Pub Date : 2024-11-19DOI: 10.1016/j.robot.2024.104861
Rodrigo Bernardo , João M.C. Sousa , Paulo J.S. Gonçalves
Several frameworks for robot control platforms have been developed in recent years. However, strategies that incorporate automatic replanning have to be explored, which is a requirement for Autonomous Robotic Systems (ARS) to be widely adopted. Ontologies can play an essential role by providing a structured representation of knowledge. This paper proposes a new framework capable of replanning high-level tasks in failure situations for ARSs. The framework utilizes an ontology-based reasoning engine to overcome constraints and execute tasks through Behavior Trees (BTs). The proposed framework was implemented and validated in a real experimental environment using an Autonomous Mobile Robot (AMR) sharing a plan with a human operator. The proposed framework uses semantic reasoning in the planning system, offering a promising solution to improve the adaptability and efficiency of ARSs.
{"title":"Ontological framework for high-level task replanning for autonomous robotic systems","authors":"Rodrigo Bernardo , João M.C. Sousa , Paulo J.S. Gonçalves","doi":"10.1016/j.robot.2024.104861","DOIUrl":"10.1016/j.robot.2024.104861","url":null,"abstract":"<div><div>Several frameworks for robot control platforms have been developed in recent years. However, strategies that incorporate automatic replanning have to be explored, which is a requirement for <em>Autonomous Robotic Systems</em> (ARS) to be widely adopted. Ontologies can play an essential role by providing a structured representation of knowledge. This paper proposes a new framework capable of replanning high-level tasks in failure situations for ARSs. The framework utilizes an ontology-based reasoning engine to overcome constraints and execute tasks through Behavior Trees (BTs). The proposed framework was implemented and validated in a real experimental environment using an <em>Autonomous Mobile Robot</em> (AMR) sharing a plan with a human operator. The proposed framework uses semantic reasoning in the planning system, offering a promising solution to improve the adaptability and efficiency of ARSs.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"184 ","pages":"Article 104861"},"PeriodicalIF":4.3,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702830","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}
Pub Date : 2024-11-16DOI: 10.1016/j.robot.2024.104858
Marek Retinger, Jacek Michalski, Piotr Kozierski
The paper presents and discusses the usability of a lightweight alternative to the spherical markers used in the motion capture systems. The flat marker is an approach that can allow a significant reduction in weight with only a minor negative impact on the tracking capabilities. The low weight of the markers is particularly desirable in the case of micro flying robots with payload capacity limited to a few grams. The document takes a look at the retro reflective material advantages in the case of micro flying robots. For testing purposes, over 30 different widely available products were selected and compared. The experiments were performed on both 2D and 3D surfaces, including static and dynamic objects and different scenarios. The paper includes a comparison of the materials tested and their usability as flat markers. The results showed that in the case of the best material found, the total weight of the markers can be reduced to less than one gram while ensuring continuous tracking for up to 99.7% of the test time. The research is valuable not only to people working with micro flying robots, but also to those looking for customisable and lighter replacement marker materials for the constructing of 2D or 3D markers.
