Pub Date : 2024-02-03DOI: 10.1007/s10846-024-02060-z
Xiwei Wu, Bing Xiao, Lu Cao, Haibin Huang
This paper presents a simultaneous task assignment and trajectory planning method for unmanned system swarm by using optimal transport and model predictive control (OT-MPC). Unlike the conventional hierarchical assignment and planning, the proposed approach addresses both the task assignment and trajectory planning subproblems concurrently. To be specific, a unified cost function is designed to solve task assignment and trajectory planning problem. Moreover, the multi-tasks are assigned by using optimal transport, which establishes an optimal mapping between tasks and unmanned system vehicles based on transportation cost. The trajectory planning is achieved by using model predictive control, which generates high-quality navigation trajectories considering obstacle avoidance. Finally, the proposed method is applied to the unmanned surface vehicles swarm. Numerical simulations and experiments were conducted to validate the effectiveness of the proposed method.
{"title":"Optimal Transport and Model Predictive Control-based Simultaneous Task Assignment and Trajectory Planning for Unmanned System Swarm","authors":"Xiwei Wu, Bing Xiao, Lu Cao, Haibin Huang","doi":"10.1007/s10846-024-02060-z","DOIUrl":"https://doi.org/10.1007/s10846-024-02060-z","url":null,"abstract":"<p>This paper presents a simultaneous task assignment and trajectory planning method for unmanned system swarm by using optimal transport and model predictive control (OT-MPC). Unlike the conventional hierarchical assignment and planning, the proposed approach addresses both the task assignment and trajectory planning subproblems concurrently. To be specific, a unified cost function is designed to solve task assignment and trajectory planning problem. Moreover, the multi-tasks are assigned by using optimal transport, which establishes an optimal mapping between tasks and unmanned system vehicles based on transportation cost. The trajectory planning is achieved by using model predictive control, which generates high-quality navigation trajectories considering obstacle avoidance. Finally, the proposed method is applied to the unmanned surface vehicles swarm. Numerical simulations and experiments were conducted to validate the effectiveness of the proposed method.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"68 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139662543","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}
Pub Date : 2024-02-03DOI: 10.1007/s10846-023-02037-4
José Sarmento, Filipe Neves dos Santos, André Silva Aguiar, Vítor Filipe, António Valente
Human-robot collaboration (HRC) is becoming increasingly important in advanced production systems, such as those used in industries and agriculture. This type of collaboration can contribute to productivity increase by reducing physical strain on humans, which can lead to reduced injuries and improved morale. One crucial aspect of HRC is the ability of the robot to follow a specific human operator safely. To address this challenge, a novel methodology is proposed that employs monocular vision and ultra-wideband (UWB) transceivers to determine the relative position of a human target with respect to the robot. UWB transceivers are capable of tracking humans with UWB transceivers but exhibit a significant angular error. To reduce this error, monocular cameras with Deep Learning object detection are used to detect humans. The reduction in angular error is achieved through sensor fusion, combining the outputs of both sensors using a histogram-based filter. This filter projects and intersects the measurements from both sources onto a 2D grid. By combining UWB and monocular vision, a remarkable 66.67% reduction in angular error compared to UWB localization alone is achieved. This approach demonstrates an average processing time of 0.0183s and an average localization error of 0.14 meters when tracking a person walking at an average speed of 0.21 m/s. This novel algorithm holds promise for enabling efficient and safe human-robot collaboration, providing a valuable contribution to the field of robotics.
