Journal of Field Robotics最新文献

{"title":"Control Method of Upper Limb Rehabilitation Exoskeleton for Better Assistance: A Comprehensive Review","authors":"Wendong Wang,&nbsp;Huizhao Ren,&nbsp;Zelin Ci,&nbsp;Xiaoqing Yuan,&nbsp;Peng Zhang,&nbsp;Chenyang Wang","doi":"10.1002/rob.22455","DOIUrl":"https://doi.org/10.1002/rob.22455","url":null,"abstract":"<div>\u0000 \u0000 <p>The upper limb rehabilitation exoskeleton is a robotic-arm-like device that fits the human upper limb and assists in movement, having the potential to be widely used in medical practice. The control method of the upper limb rehabilitation exoskeleton system is an important factor that affects the effectiveness of its rehabilitation training assistance and is also the focus of research in this field. In this article, we divide the control method of the upper limb rehabilitation exoskeleton into two levels, the high-level control mode (including passive mode, active mode, and ANN, etc.) and the low-level controller. The design of the controller aims to meet the requirements of the control mode but faces difficulties such as complex dynamic models of the system, unknown external disturbances, and motion intention recognition to achieve accurate motion trajectory tracking and flexible human–robot interaction. Based on relevant literature in the field of upper limb rehabilitation exoskeleton control methods in recent years, we analyze the rehabilitation training control modes that researchers aim to achieve, as well as the work they have done in controller design to achieve these control modes. We also propose potential research directions for achieving better exoskeleton-assisted training effects.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 4","pages":"1373-1387"},"PeriodicalIF":4.2,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950318","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}

{"title":"Autonomous Positioning for Mobile Vehicles Based on Visual-Inertial Fusion in Challenging Dark Roadway Scenes","authors":"Yuming Cui,&nbsp;Jiajun Pu,&nbsp;Ningning Hu,&nbsp;Yongbo Guo,&nbsp;Yanxun Zhou,&nbsp;Songyong Liu","doi":"10.1002/rob.22454","DOIUrl":"https://doi.org/10.1002/rob.22454","url":null,"abstract":"<div>\u0000 \u0000 <p>Accurate positioning for autonomous driven underground mining vehicles (UMVs) and coal mine robots (CMRs) is indeed one of the cores in the intelligentization of coal mining. Completely different from positioning on the ground and in parking scenes, there will be great difficulties in realizing the accurate active positioning for UMVs shuttled in dark and narrow roadways. We propose an effective visual and inertial fusion positioning method for autonomous CMRs and roadheaders in challenging roadway scenarios based on the odometer-aided inertial navigation system and visual pose estimation system. Velocity information of the odometer is adapted to restrain the error accumulation of inertial positioning based on a Kalman filter. The hybrid visual feature detection algorithm is put forward to improve the accuracy and robustness of visual observation information in a dark environment. Autonomous experiments for CMRs and roadheaders are separately performed in the narrow roadway and dark passageway to demonstrate the applicability of our localization method. The proposed approach outperforms the subsystems and existing methods in accuracy and has outstanding stability.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 4","pages":"1333-1343"},"PeriodicalIF":4.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950231","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}

{"title":"A Machine Learning–Based Ergonomic Assessment of Wireless Hand Control System for Lower-Limb Disabled Tractor Operators and Abled Female Agricultural Workers","authors":"Smrutilipi Hota,&nbsp;V. K. Tewari","doi":"10.1002/rob.22458","DOIUrl":"https://doi.org/10.1002/rob.22458","url":null,"abstract":"<div>\u0000 \u0000 <p>Tractor being the most used power source for agricultural operations needs hand control (HC) and foot control (FC) to maneuver it. FCs restrict lower-limb disabled agricultural workers from participating in tractor operation, and high requirement of actuation forces to operate FCs may create overexertion and early fatigue to female agricultural workers. Therefore, a sensor-based HC system has been developed to assist them in tractor operation with minimal actuating force. This study focuses on ergonomic assessment of the HC system to assess the suitability for the abled and disabled agricultural workers, including physiological, psychophysical, and muscle fatigue parameters. Heart rate (HR) of abled male and female, and disabled male and female was observed in the range of 83–118, 85–117, 93–118, and 92–114 beats/min, respectively, during tractor operation. Energy expenditure rate (EER) during tractor operation with FCs (9.7–17.4 kJ/min) was observed higher than with the HC system (7.3–16.5 kJ/min). Body parts discomfort was observed highest for the right hand of all the subjects (4.9–5.3) and maximum overall discomfort was experienced by abled females during the operation with FCs (5.4) as they have to exert higher force. The root mean square (RMS) value of the electromyography signal obtained for extensor digitorum muscle was found to be higher for all the subjects and with both HC and FC (abled male, 17.37–40.43 µV; abled female, 14.76–45.29 µV; disabled male, 15.49–40.23 µV; disabled female, 30.32–54.29 µV) than other upper arm muscles middle deltoid, flexor carpi radialis, and brachioradialis. Muscle workload for all the selected muscles of all the subjects was observed within the recommended limit during the tractor operation with a developed HC system (&lt; 30%). Categorization of overall discomfort rating (ODR) of the subjects using HR, EER, and RMS through machine learning algorithms such as <i>k</i>-nearest neighbor (KNN), random forest classifier, and support vector machine predicted the ODR with accuracies in the range of 77%–83%. KNN algorithm was found to be most accurate with prediction accuracy of 83%. The developed HC system provides assistantship to the lower-limb disabled agricultural workers (1%–100% disability of lower limbs) and allows female workers to operate the tractor with minimal physical exertion.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 4","pages":"1344-1360"},"PeriodicalIF":4.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950232","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}