{"title":"Flat marker: Reducing the weight of motion capture markers for micro flying robots","authors":"Marek Retinger, Jacek Michalski, Piotr Kozierski","doi":"10.1016/j.robot.2024.104858","DOIUrl":"10.1016/j.robot.2024.104858","url":null,"abstract":"<div><div>The paper presents and discusses the usability of a lightweight alternative to the spherical markers used in the motion capture systems. The flat marker is an approach that can allow a significant reduction in weight with only a minor negative impact on the tracking capabilities. The low weight of the markers is particularly desirable in the case of micro flying robots with payload capacity limited to a few grams. The document takes a look at the retro reflective material advantages in the case of micro flying robots. For testing purposes, over 30 different widely available products were selected and compared. The experiments were performed on both 2D and 3D surfaces, including static and dynamic objects and different scenarios. The paper includes a comparison of the materials tested and their usability as flat markers. The results showed that in the case of the best material found, the total weight of the markers can be reduced to less than one gram while ensuring continuous tracking for up to 99.7% of the test time. The research is valuable not only to people working with micro flying robots, but also to those looking for customisable and lighter replacement marker materials for the constructing of 2D or 3D markers.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"184 ","pages":"Article 104858"},"PeriodicalIF":4.3,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702687","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}
Pub Date : 2024-11-16DOI: 10.1016/j.robot.2024.104863
R.J. van der Kruk , B.H.T. Bindels , H.P.J. Bruyninckx , M.J.G. van de Molengraft
This paper introduces a new control method for suctioned products in robotic pick-and-place applications with the aim of significantly reducing the peel-off force and overshooting. A controlled cart-pendulum-mass model approximates the complex dynamics of the robot with the attached load. A design procedure is outlined based on the relationship between relative dynamic placement inaccuracy and the ratio of vibration time to move time. An algorithm is outlined for the implementation of the design method. This procedure enables the determination of the highest acceleration value that maintains accuracy within the desired range. This paper builds on previously published conference work (van der Kruk et al., 2023), incorporating a self-adjusting method, a specialised gripper, validation for significant mass variations, a frequency domain analysis and experimental results using chicken fillets handling. A passive rotational single degree of freedom is incorporated into a standard bellow vacuum gripper to minimise the torque applied to the end effector alongside input shaping. The accelerations allowed in the end effector are increased. Robustness against peel-off at higher accelerations is improved while leveraging the advantages of swing-free controls. Automatic tuning of the control parameters is achieved through a background subtraction method that measures the tracking errors in the joint motion controllers. The effectiveness of the proposed method is validated through a practical use case involving chicken fillet packaging with a fast industrial delta robot. This is a weight and pick-up spread case test. All fillets in the industrial use-case weight distribution range can be consistently picked and handled using the same constant parameters without experiencing peel-off. The Zero Vibration input shaper demonstrates the best overall performance for realistic variations (such as weight and pick-up pose), well within 10% of the variations of the natural frequency.
本文介绍了在机器人拾放应用中对吸入式产品的一种新控制方法，旨在显著降低剥离力和超程。一个受控的小车-摆-质量模型近似了机器人与附加负载的复杂动力学。根据相对动态放置误差与振动时间与移动时间之比之间的关系，概述了设计程序。概述了设计方法的实施算法。该程序能够确定最高加速度值，从而将精度保持在所需范围内。本文以之前发表的会议工作（van der Kruk 等人，2023 年）为基础，结合了自调整方法、专用夹具、重大质量变化验证、频域分析以及使用鸡排处理的实验结果。在标准波纹管真空机械手中加入了一个被动旋转单自由度，以最大限度地减少输入塑形时施加到末端效应器上的扭矩。末端效应器允许的加速度增加了。在利用无摆动控制优势的同时，提高了在更高加速度下防止剥离的稳定性。通过测量关节运动控制器的跟踪误差的背景减法实现了控制参数的自动调整。通过使用快速工业三角洲机器人进行鸡排包装的实际案例，验证了所提方法的有效性。这是一个重量和拾取传播案例测试。使用相同的恒定参数，可持续拾取和处理工业用例重量分布范围内的所有鸡排，而不会出现剥离现象。零振动输入插齿机在实际变化（如重量和拾取姿势）中表现出最佳的整体性能，其固有频率变化在 10%以内。
{"title":"Automatic control for swing-free control of suctioned products in robotic pick-and-place operations","authors":"R.J. van der Kruk , B.H.T. Bindels , H.P.J. Bruyninckx , M.J.G. van de Molengraft","doi":"10.1016/j.robot.2024.104863","DOIUrl":"10.1016/j.robot.2024.104863","url":null,"abstract":"<div><div>This paper introduces a new control method for suctioned products in robotic pick-and-place applications with the aim of significantly reducing the peel-off force and overshooting. A controlled cart-pendulum-mass model approximates the complex dynamics of the robot with the attached load. A design procedure is outlined based on the relationship between relative dynamic placement inaccuracy and the ratio of vibration time to move time. An algorithm is outlined for the implementation of the design method. This procedure enables the determination of the highest acceleration value that maintains accuracy within the desired range. This paper builds on previously published conference work (van der Kruk et al., 2023), incorporating a self-adjusting method, a specialised gripper, validation for significant mass variations, a frequency domain analysis and experimental results using