Robotica最新文献_第10页

Reinforcement learning-based motion control for snake robots in complex environments 基于强化学习的蛇形机器人在复杂环境中的运动控制

IF 2.7 4区计算机科学

Robotica Pub Date : 2024-02-12 DOI: 10.1017/s0263574723001613

Dong Zhang, Renjie Ju, Zhengcai Cao

引用次数: 0

IFE-net: improved feature enhancement network for weak feature target recognition in autonomous underwater vehicles IFE-网络：用于自动驾驶水下航行器弱特征目标识别的改进型特征增强网络

IF 2.7 4区计算机科学

Robotica Pub Date : 2024-02-08 DOI: 10.1017/s0263574724000195

Lei Cai, Bingyuan Zhang, Yuejun Li, Haojie Chai

{"title":"IFE-net: improved feature enhancement network for weak feature target recognition in autonomous underwater vehicles","authors":"Lei Cai, Bingyuan Zhang, Yuejun Li, Haojie Chai","doi":"10.1017/s0263574724000195","DOIUrl":"https://doi.org/10.1017/s0263574724000195","url":null,"abstract":"The recognizing underwater targets is a crucial component of autonomous underwater vehicle patrols and detection efforts. In the process of visual image recognition in real underwater environment, the spatial and semantic features of the target often appear to different degrees of loss, and the scarcity of specific types of underwater samples leads to unbalanced data on categories. This kind of problem makes the target features appear weak and seriously affects the accuracy of underwater target recognition. Traditional deep learning methods based on data and feature enhancement cannot achieve ideal recognition effect. Based on the above difficulties, this paper proposes an improved feature enhancement network for weak feature target recognition. Firstly, a multi-scale spatial and semantic feature enhancement module is constructed to extract the feature information of the extraction target accurately. Secondly, this paper solves the influence of target feature distortion on classification through multi-scale feature comparison of positive and negative samples. Finally, the Rank & Sort Loss function was used to train the depth target detection to solve the problem of recognition accuracy under highly unbalanced sample data. Experimental results show that the recognition accuracy of the proposed method is 2.28% and 3.84% higher than that of the existing algorithms in the recognition of underwater fuzzy and distorted target images, which demonstrates the effectiveness and superiority of the proposed method.","PeriodicalId":49593,"journal":{"name":"Robotica","volume":"1 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139761234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and analysis of a wall-climbing robot with passive compliant mechanisms to adapt variable curvatures walls 设计和分析带被动顺应机构的爬墙机器人，以适应不同曲率的墙壁

IF 2.7 4区计算机科学

Robotica Pub Date : 2024-02-05 DOI: 10.1017/s026357472300173x

Yifeng Song, Zhenyu Yang, Yong Chang, Hui Yuan, Song Lin

引用次数: 0

Panoramic visual system for spherical mobile robots 球形移动机器人的全景视觉系统

IF 2.7 4区计算机科学

Robotica Pub Date : 2024-02-05 DOI: 10.1017/s0263574724000043

Muhammad Affan Arif, Aibin Zhu, Han Mao, Yao Tu

{"title":"Panoramic visual system for spherical mobile robots","authors":"Muhammad Affan Arif, Aibin Zhu, Han Mao, Yao Tu","doi":"10.1017/s0263574724000043","DOIUrl":"https://doi.org/10.1017/s0263574724000043","url":null,"abstract":"Aimed at the challenges of wide-angle mobile robot visual perception for diverse field applications, we present the spherical robot visual system that uses a 360° field of view (FOV) for realizing real-time object detection. The spherical robot image acquisition system model is developed with optimal parameters, including camera spacing, camera axis angle, and the distance of the target image plane. Two 180<img data-mimesubtype=\"png\" data-type=\"\" src=\"https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20240203031027772-0638:S0263574724000043:S0263574724000043_inline1.png\">$^{circ}$</img>-wide panoramic FOVs, front and rear view, are formed using four on-board cameras. The speed of the SURF algorithm is increased for feature extraction and matching. For seamless fusion of the images, an improved fade-in and fade-out algorithm is used, which not only improves the seam quality but also improves object detection performance. The speed of the dynamic image stitching is significantly enhanced by using a cache-based sequential image fusion method. On top of the acquired panoramic wide FOVs, the YOLO algorithm is used for real-time object detection. The panoramic visual system for the spherical robot is then tested in real time, which outputs panoramic views of the scene at an average frame rate of 21.69 fps and panoramic views with object detection at an average of 15.39 fps.","PeriodicalId":49593,"journal":{"name":"Robotica","volume":"29 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139690174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and control of a compliant robotic actuator with parallel spring-damping transmission 设计和控制带平行弹簧阻尼传动的顺应式机器人致动器

IF 2.7 4区计算机科学

Robotica Pub Date : 2024-02-05 DOI: 10.1017/s0263574724000110

Peikang Yuan, Jianbin Liu, David T. Branson, Zhibin Song, Shuai Wu, Jian S. Dai, Rongjie Kang