{"title":"Fusion of Time-of-Flight Based Sensors with Monocular Cameras for a Robotic Person Follower","authors":"José Sarmento, Filipe Neves dos Santos, André Silva Aguiar, Vítor Filipe, António Valente","doi":"10.1007/s10846-023-02037-4","DOIUrl":"https://doi.org/10.1007/s10846-023-02037-4","url":null,"abstract":"<p>Human-robot collaboration (HRC) is becoming increasingly important in advanced production systems, such as those used in industries and agriculture. This type of collaboration can contribute to productivity increase by reducing physical strain on humans, which can lead to reduced injuries and improved morale. One crucial aspect of HRC is the ability of the robot to follow a specific human operator safely. To address this challenge, a novel methodology is proposed that employs monocular vision and ultra-wideband (UWB) transceivers to determine the relative position of a human target with respect to the robot. UWB transceivers are capable of tracking humans with UWB transceivers but exhibit a significant angular error. To reduce this error, monocular cameras with Deep Learning object detection are used to detect humans. The reduction in angular error is achieved through sensor fusion, combining the outputs of both sensors using a histogram-based filter. This filter projects and intersects the measurements from both sources onto a 2D grid. By combining UWB and monocular vision, a remarkable 66.67% reduction in angular error compared to UWB localization alone is achieved. This approach demonstrates an average processing time of 0.0183s and an average localization error of 0.14 meters when tracking a person walking at an average speed of 0.21 m/s. This novel algorithm holds promise for enabling efficient and safe human-robot collaboration, providing a valuable contribution to the field of robotics.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"59 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139662536","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}
Pub Date : 2024-02-02DOI: 10.1007/s10846-023-02046-3
Jianfeng Li, Juan Dai, Zhong Su, Cui Zhu
Most current research on dynamic visual Simultaneous Localization and Mapping (SLAM) systems focuses on scenes where static objects occupy most of the environment. However, in densely populated indoor environments, the movement of the crowd can lead to the loss of feature information, thereby diminishing the system’s robustness and accuracy. This paper proposes a visual SLAM algorithm for dense crowd environments based on a combination of the ORB-SLAM2 framework and RGB-D cameras. Firstly, we introduced a dedicated target detection network thread and improved the performance of the target detection network, enhancing its detection coverage in crowded environments, resulting in a 41.5% increase in average accuracy. Additionally, we found that some feature points other than humans in the detection box were mistakenly deleted. Therefore, we proposed an algorithm based on standard deviation fitting to effectively filter out the features. Finally, our system is evaluated on the TUM and Bonn RGB-D dynamic datasets and compared with ORB-SLAM2 and other state-of-the-art visual dynamic SLAM methods. The results indicate that our system’s pose estimation error is reduced by at least 93.60% and 97.11% compared to ORB-SLAM2 in high dynamic environments and the Bonn RGB-D dynamic dataset, respectively. Our method demonstrates comparable performance compared to other recent visual dynamic SLAM methods.
目前对动态视觉同步定位与绘图(SLAM)系统的研究大多集中在静态物体占据大部分环境的场景上。然而,在人口密集的室内环境中,人群的移动会导致特征信息的丢失,从而降低系统的鲁棒性和准确性。本文结合 ORB-SLAM2 框架和 RGB-D 摄像机,提出了一种适用于密集人群环境的视觉 SLAM 算法。首先,我们引入了专用的目标检测网络线程,并改进了目标检测网络的性能,提高了其在拥挤环境中的检测覆盖率,使平均精度提高了 41.5%。此外,我们还发现检测框中一些非人类的特征点被误删。因此,我们提出了一种基于标准偏差拟合的算法,以有效过滤掉这些特征点。最后,我们的系统在 TUM 和 Bonn RGB-D 动态数据集上进行了评估,并与 ORB-SLAM2 和其他最先进的视觉动态 SLAM 方法进行了比较。结果表明,在高动态环境和波恩 RGB-D 动态数据集中,与 ORB-SLAM2 相比,我们系统的姿态估计误差分别减少了至少 93.60% 和 97.11%。与其他最新的视觉动态 SLAM 方法相比,我们的方法性能相当。
{"title":"RGB-D Based Visual SLAM Algorithm for Indoor Crowd Environment","authors":"Jianfeng Li, Juan Dai, Zhong Su, Cui Zhu","doi":"10.1007/s10846-023-02046-3","DOIUrl":"https://doi.org/10.1007/s10846-023-02046-3","url":null,"abstract":"<p>Most current research on dynamic visual Simultaneous Localization and Mapping (SLAM) systems focuses on scenes where static objects occupy most of the environment. However, in densely populated indoor environments, the movement of the crowd can lead to the loss of feature information, thereby diminishing the system’s robustness and accuracy. This paper proposes a visual SLAM algorithm for dense crowd environments based on a combination of the ORB-SLAM2 framework and RGB-D cameras. Firstly, we introduced a dedicated target detection network thread and