Robotics and Autonomous Systems最新文献_第3页

A compound planning algorithm considering both collision detection and obstacle avoidance for intelligent demolition robots 同时考虑碰撞检测和避障的智能爆破机器人复合规划算法

IF 4.3 2区计算机科学

Robotics and Autonomous Systems Pub Date : 2024-08-12 DOI: 10.1016/j.robot.2024.104781

{"title":"A compound planning algorithm considering both collision detection and obstacle avoidance for intelligent demolition robots","authors":"","doi":"10.1016/j.robot.2024.104781","DOIUrl":"10.1016/j.robot.2024.104781","url":null,"abstract":"<div><p>This paper presents a compound planning algorithm considering both collision detection and obstacle avoidance for intelligent demolition robots working safely in high-radiation environments. Firstly, configurations and kinematics of the intelligent demolition robot are detailed to detect the possible obstacles in its workspace. A collision detection function based on the improved dual vector method is proposed to detect the different distances between the robot and obstacles in three cases: a point and a line segment, two line segments, and a line segment and a geometric shape. This function can also be applied to detect collisions with various obstacles of different shapes reasonably and efficiently. Furthermore, an obstacle avoidance function based on modified gradient projection method considering multi-task transformation is proposed. According to the different distances between the robot and the obstacle, it can be used in three situations: end obstacle avoidance task, end effector operation task, and end trajectory tracking task. This function can be applied to avoid obstacles both in the workspace and on the desired path. Finally, a simulation system is established to verify the collision detection and obstacle avoidance algorithms of the intelligent demolition robot. An experiment was conducted on the intelligent demolition robot. This robot can successfully achieve the expected trajectory with the method described in this article. Results of simulation and experiment demonstrate that obstacles both in workspace and on desired path can be detected and avoided properly.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142049005","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}

引用次数: 0

A multi-purpose robot perception system enabling closed-loop control for zero defect manufacturing in gluing processes of large parts 多功能机器人感知系统实现闭环控制，实现大型部件涂胶过程的零缺陷制造

IF 4.3 2区计算机科学

Robotics and Autonomous Systems Pub Date : 2024-08-08 DOI: 10.1016/j.robot.2024.104778

{"title":"A multi-purpose robot perception system enabling closed-loop control for zero defect manufacturing in gluing processes of large parts","authors":"","doi":"10.1016/j.robot.2024.104778","DOIUrl":"10.1016/j.robot.2024.104778","url":null,"abstract":"<div><p>Significant progress has been made in robot perception facilitating the deployment of advanced automation across a wide range of applications however typically little solutions are presented for large parts manufacturing. This paper presents a versatile robot perception system designed to enhance the flexibility and precision of robotic adhesive dispensing processes. This solution is capable of addressing the unique challenges of implementing automation solutions in large parts manufacturing, such as flexibility to manufacture small lot sizes, perception for complex task sequences, and handling parts with large dimensions that cannot be captured in single camera frames. A solution based on one single vision sensor is presented for part type recognition, part localization, process monitoring, and quality inspection. This includes algorithms for these perception functionalities and a closed-loop control framework aimed at zero-defect manufacturing. The task planning and execution architecture is based on Behavior Trees to allow modular and scalable robot task modeling and execution, whereas a knowledge database updated with process monitoring results via a module named event manager serves to prevent the propagation of defects to the following production steps. The proposed approach was tested and validated in a robotic cell for glue dispensing for a case study inspired by the bus and coach sector. The results indicate that the system can tolerate position uncertainties and random parts feeding, address disruptions in-process or trigger corrective actions post-process, and easily accommodate new variants.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142040399","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}

引用次数: 0

Hierarchical optimum control of a novel wheel-legged quadruped 新型轮足四足动物的分层优化控制

IF 4.3 2区计算机科学

Robotics and Autonomous Systems Pub Date : 2024-08-06 DOI: 10.1016/j.robot.2024.104775

引用次数: 0

A decoupled solution to heterogeneous multi-formation planning and coordination for object transportation 物体运输中异构多变形规划与协调的解耦解决方案

IF 4.3 2区计算机科学

Robotics and Autonomous Systems Pub Date : 2024-08-05 DOI: 10.1016/j.robot.2024.104773

{"title":"A decoupled solution to heterogeneous multi-formation planning and coordination for object transportation","authors":"","doi":"10.1016/j.robot.2024.104773","DOIUrl":"10.1016/j.robot.2024.104773","url":null,"abstract":"<div><p>Multi-robot formations have numerous applications, such as cooperative object transportation in intelligent warehouses. In this context, robots are tasked with delivering objects in formation while avoiding intra- and inter-formation collisions. This necessitates the development of solutions for multi-robot task allocation, formation generation, rigid formation route planning, and formation coordination. In this paper, we present a cooperative formation object transportation system for heterogeneous multi-robot systems which captures robot dynamics and avoids inter-formation collisions. Accounting for heterogeneous formations expands the applicability of the proposed robotic transport system. For formation generation, we propose an approach based on conflict-based search, which integrates high-level path planning with low-level trajectory optimisation. For heterogeneous formation planning, we present a two-stage iterative trajectory optimisation framework which adheres to the kinematic constraints of our heterogeneous multi-robot system while retaining formation rigidity. For multi-formation coordination, we use a loosely-coupled algorithm which can guarantee collision-free and deadlock-free formation navigation under minimal assumptions. We demonstrate the efficacy of our approach in simulation.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S092188902400157X/pdfft?md5=e74907924c3b480bce1601e46314e6dc&pid=1-s2.0-S092188902400157X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141979648","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}

