism directly influence the safety and efficiency of these machinery systems. To enhance the design methodology for multi‐crawler machinery, improve path controllability, and achieve adaptive driving, a satellite navigation control system for six‐crawler machinery was developed based on the principles of real‐time kinematic (RTK) satellite positioning. This system utilizes the distance deviation and heading angle deviation between the actual path and the predetermined path of the six‐crawler machinery as inputs to a fuzzy proportion integration differentiation (fuzzy PID) controller. This controller regulates the deviation angle of the steering crawler and the driving speeds of each track, thereby ensuring precise path tracking control. To evaluate the path tracking control performance under both straight and curved driving conditions, a virtual prototype model of the six‐crawler mechanical system was established, and co‐simulation analysis was conducted. In addition, an experimental platform for path tracking control of six‐crawler machinery was established to validate the efficacy of the satellite navigation system. The actual tracking data obtained from various driving conditions and initial deviations demonstrated that the RTK satellite navigation path tracking control system exhibited excellent control performance.","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"4 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178545","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}
Xinyang Mu, Long He, Paul Heinemann, James Schupp, Manoj Karkee, Minghui Zhu
Blossom thinning is one of the key steps in apple crop load management that improves the quality of apples, reduces stress on the trees, and avoids the likelihood of biennial bearing. Conventional chemical blossom thinning such as air‐blast spraying can lead to excessive use of chemical thinner to ensure full coverage, which can also cause leaf damage fruit russeting. In addition, a well‐trained operator is required to use these chemical spraying systems. To address these challenges, a UGV‐based precision spraying system was developed for automated and targeted chemical blossom thinning for apples. The system is capable of automatically driving along the tree row in the orchard environment during blooming stage, locating apple flower clusters to be thinned using a real‐time machine vision system, and precisely spraying the chemical thinner to the targeted flower clusters. A set of field tests were conducted to evaluate the performance of the UGV‐based target spraying system by comparing it to a conventional air‐blast sprayer (ABS) and a previous prototype named the cartesian target sprayer (CTS). Tests showed that the flower cluster detection reached a precision of 93.8%. The UGV‐based spraying system used 2.2 L of chemical thinner to finish the chemical thinning for 30 apple trees, followed by the ABS and CTS with 4.2 and 2.4 L usage, respectively. The robotic system also obtained an average fruit set of 2.2 per cluster after thinning, which was comparable to that with the air blast sprayer. The findings indicated that the robotic thinning system demonstrated a 66.7% reduction in chemical usage compared to the ABS and exhibited a 43.0% faster operational pace than the CTS, while attaining a comparable fruit set per cluster. The outcomes of the study provided guidance for developing a full scale robotic chemical thinning system for modern apple orchards.
{"title":"UGV‐Based Precision Spraying System for Chemical Apple Blossom Thinning on Trellis Trained Canopies","authors":"Xinyang Mu, Long He, Paul Heinemann, James Schupp, Manoj Karkee, Minghui Zhu","doi":"10.1002/rob.22435","DOIUrl":"https://doi.org/10.1002/rob.22435","url":null,"abstract":"Blossom thinning is one of the key steps in apple crop load management that improves the quality of apples, reduces stress on the trees, and avoids the likelihood of biennial bearing. Conventional chemical blossom thinning such as air‐blast spraying can lead to excessive use of chemical thinner to ensure full coverage, which can also cause leaf damage fruit russeting. In addition, a well‐trained operator is required to use these chemical spraying systems. To address these challenges, a UGV‐based precision spraying system was developed for automated and targeted chemical blossom thinning for apples. The system is capable of automatically driving along the tree row in the orchard environment during blooming stage, locating apple flower clusters to be thinned using a real‐time machine vision system, and precisely spraying the chemical thinner to the targeted flower clusters. A set of field tests were conducted to evaluate the performance of the UGV‐based target spraying system by comparing it to a conventional air‐blast sprayer (ABS) and a previous prototype named the cartesian target sprayer (CTS). Tests showed that the flower cluster detection reached a precision of 93.8%. The UGV‐based spraying system used 2.2 L of chemical thinner to finish the chemical thinning for 30 apple trees, followed by the ABS and CTS with 4.2 and 2.4 L usage, respectively. The robotic system also obtained an average fruit set of 2.2 per cluster after thinning, which was comparable to that with the air blast sprayer. The findings indicated that the robotic thinning system demonstrated a 66.7% reduction in chemical usage compared to the ABS and exhibited a 43.0% faster operational pace than the CTS, while attaining a comparable fruit set per cluster. The outcomes of the study provided guidance for developing a full scale robotic chemical thinning system for modern apple orchards.","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"5 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223576","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}
Crewed lunar vehicles (CLVs) significantly enhance astronauts’ exploration range and efficiency on the moon, paving the way for more comprehensive scientific research. Utilizing computer simulations offers an effective alternative to conducting experiments in low‐gravity conditions if backed up by appropriate model validation. This study introduces a detailed simulation framework CLVSim (Crewed Lunar Vehicle Simulation), including subsystems of smoothed particle hydrodynamics (SPH) soft terrain, suspensions, motors, wheels, fenders, and driver. A high‐fidelity instance of CLVSim was modeled and benchmarked based on the Lunar Roving Vehicle (LRV) from the “Apollo” program. Each subsystem was independently modeled and benchmarked based on the information from the Apollo handbook. These subsystems were then integrated to benchmark the overall operation of the CLV with experiment in a simulated lunar environment, with a mean relative error of 8.6%. The mean relative error between simulation and experiment for all subsystems and overall CLV test was less than 10%. Further applications of CLVSim were investigated. For instance, two fender designs were investigated to evaluate their effectiveness in mitigating dust emission from wheels. The vehicles’ performances were examined with four different configurations: a standard CLV on flat terrain, and CLVs with two types of suspension stiffness and torque coordination strategy driveline on rugged terrain. Comparing the maneuverability of CLVs with passive and differential drive to those with stiffer suspensions, there were approximately 9% and 7% savings in steering, respectively. The high fidelity and potential for advanced research of the simulation framework were demonstrated in areas like CLV mechanism design, dust prevention and control strategy design.