improved the performance of the target detection network, enhancing its detection coverage in crowded environments, resulting in a 41.5% increase in average accuracy. Additionally, we found that some feature points other than humans in the detection box were mistakenly deleted. Therefore, we proposed an algorithm based on standard deviation fitting to effectively filter out the features. Finally, our system is evaluated on the TUM and Bonn RGB-D dynamic datasets and compared with ORB-SLAM2 and other state-of-the-art visual dynamic SLAM methods. The results indicate that our system’s pose estimation error is reduced by at least 93.60% and 97.11% compared to ORB-SLAM2 in high dynamic environments and the Bonn RGB-D dynamic dataset, respectively. Our method demonstrates comparable performance compared to other recent visual dynamic SLAM methods.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"2 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139670319","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}
Pub Date : 2024-02-01DOI: 10.1007/s10846-023-01906-2
Nesrine Harbaoui, Khoder Makkawi, Nourdine Ait-Tmazirte, Maan El Badaoui El Najjar
In many transport applications, one of the safety critical function is the localization. This is all the more true for land transport applications such as autonomous vehicles. While the democratization of satellite positioning systems, such as GPS, Galileo, Beidou or Glonass, has made it possible to consider a global solution applicable anywhere in the world, the principle of positioning by receiving signals from satellites more than twenty thousand kilometers away shows limits when they are confronted with disturbances related to the environment close to the receiver. However, for these safety-critical applications, the requirements are strong and sometimes even conflicting. The developed function must meet a defined level of precision, availability, continuity of service, integrity, operational safety and finally robustness to environment changes. Taken separately, these requirements can be achieved by actions recommended by the literature. For more precision and availability, coupling between absolute GNSS data and relative INS and odometer data, is recommended. To increase safety and integrity, a fault detection layer is essential, but this will negatively impact availability. One therefore needs a fault management layer. A harmonious policy, thought at the function design, makes it possible to achieve all the objectives. In this study, we propose a framework based on a tripartite approach: the tight fusion of GNSS and IMU data, the development of a diagnostic layer based on information theory and using the very promising alpha Rényi divergence, as well as a fault isolation layer. The diagnostic layer is designed to be robust and adaptive to changing environment through a deep neural network. The proposed framework is tested on data acquired in the field. Encouraging results allow to consider the generalization of the concept.
在许多运输应用中,安全的关键功能之一是定位。对于自动驾驶汽车等陆地运输应用来说,更是如此。虽然卫星定位系统(如 GPS、伽利略、北斗或格洛纳斯)的民主化使我们有可能考虑一种适用于世界任何地方的全球解决方案,但通过接收来自两万公里以外卫星的信号进行定位的原理,在遇到与接收器附近环境有关的干扰时就会显示出局限性。然而,对于这些安全关键型应用,要求非常严格,有时甚至相互冲突。所开发的功能必须满足规定的精度、可用性、服务连续性、完整性、操作安全性以及对环境变化的稳健性。分别来看,这些要求可以通过文献建议的措施来实现。为了提高精度和可用性,建议将全球导航卫星系统的绝对数据与 INS 和里程表的相对数据结合起来。为提高安全性和完整性,故障检测层必不可少,但这将对可用性产生负面影响。因此,我们需要一个故障管理层。在功能设计时考虑到和谐的政策,就有可能实现所有目标。在本研究中,我们提出了一个基于三方方法的框架:GNSS 和 IMU 数据的紧密融合、基于信息论并利用前景广阔的阿尔法雷尼发散法开发的诊断层以及故障隔离层。诊断层是通过深度神经网络设计的,具有鲁棒性并能适应不断变化的环境。所提出的框架在实地获取的数据上进行了测试。令人鼓舞的结果使我们可以考虑推广这一概念。
{"title":"Context Adaptive Fault Tolerant Multi-sensor fusion: Towards a Fail-Safe Multi Operational Objective Vehicle Localization","authors":"Nesrine Harbaoui, Khoder Makkawi, Nourdine Ait-Tmazirte, Maan El Badaoui El Najjar","doi":"10.1007/s10846-023-01906-2","DOIUrl":"https://doi.org/10.1007/s10846-023-01906-2","url":null,"abstract":"<p>In many transport applications, one of the safety critical function is the localization. This is all the more true for land transport applications such as autonomous vehicles. While the democratization of satellite positioning systems, such as GPS, Galileo, Beidou or Glonass, has made it possible to consider a global solution applicable anywhere in the world, the principle of positioning by receiving signals from satellites more than twenty thousand kilometers away shows limits when they are confronted with disturbances related to the environment close to the receiver. However, for these safety-critical applications, the requirements are strong and sometimes even conflicting. The developed function must meet a defined level of precision, availability, continuity of service, integrity, operational safety and finally robustness to environment changes. Taken separately, these