{"title":"Performance-Oriented Understanding and Design of a Robotic Tadpole: Lower Energy Cost, Higher Speed","authors":"Xu Chao,&nbsp;Imran Hameed,&nbsp;David Navarro-Alarcon,&nbsp;Xingjian Jing","doi":"10.1002/rob.22452","DOIUrl":"https://doi.org/10.1002/rob.22452","url":null,"abstract":"<div>\u0000 \u0000 <p>A compliant plate driven by an active joint is frequently employed as a fin to improve swimming efficiency due to its continuous and compliant kinematics. However, very few studies have focused on the performance-oriented design of multijoint mechanisms enhanced with flexible fins, particularly regarding critical design factors such as the active-joint ratio and dimension-related stiffness distribution of the fin. To this aim, we developed a robotic tadpole by integrating a multijoint mechanism with a flexible fin and conduct a comprehensive investigation of its swimming performance with different tail configurations. A dynamic model with identified hydrodynamic parameters was established to predict propulsive performance. Numerous simulations and experiments were conducted to explore the impact of the active-joint ratio and the dimension-related stiffness distribution of the fin. The results reveal that (a) tails with different active-joint ratios achieve their best performance at a small phase difference, while tails with a larger active-joint ratio tend to perform worse than those with a smaller active-joint ratio when a larger phase difference is used; (b) the optimal active-joint ratio enables the robot to achieve superior performance in terms of swimming velocity and energy efficiency; and (c) with the same surface area, a longer fin with a wide leading edge and a narrow trailing edge can achieve higher swimming speeds with lower energy consumption. This work presents novel and in-depth insights into the design of bio-inspired underwater robots with compliant propulsion mechanisms.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 3","pages":"607-624"},"PeriodicalIF":4.2,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826720","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}

{"title":"Model Reference-Based Neural Controller for Transmission Line Inspection Robot","authors":"Zehra Karagöz,&nbsp;Nazmi Ekren,&nbsp;Uğur Demir,&nbsp;Ahmet Fevzi Baba,&nbsp;Mustafa Şahin","doi":"10.1002/rob.22448","DOIUrl":"https://doi.org/10.1002/rob.22448","url":null,"abstract":"<p>The regular inspection of the power transmission lines is essential for the uninterrupted transmission of electrical energy to demand points. This quickly requires actions with economically, efficiently, and safely. Therefore, the transmission line inspection robots are inevitable solution as an alternative to existing line inspection methods. This study present design and control of a transmission line inspection robot (I-Robot). Since the I-Robot exhibits nonlinear behavior and has multiple inputs and multiple outputs, a model reference-based neural controller is determined to achieve nonlinear control. The robot design process consists of four stages which are kinematic modelling, dynamic modelling, actuator modelling and controller design. To meet inspection requirements, the conceptual design of the I-Robot is performed, and the kinematic model are calculated in terms of the transformation matrices. According to the design requirements and system constraints, the dynamic model of the I-Robot is created. To provide desired motions and trajectory tracking, the actuator models are determined. Then, the I-Robot is prototyped. According to the dynamics of joint, robot and constraints, the system identification is performed to create reference model. During the system identification, the logged data are used the train the reference model. Finally, the desired trajectory for the driving cycles is created by manual excitation of the I-Robot. During the manual excitation, the logged data are used to train the neural network (NN)-based controller. Eventually, the I-Robot is assessed under the test scenarios in term of the trajectory tracking performance as regression value and mean squared errors. According to the experiments, the neuron numbers and the training algorithm of the NN controller are determined. It was observed that the controller is quickly optimized with the adapting algorithm designed for the NN reference model. As a result, the performance of the model reference-based neural controller was determined as 99%.</p>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 4","pages":"1314-1332"},"PeriodicalIF":4.2,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rob.22448","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950272","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}