chicken fillets handling. A passive rotational single degree of freedom is incorporated into a standard bellow vacuum gripper to minimise the torque applied to the end effector alongside input shaping. The accelerations allowed in the end effector are increased. Robustness against peel-off at higher accelerations is improved while leveraging the advantages of swing-free controls. Automatic tuning of the control parameters is achieved through a background subtraction method that measures the tracking errors in the joint motion controllers. The effectiveness of the proposed method is validated through a practical use case involving chicken fillet packaging with a fast industrial delta robot. This is a weight and pick-up spread case test. All fillets in the industrial use-case weight distribution range can be consistently picked and handled using the same constant parameters without experiencing peel-off. The Zero Vibration input shaper demonstrates the best overall performance for realistic variations (such as weight and pick-up pose), well within 10% of the variations of the natural frequency.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"184 ","pages":"Article 104863"},"PeriodicalIF":4.3,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702834","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}
Pub Date : 2024-11-13DOI: 10.1016/j.robot.2024.104859
Jesus Guerrero , Ahmed Chemori , Vincent Creuze , Jorge Torres
This paper proposes a new observation-based proportional–derivative control method for robust trajectory tracking of autonomous underwater vehicles (AUVs). The proposed control scheme is designed based on a new observation-based nonlinear model that captures the dynamics and uncertainties of the AUV’s behavior. The proposed control method is formulated in such a way that it can handle system nonlinearities and uncertainties, making it robust to external disturbances and model uncertainties. The effectiveness of the proposed control method is demonstrated through extensive real-time experiments in a real-world AUV trajectory tracking scenario. The obtained results show that the proposed control method outperforms other control methods in the literature regarding trajectory tracking accuracy, robustness, and disturbance rejection. Overall, the proposed observation-based proportional–derivative control method can significantly improve the trajectory tracking performance of AUVs in real-world applications.
{"title":"Robust super-twisting-based disturbance observer for autonomous underwater vehicles: Design, stability analysis, and real-time experiments","authors":"Jesus Guerrero , Ahmed Chemori , Vincent Creuze , Jorge Torres","doi":"10.1016/j.robot.2024.104859","DOIUrl":"10.1016/j.robot.2024.104859","url":null,"abstract":"<div><div>This paper proposes a new observation-based proportional–derivative control method for robust trajectory tracking of autonomous underwater vehicles (AUVs). The proposed control scheme is designed based on a new observation-based nonlinear model that captures the dynamics and uncertainties of the AUV’s behavior. The proposed control method is formulated in such a way that it can handle system nonlinearities and uncertainties, making it robust to external disturbances and model uncertainties. The effectiveness of the proposed control method is demonstrated through extensive real-time experiments in a real-world AUV trajectory tracking scenario. The obtained results show that the proposed control method outperforms other control methods in the literature regarding trajectory tracking accuracy, robustness, and disturbance rejection. Overall, the proposed observation-based proportional–derivative control method can significantly improve the trajectory tracking performance of AUVs in real-world applications.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"184 ","pages":"Article 104859"},"PeriodicalIF":4.3,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702686","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}
Pub Date : 2024-11-09DOI: 10.1016/j.robot.2024.104832
Yurou Chen , Jiyang Yu , Zhenyang Lin , Liancheng Shen , Zhiyong Liu
Achieving precise robotic assembly is paramount for safety and performance in industrial settings. Conventional assembly methods require tedious manual adjustment of many parameters, and it is challenging to meet the assembly requirements with tight clearance. Robot learning has been at the forefront of research, showing potential for automation and intelligence in robotic operations. However, intricate information such as force feedback is indispensable for high-precision robot assembly tasks, and current learning methods grapple with processing this complex observation data due to discontinuous force changes during operation and the inherent noise from the force sensor. To enhance learning efficiency amidst challenging observations, this paper proposes introducing the concept of latent causal factors that drive sensor observations and hold paramount significance in assembly tasks. This paper analyses the impact of discontinuous and noisy observations and offers two ways to infer causal factors. Based on the implied latent factors, we propose a method that learns high-precision assembly policies from interacting with the environment. The algorithm’s performance is evaluated in simulated and real-world nut insertion environments, demonstrating significant improvements over the previous methods. This research also underscores the promise of causal inference in addressing industrial challenges.