requirements can be achieved by actions recommended by the literature. For more precision and availability, coupling between absolute GNSS data and relative INS and odometer data, is recommended. To increase safety and integrity, a fault detection layer is essential, but this will negatively impact availability. One therefore needs a fault management layer. A harmonious policy, thought at the function design, makes it possible to achieve all the objectives. In this study, we propose a framework based on a tripartite approach: the tight fusion of GNSS and IMU data, the development of a diagnostic layer based on information theory and using the very promising alpha Rényi divergence, as well as a fault isolation layer. The diagnostic layer is designed to be robust and adaptive to changing environment through a deep neural network. The proposed framework is tested on data acquired in the field. Encouraging results allow to consider the generalization of the concept.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"42 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139662625","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}
Pub Date : 2024-02-01DOI: 10.1007/s10846-024-02059-6
Wai Lun Leong, Jiawei Cao, Rodney Teo
Task allocation enables heterogeneous agents to execute heterogeneous tasks in the domain of unmanned aerial vehicles, while responding to dynamic changes in the environment and available resources to complete complex, multi-objective missions, leading to swarm intelligence. We propose a bio-inspired approach using digital pheromones to perform scalable task allocation when the number of agents, tasks, and the diameter of the communications graph increase. The resulting emergent behaviour also enables idle agents in the swarm to provide periodic or continuous connectivity between disconnected parts of the swarm. We validate our results through simulation and demonstrate the feasibility of our approach by applying it to the 3D coverage and patrol problem.
{"title":"Scalable Task Allocation with Communications Connectivity for Flying Ad-Hoc Networks","authors":"Wai Lun Leong, Jiawei Cao, Rodney Teo","doi":"10.1007/s10846-024-02059-6","DOIUrl":"https://doi.org/10.1007/s10846-024-02059-6","url":null,"abstract":"<p>Task allocation enables heterogeneous agents to execute heterogeneous tasks in the domain of unmanned aerial vehicles, while responding to dynamic changes in the environment and available resources to complete complex, multi-objective missions, leading to swarm intelligence. We propose a bio-inspired approach using digital pheromones to perform scalable task allocation when the number of agents, tasks, and the diameter of the communications graph increase. The resulting emergent behaviour also enables idle agents in the swarm to provide periodic or continuous connectivity between disconnected parts of the swarm. We validate our results through simulation and demonstrate the feasibility of our approach by applying it to the 3D coverage and patrol problem.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"10 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139670130","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}
Pub Date : 2024-01-29DOI: 10.1007/s10846-024-02051-0
Antonis Sidiropoulos, Zoe Doulgeri
Dynamic Movement Primitives (DMP) have found remarkable applicability and success in various robotic tasks, which can be mainly attributed to their generalization, modulation and robustness properties. However, the spatial generalization of DMP can be problematic in some cases, leading to excessive overscaling and in turn large velocities and accelerations. While other DMP variants have been proposed in the literature to tackle this issue, they can also exhibit excessive overscaling as we show in this work. Moreover, incorporating intermediate points (via-points) for adjusting the DMP trajectory to account for the geometry of objects related to the task, or to avoid or push aside objects that obstruct a specific task, is not addressed by the current DMP literature. In this work we tackle these unresolved so far issues by proposing an improved online spatial generalization, that remedies the shortcomings of the classical DMP generalization, and moreover allows the incorporation of dynamic via-points. This is achieved by designing an online adaptation scheme for the DMP weights which is proved to minimize the distance from the demonstrated acceleration profile to retain the shape of the demonstration, subject to dynamic via-point and initial/final state constraints. Extensive comparative simulations with the classical and other DMP variants are conducted, while experimental results validate the practical usefulness and efficiency of the proposed method.