{"title":"Utilizing Photovoltaic Solar Panels for Real-Time Localization and Speed Detection of Approaching Illuminated Objects in Humanoid Robots","authors":"Amir R. Ali,&nbsp;Abdelhameed Mubarak","doi":"10.1002/rob.22449","DOIUrl":"https://doi.org/10.1002/rob.22449","url":null,"abstract":"<div>\u0000 \u0000 <p>In the field of humanoid robotics, this paper showcases a promising method of integrating the photovoltaic (PV) solar panels into the “GUCnoid 1.0” humanoid robot model. Instead of the conventional power generation, solar cells are used to supply electrical energy to various sensors to create a system capable of real-time sensing and perception. The main focus of the study will be the use of PV panels as receptors that are capable of detecting the light, enabling an adaptive system which perceives environmental changes. The behavior of the PV cell is superbly studied when various light sources are approached or depart. They finally reveal unique patterns in the voltage output signal amplitude. Interestingly, these patterns figure out the same symmetric structure, which reflects on a vertical axis by their mirroring. Using this simplicity, the method involves using an artificial neural network that is able to distinguish the light sources coming towards the detector and the ones running away and the rate at which they approach/recede. Outdoor experiment was organized for verification of methods. GUCnoid 1.0— humanoid robot was placed in front of a moving vehicle with different speeds of approach. To be able to identify the vehicle's position and velocity, a PV sensing technique has to be applied. This innovative technology will have wide applications, with much attention paid to improving the speed of finding nearby objects or vehicles in the scenarios where quick detection is a serious life safety issue. Through the process of PV solar panels' smart sensing, we directly connect the areas of high-tech robotics and renewable energy. This discovery creates an opportunity for companies to build more responsive and flexible humanoid robots that can effectively collaborate with humans to achieve greater outcomes through more secure and efficient interactions between humans and robots.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 4","pages":"1298-1313"},"PeriodicalIF":4.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950557","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}

{"title":"Robot Grasping Detection Method Based on Keypoints","authors":"Song Yan,&nbsp;Lei Zhang","doi":"10.1002/rob.22447","DOIUrl":"https://doi.org/10.1002/rob.22447","url":null,"abstract":"<div>\u0000 \u0000 <p>This study introduces a novel keypoint-based grasp detection network, denoted as GKSCConv-Net, which operates on n-channel input images. The network architecture comprises three SCConv2D layers and three SCConvT2D layers. The SCConvT2D layers facilitate upsampling to maintain consistent dimensions between the output and input images. The resultant output consists of maps indicating left grasp points, right grasp points, and grasp center keypoints. The accuracy of predictions is enhanced through the incorporation of the keypoint refinement module and feature fusion module. To validate the model's generalization and applicability, comprehensive training, testing, and evaluation are conducted on diverse data sets, including the Cornell data set, Jacquard data set, and others representing real-world scenarios. Furthermore, ablation experiments are employed to substantiate the efficacy of the spatial reconstruction unit (SRU) and channel reconstruction unit (CRU) within the SCConv, exploring their impact on grasp keypoint detection outcomes. Real robotic grasping experiments ultimately affirm the model's outstanding performance in practical settings.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 4","pages":"1271-1286"},"PeriodicalIF":4.2,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950180","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}