{"title":"Learning latent causal factors from the intricate sensor feedback of contact-rich robotic assembly tasks","authors":"Yurou Chen , Jiyang Yu , Zhenyang Lin , Liancheng Shen , Zhiyong Liu","doi":"10.1016/j.robot.2024.104832","DOIUrl":"10.1016/j.robot.2024.104832","url":null,"abstract":"<div><div>Achieving precise robotic assembly is paramount for safety and performance in industrial settings. Conventional assembly methods require tedious manual adjustment of many parameters, and it is challenging to meet the assembly requirements with tight clearance. Robot learning has been at the forefront of research, showing potential for automation and intelligence in robotic operations. However, intricate information such as force feedback is indispensable for high-precision robot assembly tasks, and current learning methods grapple with processing this complex observation data due to discontinuous force changes during operation and the inherent noise from the force sensor. To enhance learning efficiency amidst challenging observations, this paper proposes introducing the concept of latent causal factors that drive sensor observations and hold paramount significance in assembly tasks. This paper analyses the impact of discontinuous and noisy observations and offers two ways to infer causal factors. Based on the implied latent factors, we propose a method that learns high-precision assembly policies from interacting with the environment. The algorithm’s performance is evaluated in simulated and real-world nut insertion environments, demonstrating significant improvements over the previous methods. This research also underscores the promise of causal inference in addressing industrial challenges.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"183 ","pages":"Article 104832"},"PeriodicalIF":4.3,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658821","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}
Pub Date : 2024-11-09DOI: 10.1016/j.robot.2024.104855
Giovanni Boschetti , Riccardo Minto
Cable-driven parallel robots (CDPRs) are a particular class of parallel robots that provide several advantages that may well be received in the industrial field. However, the risk of damage due to cable failure is not negligible, thus procedures that move the end-effector to a safe pose after failure are required. This work aims to provide a sensorless failure detection and identification strategy to properly recognize the cable failure event without adding additional devices. This approach is paired with an end-effector recovery strategy to move the end-effector towards a safe position, thus providing for a complete cable failure recovery strategy, which detects the failure event and controls the end-effector accordingly. The proposed strategy is tested on a cable-driven suspended parallel robot prototype composed of industrial-grade components. The experimental results show the feasibility of the proposed approach.
{"title":"A sensorless approach for cable failure detection and identification in cable-driven parallel robots","authors":"Giovanni Boschetti , Riccardo Minto","doi":"10.1016/j.robot.2024.104855","DOIUrl":"10.1016/j.robot.2024.104855","url":null,"abstract":"<div><div>Cable-driven parallel robots (CDPRs) are a particular class of parallel robots that provide several advantages that may well be received in the industrial field. However, the risk of damage due to cable failure is not negligible, thus procedures that move the end-effector to a safe pose after failure are required. This work aims to provide a sensorless failure detection and identification strategy to properly recognize the cable failure event without adding additional devices. This approach is paired with an end-effector recovery strategy to move the end-effector towards a safe position, thus providing for a complete cable failure recovery strategy, which detects the failure event and controls the end-effector accordingly. The proposed strategy is tested on a cable-driven suspended parallel robot prototype composed of industrial-grade components. The experimental results show the feasibility of the proposed approach.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"183 ","pages":"Article 104855"},"PeriodicalIF":4.3,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658820","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}
Pub Date : 2024-11-08DOI: 10.1016/j.robot.2024.104854
Alessandro Navone, Mauro Martini, Marco Ambrosio, Andrea Ostuni, Simone Angarano, Marcello Chiaberge
Segmentation-based autonomous navigation has recently been presented as an appealing approach to guiding robotic platforms through crop rows without requiring perfect GPS localization. Nevertheless, current techniques are restricted to situations where the distinct separation between the plants and the sky allows for the identification of the row’s center. However, tall, dense vegetation, such as high tree rows and orchards, is the primary cause of GPS signal blockage. In this study, we increase the overall robustness and adaptability of the control algorithm by extending the segmentation-based robotic guiding to those cases where canopies and branches occlude the sky and prevent the utilization of GPS and earlier approaches. An efficient Deep Neural Network architecture has been used to address semantic segmentation, performing the training with synthetic data only. Numerous vineyards and tree fields have undergone extensive testing in both simulation and real world to show the solution’s competitive benefits. The system achieved unseen results in orchards, with a Mean Average Error smaller than 9% of the maximum width of each row, improving state-of-the-art algorithms by disclosing new scenarios such as close canopy crops. The official code can be found at: https://github.com/PIC4SeR/SegMinNavigation.git.