引用次数: 0

Learning continuous multi-UAV controls with directed explorations for flood area coverage 学习多无人机的连续控制，进行洪水区域覆盖的定向探索

IF 4.3 2区计算机科学

Robotics and Autonomous Systems Pub Date : 2024-08-05 DOI: 10.1016/j.robot.2024.104774

{"title":"Learning continuous multi-UAV controls with directed explorations for flood area coverage","authors":"","doi":"10.1016/j.robot.2024.104774","DOIUrl":"10.1016/j.robot.2024.104774","url":null,"abstract":"<div><p>Real time on-ground information is of critical value during any natural disaster such as floods. The disaster response teams require the latest ground information of the flooded areas to effectively plan and execute rescue operations. Unmanned Aerial Vehicles (UAVs) are increasingly becoming a tool to perform quick surveys of larger areas such as flood disasters. In this paper, we propose a method to perform critical area coverage of flood-struck regions using multiple autonomous UAVs. A Deep Reinforcement Learning algorithm is proposed to learn continuous multi-UAV controls, incorporating a directed exploration strategy for the DDPG’s target actor, which relies on the D-infinity (DINF) algorithm. The DINF water flow estimation technique utilizes surface elevation data to understand and predict the directed discharge of floodwater. Further, we introduce a Path scatter strategy for the multi-UAV system that inhibits the clustered formation of the UAVs over low-elevated regions. The performance of the proposed D3S (DDPG+DINF+Path Scatter) algorithm is evaluated using various performance metrics, such as average cumulative rewards, number of collisions, and UAVs’ spread observed over the environment. In comparison to the baseline algorithms and other prevalent approaches in the literature, the proposed method is found to be better placed as the results highlight a significantly improved performance by D3S across different metrics.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141979647","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}

引用次数: 0

Optimizing robotic arm control using deep Q-learning and artificial neural networks through demonstration-based methodologies: A case study of dynamic and static conditions 通过基于演示的方法使用深度 Q-learning 和人工神经网络优化机械臂控制：动态和静态条件案例研究

IF 4.3 2区计算机科学

Robotics and Autonomous Systems Pub Date : 2024-08-03 DOI: 10.1016/j.robot.2024.104771

{"title":"Optimizing robotic arm control using deep Q-learning and artificial neural networks through demonstration-based methodologies: A case study of dynamic and static conditions","authors":"","doi":"10.1016/j.robot.2024.104771","DOIUrl":"10.1016/j.robot.2024.104771","url":null,"abstract":"<div><p>This paper uses robot programming techniques, such as Deep Q Network, Artificial Neural Network, and Artificial Deep Q Network, to address challenges related to controlling robotic arms through demonstration learning. Static and dynamic states of the subjects were the subjects of experiments. Each method's classification accuracy process success values and experimental condition combination were evaluated. The DQN method demonstrated favourable classification accuracy outcomes, achieving an Accuracy value of 0.64 for the fixed dice and 0.52 for the moving dice. The Response value was 0.51 for the fixed dice and 0.41 for the moving dice, indicating a moderate level. The ANN method demonstrated lower accuracy, with Accuracy values of 0.59 and 0.56 and Response values of 0.61 and 0.58, respectively. The ADQN method demonstrated superior outcomes, with Accuracy values of 0.66 and 0.59 and Response values of 0.67 and 0.61. During the initial learning iterations, ADQN demonstrated the highest success rate at 33.67 %, whereas DQN and ANN achieved 28.39 % and 20.13 % success rates, respectively. As the number of iterations increased, all methods demonstrated improvement in their results. ADQN maintained a high success rate of 97.59 %, while DQN and ANN attained 82.16 % and 88.66 %, respectively. As the number of iterations increases, the results of all methods improve, but the success rate of the Artificial Deep Q Network remains high. As the number of iterations increases, both Deep Q Network and Artificial Neural Network demonstrate the potential to achieve good results. Overall, the findings support the efficacy of robot programming techniques that incorporate demonstration learning. The Artificial Deep Q Network is the most successful and fast-converging method suitable for various robot control tasks. These findings provide a foundation for future research and large-scale, comprehensive learning applications for complex rot control.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142001989","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}

引用次数: 0

Mission based systems for connected automated mobility 基于任务的互联自动交通系统

IF 4.3 2区计算机科学

Robotics and Autonomous Systems Pub Date : 2024-07-31 DOI: 10.1016/j.robot.2024.104772