{"title":"Enhancing Maneuverability in a Variable Wheelbase Wheeled Mobile Robot Through Dynamic Steering Curvature Control","authors":"Huanan Qi,&nbsp;Xinyu Li,&nbsp;Liang Ding,&nbsp;Qiannan Cheng,&nbsp;Haibo Gao,&nbsp;Zdravko Terze,&nbsp;Zongquan Deng","doi":"10.1002/rob.22437","DOIUrl":"https://doi.org/10.1002/rob.22437","url":null,"abstract":"<div>\u0000 \u0000 <p>Variable wheelbase wheeled mobile robot (VW-WMR) is capable of maneuvering flexibly and traversing on rough and soil terrains within confined spaces. While the steering radius of the robot model can be robustly changed by the variable wheelbase length, a challenge is posed in accurately tracking a predefined trajectory through the alteration of wheelbase length. A dynamic steering curvature (DSC) control method is proposed in this work to overcome this challenge, which is achieved by two different approaches utilizing the variable wheelbase length and manipulating drifting motions. First, to enable flexible trajectory adjustments, a 3D Ackermann kinematics model, incorporating the lifting motion of the robot box, is developed to control steering curvature by the changes in wheelbase length. Second, to achieve flexible movement for the inner and outer curves of the originally planned curvilinear trajectory, Ackermann drift models are presented by the establishment of two sequence instantaneous centers. Furthermore, the control performance of DSC is validated through simulation experiments on the ROSTDyn Vortex platform, using a six-wheeled VW-WMR named HIT-MRII robot. The effectiveness of DSC for strategically altering the robot's motion trajectory is demonstrated by the results, which show the relation between the changed trajectory position and the variation in wheelbase length, and the variation in the radii of the instantaneous centers (ICs) in the Ackermann drift model, respectively. In addition, the high maneuverability of the robot using the Ackermann model is proven by physical experiments during steering motions on soil terrain. A comprehensive advantage is demonstrated by the results via Ackermann models, which include shorter runtimes, moderate travel distances, and moderate variations in force on the wheels, compared to different velocity, crabbing motion, and equivalent bicycle models.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 4","pages":"1244-1270"},"PeriodicalIF":4.2,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949742","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}

{"title":"Four-Wheeled Mobile Robot With Flexible Posture Control","authors":"Tianxiang Lan,&nbsp;Guotian Yang","doi":"10.1002/rob.22450","DOIUrl":"https://doi.org/10.1002/rob.22450","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper presents a novel wheeled robot with adaptive suspensions to maintain a stable body posture when driving uneven roads. Each robot suspension is driven by a brushless geared motor, eliminating the traditional mechanical shock absorber. We design a virtual spring-damping system using force control to solve the problem of uneven support and high-frequency oscillation on four wheels. Subsequently, we incorporated a flexible posture control that uses the chassis posture as feedback and linearized the control to improve the dynamic response. Finally, the prototype is experimented on a simulated road and verified that the prototype and the proposed control algorithm can realize the expected requirements.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 4","pages":"1287-1297"},"PeriodicalIF":4.2,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950181","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}

{"title":"In-Pipe Maintenance Robot Using Spray-In-Place Pipe Technique for Long-Distance and Complex Pipe Environment","authors":"Colin Pak Yu Chan,&nbsp;Zijia Qu,&nbsp;Kin Hei Shiu,&nbsp;Chun Ho So,&nbsp;Keng Huat Koh,&nbsp;Musthafa Farhan,&nbsp;Chun Yiu Ho,&nbsp;Tsz Hei Wong,&nbsp;King Wai Chiu Lai","doi":"10.1002/rob.22440","DOIUrl":"https://doi.org/10.1002/rob.22440","url":null,"abstract":"<div>\u0000 \u0000 <p>Conventional pipe rehabilitation technologies are not the most sustainable solution for the utility industry because of various drawbacks, such as time consumption, disturbance to operations, society, and traffic, and the production of waste material. However, aged underground metal pipes are affected by natural forces. Trenchless rehabilitation technologies have been introduced for the treatment and renovation of aged pipes to ensure that utilities are safe and durable from an economic perspective. This paper proposes a portable and automatic robotic solution for a trenchless spray-in-place pipe approach for small underground pipelines. This approach shortens the duration of the rehabilitation operation from approximately a week to &lt; 5 h. The robot delivered and monitored a protective well-mixed urethane coating with plural components accurately using rotary mixing and spraying with a low-pressure and safer configuration (&lt; 0.8 MPa). The robot exhibited superior capacities in complicated pipe environments for turning into 90° elbows and 6-in. (150 mm), 8-in. (200 mm), and 10-in. (250 mm) pipelines. An automated robot was deployed and rehabilitated at various underground and on-ground pipe sites. The spray performance was validated using tensile tests. This robot can be applied to any pipeline system and can be developed for other in-pipe robotic construction and renovation approaches.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 4","pages":"1226-1243"},"PeriodicalIF":4.2,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950093","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}