{"title":"Dynamic Via-points and Improved Spatial Generalization for Online Trajectory Generation with Dynamic Movement Primitives","authors":"Antonis Sidiropoulos, Zoe Doulgeri","doi":"10.1007/s10846-024-02051-0","DOIUrl":"https://doi.org/10.1007/s10846-024-02051-0","url":null,"abstract":"<p>Dynamic Movement Primitives (DMP) have found remarkable applicability and success in various robotic tasks, which can be mainly attributed to their generalization, modulation and robustness properties. However, the spatial generalization of DMP can be problematic in some cases, leading to excessive overscaling and in turn large velocities and accelerations. While other DMP variants have been proposed in the literature to tackle this issue, they can also exhibit excessive overscaling as we show in this work. Moreover, incorporating intermediate points (via-points) for adjusting the DMP trajectory to account for the geometry of objects related to the task, or to avoid or push aside objects that obstruct a specific task, is not addressed by the current DMP literature. In this work we tackle these unresolved so far issues by proposing an improved online spatial generalization, that remedies the shortcomings of the classical DMP generalization, and moreover allows the incorporation of dynamic via-points. This is achieved by designing an online adaptation scheme for the DMP weights which is proved to minimize the distance from the demonstrated acceleration profile to retain the shape of the demonstration, subject to dynamic via-point and initial/final state constraints. Extensive comparative simulations with the classical and other DMP variants are conducted, while experimental results validate the practical usefulness and efficiency of the proposed method.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"169 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139580650","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}
Pub Date : 2024-01-25DOI: 10.1007/s10846-024-02050-1
Keshab Patra, Arpita Sinha, Anirban Guha
The cooperative manipulator group can accomplish complex and heavy payload tasks of object manipulation and transportation compared to a single manipulator. Effective coordination is crucial for cooperative task accomplishments. Multi-manipulator task distribution is highly complex because of the varying dynamic capabilities of the manipulators. We have introduced a novel fastest technique to quantify the dynamic task capability of the cooperative manipulator by scalar quantity and allocate the task accordingly. The scalar quantity determines the capability of applying an external wrench by end effector (EE) in line with the required wrench at the center of mass of the manipulating object. This quantity helps to diminish tracking errors in object manipulations or transportation and actuator saturation avoidance. The task distribution among the members is in proportion to their computed dynamic capability to ensure equal priority to the individual manipulators. The proposed task distribution formulation ensures the minimum magnitude of wrench interaction at the grasp point and the minimum internal wrench build-up in the object. Several physical simulation results assure trajectory tracking performance with the proposed task capability metric. The same metric aids in identifying the least capable manipulator, rearranging members for better performance, and deciding the required number of manipulators in the manipulator group.