{"title":"CLVSim: A comprehensive framework for crewed lunar vehicle simulation—Modeling and applications","authors":"Qingning Lan, Liang Ding, Huaiguang Yang, Lutz Richter, Zhengyin Wang, Haibo Gao, Zongquan Deng","doi":"10.1002/rob.22421","DOIUrl":"https://doi.org/10.1002/rob.22421","url":null,"abstract":"Crewed lunar vehicles (CLVs) significantly enhance astronauts’ exploration range and efficiency on the moon, paving the way for more comprehensive scientific research. Utilizing computer simulations offers an effective alternative to conducting experiments in low‐gravity conditions if backed up by appropriate model validation. This study introduces a detailed simulation framework CLVSim (Crewed Lunar Vehicle Simulation), including subsystems of smoothed particle hydrodynamics (SPH) soft terrain, suspensions, motors, wheels, fenders, and driver. A high‐fidelity instance of CLVSim was modeled and benchmarked based on the Lunar Roving Vehicle (LRV) from the “Apollo” program. Each subsystem was independently modeled and benchmarked based on the information from the Apollo handbook. These subsystems were then integrated to benchmark the overall operation of the CLV with experiment in a simulated lunar environment, with a mean relative error of 8.6%. The mean relative error between simulation and experiment for all subsystems and overall CLV test was less than 10%. Further applications of CLVSim were investigated. For instance, two fender designs were investigated to evaluate their effectiveness in mitigating dust emission from wheels. The vehicles’ performances were examined with four different configurations: a standard CLV on flat terrain, and CLVs with two types of suspension stiffness and torque coordination strategy driveline on rugged terrain. Comparing the maneuverability of CLVs with passive and differential drive to those with stiffer suspensions, there were approximately 9% and 7% savings in steering, respectively. The high fidelity and potential for advanced research of the simulation framework were demonstrated in areas like CLV mechanism design, dust prevention and control strategy design.","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"11 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178547","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}
Underwater object detection serves as a crucial means for autonomous underwater vehicles (AUVs) to gain awareness of their surroundings. Currently, AUVs predominantly depend on underwater optical cameras or sonar sensing techniques to furnish vital information sources for subsequent tasks such as underwater rescue and mining exploration. However, the influence of underwater light attenuation or significant background noise often leads to the failure of either the acoustic or optical sensor. Consequently, the traditional single‐modal object detection network, which relies exclusively on either the optical or acoustic modality, struggles to adapt to the varying complexities of underwater environments. To address this challenge, this paper proposes a novel underwater acoustic‐optical fusion‐based underwater multi‐modal object detection paradigm termed UAMFDet, which fuses highly misaligned acoustic‐optical features in the spatial dimension at both the fine‐grained level and the instance level. First, we propose a multi‐modal deformable self‐aligned feature fusion module to adaptively capture feature dependencies between multi‐modal targets, and perform self‐aligned multi‐modal fine‐grained feature fusion by differential fusion. Then a multi‐modal instance‐level feature matching network is designed. It matches multi‐modal instance features by a lightweight cross‐attention mechanism and performs differential fusion to achieve instance‐level feature fusion. In addition, we establish a data set dedicated to underwater acoustic‐optical fusion object detection tasks called UAOF, and conduct a large number of experiments on the UAOF data set to verify the effectiveness of UAMFDet.