{"title":"Mission based systems for connected automated mobility","authors":"","doi":"10.1016/j.robot.2024.104772","DOIUrl":"10.1016/j.robot.2024.104772","url":null,"abstract":"<div><p>Cooperative, connected and automated mobility (CCAM) is one of the next big steps in the automotive industry. Thanks to recent improvements in Advanced Driver Assistance Systems, and novel methods for automating vehicles, more safe and efficient transport mechanisms have been achieved. Current vehicles are already connected devices, and communications between vehicles, infrastructure and other road users will allow traffic agents to share information and use it to coordinate their actions. The full integration between cooperation, connectivity, and automation technologies entail an important achievement to improve road safety, traffic efficiency and comfort of driving. To approach this goal, the main contributions of this work propose a new distributed mission system based on Advanced Behavioral Points (ABP). That is, based on relevant points inside a plan which store a collection of predefined tasks that operate at the high level layer of an automated and connected vehicle to coordinate behaviors when connecting to critical emplacements like junctions and roundabouts. This approach, which has been tested in the simulation environment of Carla, provide a collaboration stack between the traffic infrastructure and the ego vehicle so as to cope with actual problems such as traffic congestion and road accidents.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0921889024001568/pdfft?md5=8b3491dabbc80cc6bfc0b42e6fae5ea1&pid=1-s2.0-S0921889024001568-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934837","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}

引用次数: 0

Visual Predictive Control for mobile manipulator: Visibility, manipulability, and stability 移动机械手的视觉预测控制：可视性、可操作性和稳定性

IF 4.3 2区计算机科学

Robotics and Autonomous Systems Pub Date : 2024-07-26 DOI: 10.1016/j.robot.2024.104754

引用次数: 0

Learning periodic skills for robotic manipulation: Insights on orientation and impedance 学习机器人操作的周期性技能：对方向和阻抗的见解

IF 4.3 2区计算机科学

Robotics and Autonomous Systems Pub Date : 2024-07-26 DOI: 10.1016/j.robot.2024.104763

{"title":"Learning periodic skills for robotic manipulation: Insights on orientation and impedance","authors":"","doi":"10.1016/j.robot.2024.104763","DOIUrl":"10.1016/j.robot.2024.104763","url":null,"abstract":"<div><p>Many daily tasks exhibit a periodic nature, necessitating that robots possess the ability to execute them either alone or in collaboration with humans. A widely used approach to encode and learn such periodic patterns from human demonstrations is through periodic Dynamic Movement Primitives (DMPs). Periodic DMPs encode cyclic data independently across multiple dimensions of multi-degree of freedom systems. This method is effective for simple data, like Cartesian or joint position trajectories. However, it cannot account for various geometric constraints imposed by more complex data, such as orientation and stiffness. To bridge this gap, we propose a novel periodic DMP formulation that enables the encoding of periodic orientation trajectories and varying stiffness matrices while considering their geometric constraints. Our geometry-aware approach exploits the properties of the Riemannian manifold and Lie group to directly encode such periodic data while respecting its inherent geometric constraints. We initially employed simulation to validate the technical aspects of the proposed method thoroughly. Subsequently, we conducted experiments with two different real-world robots performing daily tasks involving periodic changes in orientation and/or stiffness, <em>i.e.,</em> operating a drilling machine using a rotary handle and facilitating collaborative human–robot sawing.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0921889024001477/pdfft?md5=ea9ea9b48b7711883884dd3fa83f8311&pid=1-s2.0-S0921889024001477-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141844761","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}

引用次数: 0

An overactuated aerial robot based on cooperative quadrotors attached through passive universal joints: Modeling, control and 6-DoF trajectory tracking 基于通过无源万向节连接的合作四旋翼的过驱动空中机器人：建模、控制和 6-DoF 轨迹跟踪

IF 4.3 2区计算机科学

Robotics and Autonomous Systems Pub Date : 2024-07-24 DOI: 10.1016/j.robot.2024.104761

{"title":"An overactuated aerial robot based on cooperative quadrotors attached through passive universal joints: Modeling, control and 6-DoF trajectory tracking","authors":"","doi":"10.1016/j.robot.2024.104761","DOIUrl":"10.1016/j.robot.2024.104761","url":null,"abstract":"<div><p>This article discusses a novel aerial robot architecture that overcomes the underactuation of conventional multirotor systems without adding dedicated rotor tilting actuators. The proposed system is based on four quadrotors cooperatively carrying a central body to which they are attached through passive universal joints. While conventional parallel axis multirotors are underactuated, the proposed mechanism makes the system overactuated, enabling independent position and orientation control of the main body. This implies that the payload can be carried in the minimum drag orientation, it enables take-off and landing on inclined surfaces and it provides thrust-vectoring capabilities to the system, leading to high control authority. A detailed dynamic model is derived making use of Lagrangian formalism and a hierarchical control law based on such model is proposed to stabilize the system. This control law is designed to ensure good tracking while minimizing power consumption. The proposed control law and the capabilities of the architecture are evaluated in simulation and in outdoor experimental flights, where the aerial robot shows autonomous tracking of the six degrees of freedom (DoF) of the main body, an inherently unfeasible maneuver for conventional underactuated multirotors.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0921889024001453/pdfft?md5=6313724e3f9a37984858df668d0d80e0&pid=1-s2.0-S0921889024001453-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141851211","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}

引用次数: 0