引用次数: 0

Path planning for robots in preform weaving based on learning from demonstration 基于示范学习的预成型编织机器人路径规划

IF 2.7 4区计算机科学

Robotica Pub Date : 2024-02-01 DOI: 10.1017/s0263574724000146

Zhuo Meng, Shuo Li, Yujing Zhang, Yize Sun

{"title":"Path planning for robots in preform weaving based on learning from demonstration","authors":"Zhuo Meng, Shuo Li, Yujing Zhang, Yize Sun","doi":"10.1017/s0263574724000146","DOIUrl":"https://doi.org/10.1017/s0263574724000146","url":null,"abstract":"A collision-free path planning method is proposed based on learning from demonstration (LfD) to address the challenges of cumbersome manual teaching operations caused by complex action of yarn storage, variable mechanism positions, and limited workspace in preform weaving. First, by utilizing extreme learning machines (ELM) to autonomously learn the teaching data of yarn storage, the mapping relationship between the starting and ending points and the teaching path points is constructed to obtain the imitation path with similar storage actions under the starting and ending points of the new task. Second, an improved rapidly expanding random trees (IRRT) method with adaptive direction and step size is proposed to expand path points with high quality. Finally, taking the spatical guidance point of imitation path as the target direction of IRRT, the expansion direction is biased toward the imitation path to obtain a collision-free path that meets the action yarn storage. The results of different yarn storage examples show that the ELM-IRRT method can plan the yarn storage path within 2s–5s when the position of the mechanism changes in narrow spaces, avoiding tedious manual operations that program the robot movements, which is feasible and effective.","PeriodicalId":49593,"journal":{"name":"Robotica","volume":"4 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139657078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SLAMB&MAI: a comprehensive methodology for SLAM benchmark and map accuracy improvement SLAMB&MAI：用于 SLAM 基准和地图精度改进的综合方法

IF 2.7 4区计算机科学

Robotica Pub Date : 2024-01-30 DOI: 10.1017/s0263574724000079

Shengshu Liu, Erhui Sun, Xin Dong

{"title":"SLAMB&MAI: a comprehensive methodology for SLAM benchmark and map accuracy improvement","authors":"Shengshu Liu, Erhui Sun, Xin Dong","doi":"10.1017/s0263574724000079","DOIUrl":"https://doi.org/10.1017/s0263574724000079","url":null,"abstract":"SLAM Benchmark plays a pivotal role in the field by providing a common ground for performance evaluation. In this paper, a novel methodology of simultaneous localization and mapping benchmark and map accuracy improvement (SLAMB&MAI) is introduced. It can objectively evaluate errors of localization and mapping, and further improve map accuracy by utilizing evaluation results as feedback. The proposed benchmark transforms all elements into a global frame and measures the errors between them. The comprehensiveness consists in the benchmark of both localization and mapping, and the objectivity consists in the consideration of the correlation between localization and mapping by the preservation of the original pose relations between all reference frames. The map accuracy improvement is realized by first obtaining the optimization that minimizes the errors between the estimated trajectory and ground truth trajectory and then applying it to the estimated map. The experimental results showed that the map accuracy can be improved by an average of 15%. The optimization that yields minimal localization errors is obtained by the proposed Centre Point Registration-Iterative Closest Point (CPR-ICP). This proposed Iterative Closest Point (ICP) variant pre-aligns two point clouds by their centroids and least square planes and then uses traditional ICP to minimize the error between them. The experimental results showed that CPR-ICP outperformed traditional ICP, especially in cases involving large-scale environments. To the extent of our knowledge, this is the first work that can not only objectively benchmark both localization and mapping but also revise the estimated map and increase its accuracy, which provides insights into the acquisition of ground truth map and robot navigation.","PeriodicalId":49593,"journal":{"name":"Robotica","volume":"71 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139579207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-adaptive learning particle swarm optimization-based path planning of mobile robot using 2D Lidar environment 基于自适应学习粒子群优化的移动机器人二维激光雷达环境路径规划

IF 2.7 4区计算机科学

Robotica Pub Date : 2024-01-26 DOI: 10.1017/s0263574723001819

Julius Fusic S., Sitharthan R.