{"title":"UAMFDet: Acoustic‐Optical Fusion for Underwater Multi‐Modal Object Detection","authors":"Haojie Chen, Zhuo Wang, Hongde Qin, Xiaokai Mu","doi":"10.1002/rob.22432","DOIUrl":"https://doi.org/10.1002/rob.22432","url":null,"abstract":"Underwater object detection serves as a crucial means for autonomous underwater vehicles (AUVs) to gain awareness of their surroundings. Currently, AUVs predominantly depend on underwater optical cameras or sonar sensing techniques to furnish vital information sources for subsequent tasks such as underwater rescue and mining exploration. However, the influence of underwater light attenuation or significant background noise often leads to the failure of either the acoustic or optical sensor. Consequently, the traditional single‐modal object detection network, which relies exclusively on either the optical or acoustic modality, struggles to adapt to the varying complexities of underwater environments. To address this challenge, this paper proposes a novel underwater acoustic‐optical fusion‐based underwater multi‐modal object detection paradigm termed UAMFDet, which fuses highly misaligned acoustic‐optical features in the spatial dimension at both the fine‐grained level and the instance level. First, we propose a multi‐modal deformable self‐aligned feature fusion module to adaptively capture feature dependencies between multi‐modal targets, and perform self‐aligned multi‐modal fine‐grained feature fusion by differential fusion. Then a multi‐modal instance‐level feature matching network is designed. It matches multi‐modal instance features by a lightweight cross‐attention mechanism and performs differential fusion to achieve instance‐level feature fusion. In addition, we establish a data set dedicated to underwater acoustic‐optical fusion object detection tasks called UAOF, and conduct a large number of experiments on the UAOF data set to verify the effectiveness of UAMFDet.","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"15 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178548","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}
In robotics, navigating a humanoid robot through a cluttered environment is challenging. The present study aims to enhance the footstep and determine optimal paths regarding the robot's route length. The objective function for navigation of multiple humanoid robots is presented to optimize the route length and travel time. A hybrid technique using a probabilistic roadmap (PRM) and firefly algorithm (FA) is presented for humanoid robot navigation in a cluttered environment with static and dynamic obstacles. Sensory information, such as barrier range in the left, right, and front directions, is fed into the PRM framework that allows the humanoid robot to walk steadily with an initial steering angle. It finds the shortest path using the Bellman–Ford algorithm. The FA technique is used for efficient guidance and footstep modification in a cluttered environment to find a smooth and optimized path. To avoid static obstacles, the suggested hybrid technique provides optimum steering angles and ensures the minimum route length by taking the output of PRM as its input. A 3D simulator and a real‐world environment have been used for simulation and experiment in a cluttered environment utilizing the developed model and standalone methods. The humanoid robot achieves the target in all scenarios, but the FA‐tuned PRM technique is advantageous to this purpose, as shown by the convergence curve, route length, and travel duration. Multiple humanoid robot navigation has an additional self‐collision issue, which is eliminated by employing a dining philosopher controller as the base technique. In addition, the proposed controller is evaluated in contrast to the existing technique. The developed strategy ensures effectiveness and efficacy depending on these findings.
在机器人学中，引导仿人机器人通过杂乱的环境是一项挑战。本研究旨在增强机器人的脚步能力，并确定与机器人路线长度相关的最佳路径。研究提出了多个仿人机器人导航的目标函数，以优化路径长度和行进时间。本文提出了一种使用概率路线图（PRM）和萤火虫算法（FA）的混合技术，用于仿人机器人在有静态和动态障碍物的杂乱环境中的导航。感知信息，如左前方、右前方和前方的障碍物范围，被输入到 PRM 框架中，使仿人机器人以初始转向角稳定行走。它利用贝尔曼-福特算法找到最短路径。FA 技术用于在杂乱的环境中进行有效的引导和脚步修正，以找到一条平滑的优化路径。为了避开静态障碍物，建议的混合技术提供了最佳转向角度，并通过将 PRM 的输出作为其输入来确保最小路径长度。利用所开发的模型和独立方法，在杂乱环境中使用三维模拟器和真实环境进行了模拟和实验。从收敛曲线、路线长度和行进时间来看，仿人机器人在所有情况下都能实现目标，但经过 FA 调整的 PRM 技术在实现目标方面更具优势。多重仿人机器人导航还有一个自碰撞问题，而采用餐饮哲学家控制器作为基础技术可以消除这个问题。此外，还对所提出的控制器与现有技术进行了对比评估。根据这些研究结果，所开发的策略确保了有效性和效能。
{"title":"Multi‐Objective Route Outlining and Collision Avoidance of Multiple Humanoid Robots in a Cluttered Environment","authors":"Abhishek Kumar Kashyap, Dayal R. Parhi","doi":"10.1002/rob.22428","DOIUrl":"https://doi.org/10.1002/rob.22428","url":null,"abstract":"In robotics, navigating a humanoid robot through a cluttered environment is challenging. The present study aims to enhance the footstep and determine optimal paths regarding the robot's route length. The objective function for navigation of multiple humanoid robots is presented to optimize the route length and travel time. A hybrid technique using a probabilistic roadmap (PRM) and firefly algorithm (FA) is presented for humanoid robot navigation in a cluttered environment with static and dynamic obstacles. Sensory information, such as barrier range in the left, right, and front directions, is fed into the PRM framework that allows the humanoid robot to walk steadily with an initial steering angle. It finds the shortest path using