Journal of Field Robotics最新文献

{"title":"SimLiquid: A Simulation-Based Liquid Perception Pipeline for Robot Liquid Manipulation","authors":"Yan Huang,&nbsp;Jiawei Zhang,&nbsp;Ran Yu,&nbsp;Shoujie Li,&nbsp;Wenbo Ding","doi":"10.1002/rob.22548","DOIUrl":"https://doi.org/10.1002/rob.22548","url":null,"abstract":"<div>\u0000 \u0000 <p>Transparent liquid volume estimation is crucial for robot manipulation tasks, such as pouring. However, estimating the volume of transparent liquids is a challenging problem. Most existing methods primarily focus on data collection in the real world, and the sensors are fixed to the robot body for liquid volume estimation. These approaches limit both the timeliness of the research process and the flexibility of perception. In this paper, we present SimLiquid20k, a high-fidelity synthetic data set for liquid volume estimation, and propose a YOLO-based multi-task network trained on fully synthetic data for estimating the volume of transparent liquids. Extensive experiments demonstrate that our method can effectively transfer from simulation to the real world. In scenarios involving changes in background, viewpoint, and container variations, our approach achieves an average error of 5% in real-world volume estimation. In addition, our work conducts two application experiments integrating with GPT-4, showcasing the potential of our method in service robotics. The accompanying videos and supporting Information are available at https://simliquid.github.io/.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 6","pages":"2908-2919"},"PeriodicalIF":5.2,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144881406","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":"Rapid Detection of Ripe Tomatoes in Unstructured Environments","authors":"Jiangtao Qi,&nbsp;Xv Cong,&nbsp;Weirong Zhang,&nbsp;Fangfang Gao,&nbsp;Bo Zhao,&nbsp;Hui Guo","doi":"10.1002/rob.22556","DOIUrl":"https://doi.org/10.1002/rob.22556","url":null,"abstract":"<div>\u0000 \u0000 <p>To achieve efficient detection of ripe tomatoes in unstructured environments, this paper proposed an improved YOLOv7 rapid detection network model for ripe tomatoes. Firstly, the original YOLOv7 backbone network's CSP-Darknet53 structure was replaced by the FasterNet network structure to enhance model detection efficiency and reduce the parameters of the model. Secondly, the Global Attention Mechanism (GAM) was introduced to improve the tomato feature expression ability with a small increase in model parameters. Next, a Diverse Branch Block (DBB) module was integrated into the ELAN module in the head structure to improve the model's inference efficiency. Finally, the batch normalization layer <i>γ</i> was selected as the parameter of the sparsity factor in the algorithm. The L₁ regularization term was used to train the original model for sparsity, and the slim pruning algorithm was used for global channel pruning to compress the model size. The pruned model was retrained through model fine-tuning to adjust the detection accuracy to near the level before pruning. The experimental results show that the improved model has a mean average precision of 96.49%, which is basically unchanged compared to the original model. However, the model parameter count, the computation, and the model size were reduced by 52.16%, 56.84%, and 36.95%, respectively, resulting in a 32.09% increase in the recognition frame rate. Compared to similar object detection models, such as SSD, YOLOv3, YOLOv4, YOLOv5s, YOLOX, and YOLOv8, the Improved-YOLOv7 model reduced the parameter by 4.44% to 89.05%, computational complexity by 30.37% to 91.18%, and model size by 26.43% to 72.16%. This paper provided technical support for the recognition of ripe tomatoes in unstructured environments.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 6","pages":"2920-2935"},"PeriodicalIF":5.2,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144881403","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":"Bioinspired Design for Soft Robot Deformation Amplification: Layout Planning, Experimental Verification, and Potential Applications","authors":"Binbin Diao,&nbsp;Xiaoxu Zhang,&nbsp;Jiangtao Di,&nbsp;Jian Xu","doi":"10.1002/rob.22558","DOIUrl":"https://doi.org/10.1002/rob.22558","url":null,"abstract":"<div>\u0000 \u0000 <p>A better capacity for moving in restricted spaces, such as pipeline inspection and post-disaster rescue, is a key point in soft locomotion robots. Therefore, the more compact design of robots attracts great attention, including the excellent deformation ratio of the robots’ structure and the integration with the actuator. However, those pose a new challenge, that is, it is difficult to coordinate the deformation ratio between the actuator and the structure. In this study, inspired by the muscle-skeleton tension structure, a novel lever-type layout of the actuator is proposed to solve this issue. Firstly, the hollow Miura-origami structure with excellent deformation ability is adopted as the skeleton of the robot. Then, theoretical and experimental results show that the deformation amplification of the actuator can be realized with the lever-type layout, i.e., the 25% deformation ratio of the SMA spring actuator can achieve about 60% deformation ratio of the Miura-origami structure. Finally, based on the equivalent dynamic model and the non-dominated sorting genetic algorithm II (NSGA-II), the operation scenario of this new layout is demonstrated through numerical simulation. The results verify the feasibility of the new design from a simulation perspective and lay the foundation for the subsequent actuation design and control of the Miura-origami earthworm-like soft robot.