{"title":"Online Capability Based Task Allocation of Cooperative Manipulators","authors":"Keshab Patra, Arpita Sinha, Anirban Guha","doi":"10.1007/s10846-024-02050-1","DOIUrl":"https://doi.org/10.1007/s10846-024-02050-1","url":null,"abstract":"<p>The cooperative manipulator group can accomplish complex and heavy payload tasks of object manipulation and transportation compared to a single manipulator. Effective coordination is crucial for cooperative task accomplishments. Multi-manipulator task distribution is highly complex because of the varying dynamic capabilities of the manipulators. We have introduced a novel fastest technique to quantify the dynamic task capability of the cooperative manipulator by scalar quantity and allocate the task accordingly. The scalar quantity determines the capability of applying an external wrench by end effector (EE) in line with the required wrench at the center of mass of the manipulating object. This quantity helps to diminish tracking errors in object manipulations or transportation and actuator saturation avoidance. The task distribution among the members is in proportion to their computed dynamic capability to ensure equal priority to the individual manipulators. The proposed task distribution formulation ensures the minimum magnitude of wrench interaction at the grasp point and the minimum internal wrench build-up in the object. Several physical simulation results assure trajectory tracking performance with the proposed task capability metric. The same metric aids in identifying the least capable manipulator, rearranging members for better performance, and deciding the required number of manipulators in the manipulator group.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"163 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139561044","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}
Pub Date : 2024-01-25DOI: 10.1007/s10846-024-02054-x
Youssef Aboudorra, Chiara Gabellieri, Ralph Brantjes, Quentin Sablé, Antonio Franchi
This paper introduces for the first time the design, modelling, and control of a novel morphing multi-rotor Unmanned Aerial Vehicle (UAV) that we call the OmniMorph. The morphing ability allows the selection of the configuration that optimizes energy consumption while ensuring the needed maneuverability for the required task. The most energy-efficient uni-directional thrust (UDT) configuration can be used, e.g., during standard point-to-point displacements. Fully-actuated (FA) and omnidirectional (OD) configurations can be instead used for full pose tracking, such as, e.g., constant attitude horizontal motions and full rotations on the spot, and for full wrench 6D interaction control and 6D disturbance rejection. Morphing is obtained using a single servomotor, allowing possible minimization of weight, costs, and maintenance complexity. The actuation properties are studied, and an optimal controller that compromises between performance and control effort is proposed and validated in realistic simulations. Preliminary tests on the prototype are presented to assess the propellers’ mutual aerodynamic interference.
{"title":"Modelling, Analysis, and Control of OmniMorph: an Omnidirectional Morphing Multi-rotor UAV","authors":"Youssef Aboudorra, Chiara Gabellieri, Ralph Brantjes, Quentin Sablé, Antonio Franchi","doi":"10.1007/s10846-024-02054-x","DOIUrl":"https://doi.org/10.1007/s10846-024-02054-x","url":null,"abstract":"<p>This paper introduces for the first time the design, modelling, and control of a novel morphing multi-rotor Unmanned Aerial Vehicle (UAV) that we call the OmniMorph. The morphing ability allows the selection of the configuration that optimizes energy consumption while ensuring the needed maneuverability for the required task. The most energy-efficient <i>uni-directional thrust</i> (UDT) configuration can be used, e.g., during standard point-to-point displacements. <i>Fully-actuated</i> (FA) and <i>omnidirectional</i> (OD) configurations can be instead used for full pose tracking, such as, e.g., constant attitude horizontal motions and full rotations on the spot, and for full wrench 6D interaction control and 6D disturbance rejection. Morphing is obtained using a single servomotor, allowing possible minimization of weight, costs, and maintenance complexity. The actuation properties are studied, and an optimal controller that compromises between performance and control effort is proposed and validated in realistic simulations. Preliminary tests on the prototype are presented to assess the propellers’ mutual aerodynamic interference.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"9 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139561037","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}
Pub Date : 2024-01-25DOI: 10.1007/s10846-023-02045-4
Gerasimos Damigos, Nikolaos Stathoulopoulos, Anton Koval, Tore Lindgren, George Nikolakopoulos
Multiple modern robotic applications benefit from centralized cognition and processing schemes. However, modern equipped robotic platforms can output a large amount of data, which may exceed the capabilities of modern wireless communication systems if all data is transmitted without further consideration. This research presents a multi-agent, centralized, and real-time 3D point cloud map merging scheme for ceaselessly connected robotic agents. Centralized architectures enable mission awareness to all agents at all times, making tasks such as search and rescue more effective. The centralized component is placed on an edge server, ensuring low communication latency, while all agents access the server utilizing a fifth-generation (5G) network. In addition, the proposed solution introduces a communication-aware control function that regulates the transmissions of map instances to prevent the creation of significant data congestion and communication latencies as well as address conditions where the robotic agents traverse in limited to no coverage areas. The presented framework is agnostic of the used localization and mapping procedure, while it utilizes the full power of an edge server. Finally, the efficiency of the novel established framework is being experimentally validated based on multiple scenarios.