the Bellman–Ford algorithm. The FA technique is used for efficient guidance and footstep modification in a cluttered environment to find a smooth and optimized path. To avoid static obstacles, the suggested hybrid technique provides optimum steering angles and ensures the minimum route length by taking the output of PRM as its input. A 3D simulator and a real‐world environment have been used for simulation and experiment in a cluttered environment utilizing the developed model and standalone methods. The humanoid robot achieves the target in all scenarios, but the FA‐tuned PRM technique is advantageous to this purpose, as shown by the convergence curve, route length, and travel duration. Multiple humanoid robot navigation has an additional self‐collision issue, which is eliminated by employing a dining philosopher controller as the base technique. In addition, the proposed controller is evaluated in contrast to the existing technique. The developed strategy ensures effectiveness and efficacy depending on these findings.","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"13 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178546","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}
To address the problem of difficulty in removing marine biofouling due to the variable curvature of the ship wall, this study proposed a marine biofouling removal wall‐climbing robot equipped with an adaptive variable curvature wall cleaning module. The robot includes a mobile module, a cleaning module, and a magnetic module. The cleaning module uses push shovel cleaning technology to scrape away marine biofouling. It adopts a rigid‐flexible coupling mechanism design and can passively adapt to ship walls with different curvatures. A barnacle stress model was established, and the front angle of the push shovel was selected to be 60° through numerical simulation. On this basis, a robot adsorption failure model was established, and the minimum magnetic force required by the robot when the safety factor was 1.5 was obtained to be 1084 N. Based on the structure size of the robot, Ansys was used to conduct a comparative analysis on the adsorption efficiency of four Halbach Array magnetic circuit structures and determined that the magnetic force generated by the five‐magnetic circuit structure is relatively higher. Based on this, the structural dimensions of the magnetic module were designed, and the effects of air gap and wall thickness on magnetic force were analyzed. It was found that when the wall thickness exceeds 6 mm, the impact on magnetic force is small, and the air gap should be set within 10 mm. A robot prototype was built, and its performance was tested. The experimental results show that the robot has good motion performance; it can reach about 5 m underwater and move stably, and has good waterproof performance; when the robot moves circumferentially on the wall, the cleaning module can adapt to surfaces with a curvature of 3 m or more, and has good surface self‐adaptation ability; it is effective in removing marine biofouling.
{"title":"Design and Analysis of a Push Shovel‐Type Hull‐Cleaning Wall‐Climbing Robot","authors":"Pei Yang, Jidong Jia, Lingyu Sun, Minglu Zhang, Delong Lv","doi":"10.1002/rob.22430","DOIUrl":"https://doi.org/10.1002/rob.22430","url":null,"abstract":"To address the problem of difficulty in removing marine biofouling due to the variable curvature of the ship wall, this study proposed a marine biofouling removal wall‐climbing robot equipped with an adaptive variable curvature wall cleaning module. The robot includes a mobile module, a cleaning module, and a magnetic module. The cleaning module uses push shovel cleaning technology to scrape away marine biofouling. It adopts a rigid‐flexible coupling mechanism design and can passively adapt to ship walls with different curvatures. A barnacle stress model was established, and the front angle of the push shovel was selected to be 60° through numerical simulation. On this basis, a robot adsorption failure model was established, and the minimum magnetic force required by the robot when the safety factor was 1.5 was obtained to be 1084 N. Based on the structure size of the robot, Ansys was used to conduct a comparative analysis on the adsorption efficiency of four Halbach Array magnetic circuit structures and determined that the magnetic force generated by the five‐magnetic circuit structure is relatively higher. Based on this, the structural dimensions of the magnetic module were designed, and the effects of air gap and wall thickness on magnetic force were analyzed. It was found that when the wall thickness exceeds 6 mm, the impact on magnetic force is small, and the air gap should be set within 10 mm. A robot prototype was built, and its performance was tested. The experimental results show that the robot has good motion performance; it can reach about 5 m underwater and move stably, and has good waterproof performance; when the robot moves circumferentially on the wall, the cleaning module can adapt to surfaces with a curvature of 3 m or more, and has good surface self‐adaptation ability; it is effective in removing marine biofouling.","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"10 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178550","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}
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