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 6","pages":"2936-2951"},"PeriodicalIF":5.2,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144881405","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":"Development and Field Evaluation of a Radial Large-Stroke Adaptive End-Effector for Continuous Robotic Harvesting of Banana Fruits at Different Stalk Diameters","authors":"Jie Guo,&nbsp;Zhou Yang,&nbsp;Yufei Liu,&nbsp;Xiongzhe Han,&nbsp;Zichen Huang,&nbsp;Wenkai Zhang,&nbsp;Jieli Duan,&nbsp;Yong He","doi":"10.1002/rob.22563","DOIUrl":"https://doi.org/10.1002/rob.22563","url":null,"abstract":"<div>\u0000 \u0000 <p>Currently, banana post-harvesting operations generally rely on manual labor, and the farming population is aging seriously, especially in hilly and mountain areas. To address these issues, the study on key technologies for mechanized banana de-handing based on an automatic feeding system was carried out, and the finite element analysis (FEA) and kinematic characteristic analysis on the de-handing cutters were conducted. The static analysis of de-handing cutters showed that the maximum stress is much smaller than the ultimate stress. Therefore, there will be no permanent deformation and no damages to de-handing cutters during the banana de-handing process. Based on the findings from FEA and kinematic characteristic analysis, the experiments to assess the self-adaptive profiling performance and de-handing performance were carried out by using the banana de-handing mechanism. The results of self-adapting profiling experiment showed that the actual profiling accuracies of the ring de-handing cutters on cylinders with diameters of 60 mm, 70 mm, 80 mm, and 90 mm were 80.80%, 80.99%, 80.90%, and 82.61%, respectively. The deviations from the corresponding theoretical profiling accuracies were 3.73%, 3.54%, 3.63%, and 1.92%, respectively. To evaluate the de-handing mechanism, the de-handing success rate, incision quality, and self-adaptive profiling effect were selected as indicators. From the de-handing experiments, it was found that the average de-handing success rate was 77.63%, the average grade of incision quality was 7.61, and the average grade of self-adaptive profiling effect was 7.70. The results of the simulation analysis and experimental study showed that the de-handing mechanism has a great stability and reliability and can meet the banana de-handing needs in the field. Compared with the de-handing cutters reported previously, the cutter proposed in this study has better profiling and enveloping capabilities for the diameter of the banana stalk, and for the first time, completely realizes the adaptive profiling of the entire stalk by the mechanical cutter, which has significant practical value for de-handing banana fruits from stalks of different diameters.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 6","pages":"2892-2907"},"PeriodicalIF":5.2,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144881018","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":"Design and Kinematic Modeling of Wrist-Inspired Joints for Restricted Operating Spaces","authors":"Qingxiang Wu,&nbsp;Yu'ao Wang,&nbsp;Yu Fu,&nbsp;Tong Yang,&nbsp;Yongchun Fang,&nbsp;Ning Sun","doi":"10.1002/rob.22552","DOIUrl":"https://doi.org/10.1002/rob.22552","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, a wrist-inspired joint with an integrated drive system is designed to realize pitch and yaw simultaneously. First, a wrist-inspired joint with a modular design using an integrated drive system is designed, which for the <i>first time</i> offers the flexibility of soft joints and the high rigidity of discrete joints. On the basis of this, the multilevel mapping between servos, wrist-inspired joints, and end-effectors is first analyzed. Furthermore, wrist-inspired joints are applied in manipulators and grippers. Additionally, the kinematic model of wrist-inspired joint manipulators is established based on the vector product method, and the damped least squares method is used to solve the inverse kinematics. Finally, some groups of experiments are conducted on a self-built experiment platform. Experimental results of two applications, including a manipulator and a gripper, verify the flexibility and maneuverability of designed wrist-inspired joints.