{"title":"GPS-free autonomous navigation in cluttered tree rows with deep semantic segmentation","authors":"Alessandro Navone, Mauro Martini, Marco Ambrosio, Andrea Ostuni, Simone Angarano, Marcello Chiaberge","doi":"10.1016/j.robot.2024.104854","DOIUrl":"10.1016/j.robot.2024.104854","url":null,"abstract":"<div><div>Segmentation-based autonomous navigation has recently been presented as an appealing approach to guiding robotic platforms through crop rows without requiring perfect GPS localization. Nevertheless, current techniques are restricted to situations where the distinct separation between the plants and the sky allows for the identification of the row’s center. However, tall, dense vegetation, such as high tree rows and orchards, is the primary cause of GPS signal blockage. In this study, we increase the overall robustness and adaptability of the control algorithm by extending the segmentation-based robotic guiding to those cases where canopies and branches occlude the sky and prevent the utilization of GPS and earlier approaches. An efficient Deep Neural Network architecture has been used to address semantic segmentation, performing the training with synthetic data only. Numerous vineyards and tree fields have undergone extensive testing in both simulation and real world to show the solution’s competitive benefits. The system achieved unseen results in orchards, with a Mean Average Error smaller than 9% of the maximum width of each row, improving state-of-the-art algorithms by disclosing new scenarios such as close canopy crops. The official code can be found at: <span><span>https://github.com/PIC4SeR/SegMinNavigation.git</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"183 ","pages":"Article 104854"},"PeriodicalIF":4.3,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658818","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}
Pub Date : 2024-10-31DOI: 10.1016/j.robot.2024.104842
Mario Ramírez-Neria , Rafal Madonski , Eduardo Gamaliel Hernández-Martínez , Norma Lozada-Castillo , Guillermo Fernández-Anaya , Alberto Luviano-Juárez
This article presents a Linear Active Disturbance Rejection scheme for the robust trajectory tracking control of an Omnidirectional robot, including an additional saturation element in the control design to improve the transient closed-loop response by including a saturation-input strategy in the Extended State Observer design, mitigating the possible arising peaking phenomenon. In addition, the controller is implemented in the kinematic model of the robotic system, assuming as the available information the position and orientation measurement and concerning the system structure, it is just known the order of the system and the control gain matrix as well. A wide set of laboratory experiments, including a comparison with a standard ADRC (i.e. without the proposed anti-peaking mechanism) and a PI-based control including an anti-peaking proposal, in the presence of different disturbance elements in the terrain of smooth and abrupt nature is carried out to formulate a comprehensive assessment of the proposal which validate the practical advantages of the proposal in robust trajectory tracking of the kind of robots.
本文提出了一种线性主动干扰抑制方案，用于全向机器人的鲁棒轨迹跟踪控制，在控制设计中加入了额外的饱和元素，通过在扩展状态观测器设计中加入饱和输入策略来改善瞬态闭环响应，缓解可能出现的峰值现象。此外，控制器是在机器人系统的运动学模型中实现的，假定位置和方向测量为可用信息，关于系统结构，只知道系统的阶次和控制增益矩阵。通过大量的实验室实验，包括与标准 ADRC（即不含提议的防抖动机制）和基于 PI 的控制（包括防抖动提议）的比较，在平滑和突变地形中存在不同干扰因素的情况下，对该提议进行了全面评估，验证了该提议在机器人稳健轨迹跟踪方面的实际优势。
{"title":"Robust trajectory tracking for omnidirectional robots by means of anti-peaking linear active disturbance rejection","authors":"Mario Ramírez-Neria , Rafal Madonski , Eduardo Gamaliel Hernández-Martínez , Norma Lozada-Castillo , Guillermo Fernández-Anaya , Alberto Luviano-Juárez","doi":"10.1016/j.robot.2024.104842","DOIUrl":"10.1016/j.robot.2024.104842","url":null,"abstract":"<div><div>This article presents a Linear Active Disturbance Rejection scheme for the robust trajectory tracking control of an Omnidirectional robot, including an additional saturation element in the control design to improve the transient closed-loop response by including a saturation-input strategy in the Extended State Observer design, mitigating the possible arising peaking phenomenon. In addition, the controller is implemented in the kinematic model of the robotic system, assuming as the available information the position and orientation measurement and concerning the system structure, it is just known the order of the system and the control gain matrix as well. A wide set of laboratory experiments, including a comparison with a standard ADRC (<em>i.e</em>. without the proposed anti-peaking mechanism) and a PI-based control including an anti-peaking proposal, in the presence of different disturbance elements in the terrain of smooth and abrupt nature is carried out to formulate a comprehensive assessment of the proposal which validate the practical advantages of the proposal in robust trajectory tracking of the kind of robots.