{"title":"Communication-Aware Control of Large Data Transmissions via Centralized Cognition and 5G Networks for Multi-Robot Map merging","authors":"Gerasimos Damigos, Nikolaos Stathoulopoulos, Anton Koval, Tore Lindgren, George Nikolakopoulos","doi":"10.1007/s10846-023-02045-4","DOIUrl":"https://doi.org/10.1007/s10846-023-02045-4","url":null,"abstract":"<p>Multiple modern robotic applications benefit from centralized cognition and processing schemes. However, modern equipped robotic platforms can output a large amount of data, which may exceed the capabilities of modern wireless communication systems if all data is transmitted without further consideration. This research presents a multi-agent, centralized, and real-time 3D point cloud map merging scheme for ceaselessly connected robotic agents. Centralized architectures enable mission awareness to all agents at all times, making tasks such as search and rescue more effective. The centralized component is placed on an edge server, ensuring low communication latency, while all agents access the server utilizing a fifth-generation (5G) network. In addition, the proposed solution introduces a communication-aware control function that regulates the transmissions of map instances to prevent the creation of significant data congestion and communication latencies as well as address conditions where the robotic agents traverse in limited to no coverage areas. The presented framework is agnostic of the used localization and mapping procedure, while it utilizes the full power of an edge server. Finally, the efficiency of the novel established framework is being experimentally validated based on multiple scenarios.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"33 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139561036","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}
Pub Date : 2024-01-24DOI: 10.1007/s10846-023-02040-9
Simone Martini, Kimon P. Valavanis, Margareta Stefanovic, Matthew J. Rutherford, Alessandro Rizzo
This technical note proves analytically how the exact equivalence of the Newton-Euler and Euler-Lagrange modeling formulations as applied to multirotor UAVs is achieved. This is done by deriving a correct Euler-Lagrange multirotor attitude dynamics model. A review of the published literature reveals that the commonly adopted Euler-Lagrange multirotor dynamics model is equivalent to the Newton-Euler model only when it comes to the position dynamics, but not in the attitude dynamics. Step-by-step derivations and calculations are provided to show how modeling equivalence to the Newton-Euler formulation is proven. The modeling equivalence is then verified by obtaining identical results in numerical simulation studies. Simulation results also illustrate that when using the correct model for feedback linearization, controller stability at high gains is improved.
{"title":"Correction to the Euler Lagrange Multirotor Model with Euler Angles Generalized Coordinates","authors":"Simone Martini, Kimon P. Valavanis, Margareta Stefanovic, Matthew J. Rutherford, Alessandro Rizzo","doi":"10.1007/s10846-023-02040-9","DOIUrl":"https://doi.org/10.1007/s10846-023-02040-9","url":null,"abstract":"<p>This technical note proves analytically how the exact equivalence of the Newton-Euler and Euler-Lagrange modeling formulations as applied to multirotor UAVs is achieved. This is done by deriving a correct Euler-Lagrange multirotor attitude dynamics model. A review of the published literature reveals that the commonly adopted Euler-Lagrange multirotor dynamics model is equivalent to the Newton-Euler model only when it comes to the position dynamics, but not in the attitude dynamics. Step-by-step derivations and calculations are provided to show how modeling equivalence to the Newton-Euler formulation is proven. The modeling equivalence is then verified by obtaining identical results in numerical simulation studies. Simulation results also illustrate that when using the correct model for feedback linearization, controller stability at high gains is improved.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"16 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139561038","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}