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 6","pages":"2878-2891"},"PeriodicalIF":5.2,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144881017","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":"Assessment of Maneuvering Influence on the Fine Alignment of Autonomous Underwater Vehicle","authors":"Adriano Frutuoso,&nbsp;Felipe O. Silva,&nbsp;Ettore A. de Barros","doi":"10.1002/rob.22551","DOIUrl":"https://doi.org/10.1002/rob.22551","url":null,"abstract":"<div>\u0000 \u0000 <p>Autonomous underwater vehicles (AUVs) are specialized robots used to accomplish important field operations such as inspection of oil and gas pipelines, marine wildlife monitoring, imaging of river and sea beds, nondestructive testing of ship hulls, and so on. Before the start of an AUV mission, its navigation system, which is generally comprised of a doppler velocity log (DVL)/pressure sensor (PS)-aided inertial navigation system (INS) needs to be initialized. After a brief coarse stage of initialization, the AUV attitude is generally refined (as well as some inertial measurement unit (IMU)/aiding sensor systematic error parameters are corrected for) in a Kalman filter (KF)-based estimation process known as fine alignment, which is usually performed in open sea conditions. When the latter is conducted before the submerged phase of the AUV, a Global Navigation Satellite System (GNSS) receiver may provide additional aiding information to the refinement process. As the excitation of the degrees of freedom of the AUV is known to interfere with the performance of the KF fine alignment, this study exploits Baram and Kailath's concept of estimability to assess what kind of deliberate AUV maneuver is able to deliver the best estimation results. As the main contribution, we show that among the tested AUV motion profiles, the lawn mower is the maneuver that, except for the IMU/DVL misalignment around the AUV longitudinal axis, decreases the estimation uncertainties of all remaining INS/GNSS/DVL/PS fine alignment states. Results from simulated and experimental tests confirm the adequacy of the outlined verifications.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 6","pages":"2853-2877"},"PeriodicalIF":5.2,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144881082","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":"Design and Analysis of a Lightweight Redundant-Degree-of-Freedom Fruit-Picking Robot Arm","authors":"Shangshang Cheng,&nbsp;Zhengwei Yu,&nbsp;Zhen Li,&nbsp;Qingru Fan,&nbsp;Shilei Lyu,&nbsp;Wei Wen,&nbsp;Zhou Yang","doi":"10.1002/rob.22545","DOIUrl":"https://doi.org/10.1002/rob.22545","url":null,"abstract":"<div>\u0000 \u0000 <p>Labor shortages have become one of the primary challenges constraining the sustainable development of the fruit industry. The adoption of traditional multi-axis industrial-grade robotic arms for fruit picking has been limited due to issues related to efficiency and cost. This paper presents a lightweight PnP-P-R-P robotic arm that features a large workspace and an active leveling function, making it suitable for harvesting fruits such as apples and citrus. First, we establish the kinematic equations of the robotic arm and solve for the Jacobian condition number and manipulability index, showing that the workspace is free of singular points, thereby ensuring smooth operation. Next, we develop a dynamic model to analyze the performance of each joint under extreme working conditions. To adapt to practical operating environments, we simplify the forward and inverse kinematics calculations by utilizing planar spatial motion and propose a three-joint redundancy strategy for obstacle avoidance. Simulations and experimental tests reveal that the robotic arm has a vertical reach of 2.2 m and a depth of 1.3 m, with a continuous operation repeatability precision of ±5 mm when carrying a 2 kg end-effector payload. These results indicate that the robotic arm is well-suited for fruit-picking operations in both structured and unstructured orchard environments.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 6","pages":"2815-2825"},"PeriodicalIF":5.2,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144881059","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":"Kinematic Modeling of a 7-DOF Tendon-Like-Driven Robot Based on Optimization and Deep Learning","authors":"SaiXuan Chen,&nbsp;SaiHu Mu,&nbsp;GuanWu Jiang,&nbsp;Abdelaziz Omar,&nbsp;Zina Zhu,&nbsp;Fuzhou Niu","doi":"10.1002/rob.22544","DOIUrl":"https://doi.org/10.1002/rob.22544","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper proposes a novel 7-DOF tendon-like-driven redundant robot (TDR7) based on a weighted inverse kinematics (IK) optimization algorithm and a deep learning fine-tuning model. The robot features a modular design that enables highly flexible movements of the shoulder, elbow, and wrist joints. Its kinematic model is established using the Denavit-Hartenberg (D-H) parameter method. To address the complexity of solving IK for 7-DOF redundant robots, a weighted gradient projection method specialized for TDR7 (SWGPM-TDR7) is introduced. This algorithm integrates joint constraints, singularity avoidance, and minimum energy consumption into a multi-objective optimization framework, significantly improving joint motion continuity and trajectory planning efficiency while maintaining solution accuracy. To further accommodate complex trajectory planning requirements, a deep learning fine-tuning model (RWKV-TDR7) that combines recurrent networks with self-attention mechanisms is introduced. Through fine-tuning, RWKV-TDR7 achieves efficient trajectory fitting for TDR7, supports long-sequence outputs, and reduces computational complexity. Simulation and experimental validations demonstrate that the robot exhibits excellent performance in forward kinematics, inverse kinematics, and trajectory tracking in terms of accuracy, stability, and continuity. This work provides an effective solution for the design of high-performance robotic systems in medical and industrial applications.