{"title":"Self-adaptive learning particle swarm optimization-based path planning of mobile robot using 2D Lidar environment","authors":"Julius Fusic S., Sitharthan R.","doi":"10.1017/s0263574723001819","DOIUrl":"https://doi.org/10.1017/s0263574723001819","url":null,"abstract":"The loading and unloading operations of smart logistic application robots depend largely on their perception system. However, there is a paucity of study on the evaluation of Lidar maps and their SLAM algorithms in complex environment navigation system. In the proposed work, the Lidar information is finetuned using binary occupancy grid approach and implemented Improved Self-Adaptive Learning Particle Swarm Optimization (ISALPSO) algorithm for path prediction. The approach makes use of 2D Lidar mapping to determine the most efficient route for a mobile robot in logistical applications. The Hector SLAM method is used in the Robot Operating System (ROS) platform to implement mobile robot real-time location and map building, which is subsequently transformed into a binary occupancy grid. To show the path navigation findings of the proposed methodologies, a navigational model has been created in the MATLAB 2D virtual environment using 2D Lidar mapping point data. The ISALPSO algorithm adapts its parameters inertia weight, acceleration coefficients, learning coefficients, mutation factor, and swarm size, based on the performance of the generated path. In comparison to the other five PSO variants, the ISALPSO algorithm has a considerably shorter path, a quick convergence rate, and requires less time to compute the distance between the locations of transporting and unloading environments, based on the simulation results that was generated and its validation using a 2D Lidar environment. The efficiency and effectiveness of path planning for mobile robots in logistic applications are validated using Quanser hardware interfaced with 2D Lidar and operated in environment 3 using proposed algorithm for production of optimal path.","PeriodicalId":49593,"journal":{"name":"Robotica","volume":"330 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139579215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design, simulation, control of a hybrid pouring robot: enhancing automation level in the foundry industry 混合浇注机器人的设计、模拟和控制：提高铸造业的自动化水平

IF 2.7 4区计算机科学

Robotica Pub Date : 2024-01-25 DOI: 10.1017/s0263574723001881

Wang Chengjun, Duan Hao, Li Long

{"title":"Design, simulation, control of a hybrid pouring robot: enhancing automation level in the foundry industry","authors":"Wang Chengjun, Duan Hao, Li Long","doi":"10.1017/s0263574723001881","DOIUrl":"https://doi.org/10.1017/s0263574723001881","url":null,"abstract":"Currently, workers in sand casting face harsh environments and the operation safety is poor. Existing pouring robots have insufficient stability and load-bearing capacity and cannot perform intelligent pouring according to the demand of pouring process. In this paper, a hybrid pouring robot is proposed to solve these limitations, and a vision-based hardware-in-the-loop (HIL) control technology is designed to achieve the real-time control problems of simulated pouring and pouring process. Firstly, based on the pouring mechanism and the motion demand of ladle, a hybrid pouring robot with a 2UPR-2RPU parallel mechanism as the main body is designed. And the equivalent hybrid kinematic model was established by using Eulerian method and differential motion. Subsequently, a motion control strategy based on HIL simulation technique was designed and presented. The working space of the robot was obtained through simulation experiments to meet the usage requirements. And the stability of the robot was tested through the key motion parameters of the robot joints. Based on the analysis of pouring quality and trajectory, optimal dynamic parameters for the experimental prototype are obtained through water simulation experiments, the pouring liquid height area is 35–40 cm, the average flow rate of pouring liquid is 112 cm3/s, and the ladle tilting speed is 0.0182 rad/s. Experimental results validate the reasonableness of the designed pouring robot structure. Its control system realizes the coordinated movement of each branch chain to complete the pouring tasks with different variable parameters. Consequently, the designed pouring robot will significantly enhance the automation level of the casting industry.","PeriodicalId":49593,"journal":{"name":"Robotica","volume":"12 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139560837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An improved fuzzy inference strategy using reinforcement learning for trajectory-tracking of a mobile robot under a varying slip ratio 利用强化学习改进模糊推理策略，用于移动机器人在不同滑移率下的轨迹跟踪

IF 2.7 4区计算机科学

Robotica Pub Date : 2024-01-25 DOI: 10.1017/s0263574724000134

Muhammad Qomaruz Zaman, Hsiu-Ming Wu

{"title":"An improved fuzzy inference strategy using reinforcement learning for trajectory-tracking of a mobile robot under a varying slip ratio","authors":"Muhammad Qomaruz Zaman, Hsiu-Ming Wu","doi":"10.1017/s0263574724000134","DOIUrl":"https://doi.org/10.1017/s0263574724000134","url":null,"abstract":"In this study, a fuzzy reinforcement learning control (FRLC) is proposed to achieve trajectory tracking of a differential drive mobile robot (DDMR). The proposed FRLC approach designs fuzzy membership functions to fuzzify the relative position and heading between the current position and a prescribed trajectory. Instead of fuzzy inference rules, the relationship between the fuzzy inputs and actuator voltage outputs is built using a reinforcement learning (RL) agent. Herein, the deep deterministic policy gradient (DDPG) methodology consisted of actor and critic neural networks is employed in the RL agent. Simulations are conducted with considering varying slip ratio disturbances, different initial positions, and two different trajectories in the testing environment. In the meantime, a comparison with the classical DDPG model is presented. The results show that the proposed FRLC is capable of successfully tracking different trajectories under varying slip ratio disturbances as well as having performance superiority to the classical DDPG model. Moreover, experimental results validate that the proposed FRLC is also applicable to real mobile robots.","PeriodicalId":49593,"journal":{"name":"Robotica","volume":"14 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139560839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0