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"183 ","pages":"Article 104842"},"PeriodicalIF":4.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586364","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}
Pub Date : 2024-10-30DOI: 10.1016/j.robot.2024.104844
Fenglei Zheng , Aijun Yin , Chuande Zhou
Object detection is the most important part in intelligent assembly tasks, accurate and fast detection for different targets can complete positioning and assembly tasks more automatically and efficiently. In this paper, a feature enhancement object detection model based on YOLO is proposed. Firstly, the expression ability of feature layer is enhanced through RFP (Recursive Feature Pyramid) structure. The ARSPP (Atrous Residual Spatial Pyramid Pooling) is proposed to have a further enhancement for the feature layers output by the backbone network, it improves the recognition performance for multi-scale targets of model by using different size of dilated convolution and residual connection. Finally, the contiguous pyramid features are fused and enhanced through the attention mechanism, the results are used for the input of next recursive or predictive output. The model proposed in this paper effectively improves the detection accuracy of YOLO, it has 3% MAP improvement in PASCAL VOC dataset. The validity and accuracy of the model are verified in the robot intelligent assembly recognition task.
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Pub Date : 2024-10-28DOI: 10.1016/j.robot.2024.104843
Yongqiang Zhu , Junru Zhu , Pingxia Zhang
Due to the length of the body, multiple number of wheels and the complexity of controlling, it is difficult for a multi-axle wheeled robot to avoid obstacles autonomously in narrow space. To solve this problem, this article presents window-zone division and gap-seeking strategies for local obstacle avoidance of a multi-axle multi-steering-mode all-wheel-steering wheeled robot. Firstly, according to the influence degree of lidar points on the robot, combining with the human driving characteristics of avoiding obstacles, a window-zone division strategy is proposed. The lidar points are selected and divided according to the degree of emergency. By eliminating irrelevant points, the work of obstacle avoidance calculation is reduced. Thus, this increases the response speed of obstacle avoidance. Based on this, the robot uses a multi-steering-mode to avoid emergency obstacle. Secondly, the gap-seeking theory of normal obstacle avoidance is proposed. It can seek the passable gap among the surrounding lidar points according to the prediction of the robot's driving trajectory corresponding to different steering angles. Thirdly, the on-board control system and the upper computer program of the robot were designed. Thereafter a multi-steering-mode algorithm was designed based on the front and rear wheel steering angles and speed, as well as the travel trajectory forecast-drawing module. Finally, the proposed methods have been implemented on a five-axle all-wheel steering wheeled robot. Some obstacle avoidance experiments are carried out with S-shaped, Z-Shaped, U-Shaped, and Random obstacle distribution. The results show that the proposed strategy can finish all obstacle avoidance successfully.
由于车身长、轮子多、控制复杂，多轴轮式机器人很难在狭窄空间内自主避障。为解决这一问题，本文提出了多轴多转向模式全轮转向轮式机器人局部避障的窗区划分和间隙寻找策略。首先，根据激光雷达点对机器人的影响程度，结合人类驾驶避障的特点，提出了窗口区域划分策略。根据紧急程度对激光雷达点进行选择和划分。通过剔除无关点，减少了避障计算的工作量。因此，这提高了避障响应速度。在此基础上，机器人采用多转向模式避开紧急障碍物。其次，提出了正常避障的间隙寻找理论。它可以根据不同转向角度对应的机器人行驶轨迹预测，在周围激光雷达点中寻找可通过的间隙。第三，设计了机器人的车载控制系统和上位机程序。之后，设计了基于前后轮转向角和速度的多转向模式算法，以及行驶轨迹预测绘制模块。最后，在一个五轴全轮转向轮式机器人上实现了所提出的方法。在 S 形、Z 形、U 形和随机障碍物分布情况下，进行了一些避障实验。结果表明，所提出的策略可以成功完成所有障碍物的避让。
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