</p></div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 6","pages":"2791-2814"},"PeriodicalIF":5.2,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144881080","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 Fully Automated Robotic System for Tuning Optimization of RF Cavity Filter","authors":"Yarkin Yigit,&nbsp;Engin Afacan","doi":"10.1002/rob.22547","DOIUrl":"https://doi.org/10.1002/rob.22547","url":null,"abstract":"<p>The advancements in radar systems, electronic warfare, and telecommunication industries have generated a substantial demand for microwave filters. Among these, cavity filters have conventionally served in transmitters and receivers, facilitating the passage of desired signals in the passband while effectively rejecting harmonics and spurious signals outside the desired frequency range. Each resonator, arranged perpendicular to the cavity filter block's length with precise spacing and alignment, is meticulously tuned to the band's center frequency and bandwidth. Post-production tuning of radiofrequency (RF) filters is essential due to material and manufacturing tolerances. Traditionally, this tuning process has been performed manually. While necessary, manual tuning is time-consuming and expensive, especially for high-order filters. It further restricts precise adjustments, limits production scalability, and escalates manufacturing costs. To address these limitations, an advanced and automated approach is imperative. This study presents a robotic control architecture for cavity filter tuning, designed to leverage intelligent computer-aided tuning processes. Specifically tailored for miniaturized tuning screw filters, the system operates fully autonomously, integrating collaborative robots (COBOTs), single and multi-axis robotic arms, and a Cartesian platform. Additionally, it incorporates an image process system, force–torque sensors, and vector network analyzer (VNA) to monitor and measure relevant parameters during the tuning process. The RF tuning control algorithm, along with its subsections—the Control Algorithm of the Robotic System and the RF Tuning Algorithm—is thoroughly explained with a hierarchical main flow. All implementation processes, including the preparation for tuning and the tuning stages, are detailed. Image processing and search optimization algorithms are employed to determine all input and unknown parameters, while soft locking and thrust force vector optimization algorithms enhance tuning sensitivity. A sample cavity filter is tuned using the robotic system with real-time monitoring on a VNA, utilizing both coarse and fine-tuning algorithms. The RF performance, measurement results, and robotic iterations are presented, comparing the advantages and disadvantages of these tuning methods. The RF tuning methods and control algorithms adopt a data-driven model, which will be further developed in future work.</p>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 6","pages":"2826-2852"},"PeriodicalIF":5.2,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rob.22547","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144881081","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":"Simulation and Experimental Study on Trajectory Tracking of Tracked Unmanned Vehicle on Nonstructured Roads in the Field","authors":"Taizhi Liu,&nbsp;Kang Wu,&nbsp;Zhi Lin,&nbsp;Rulin Shen","doi":"10.1002/rob.22549","DOIUrl":"https://doi.org/10.1002/rob.22549","url":null,"abstract":"<div>\u0000 \u0000 <p>An improved model predictive control (MPC) trajectory tracking controller is proposed for the automatic driving of tracked unmanned vehicle (TUV) on the nonstructured roads in postdisaster field, and experiments and debugging are carried out in real environments. The TUV trajectory tracking controller based on the MPC algorithm is designed according to the kinematic model of the TUV. Aiming at the model uncertainty problem caused by the vehicle body sinking and track slipping during the traveling process of the TUV, a driving wheel rotation speed correction controller is proposed. The controller can effectively suppress external interference through experimental data fitting, thereby improving tracking performance, especially during curve tracking. Adaptive Kalman Filtering technology is introduced to improve the vehicle position accuracy. The model and parameters are optimized through model simulation and debugging of real vehicle experiments in the field roads. When compared with the nonlinear model predictive control (NMPC) algorithm, the improved MPC controller demonstrates significant reductions in trajectory tracking deviations. Specifically, for the three different road conditions, the maximum positional deviation is reduced by 41.21% on average, the average positional deviation is reduced by 42.95%, the maximum heading angle deviation is reduced by 27.84% on average, and the average heading angle deviation is reduced by 19.39%. These results clearly indicate that the improved MPC controller proposed in this paper outperforms the NMPC algorithm in terms of trajectory tracking effectiveness.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 6","pages":"2777-2790"},"PeriodicalIF":5.2,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144881079","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}