Pub Date : 2023-09-30DOI: 10.3390/robotics12050137
Georgios Petrakis, Panagiotis Partsinevelos
Feature extraction plays a crucial role in computer vision and autonomous navigation, offering valuable information for real-time localization and scene understanding. However, although multiple studies investigate keypoint detection and description algorithms in urban and indoor environments, far fewer studies concentrate in unstructured environments. In this study, a multi-task deep learning architecture is developed for keypoint detection and description, focused on poor-featured unstructured and planetary scenes with low or changing illumination. The proposed architecture was trained and evaluated using a training and benchmark dataset with earthy and planetary scenes. Moreover, the trained model was integrated in a visual SLAM (Simultaneous Localization and Maping) system as a feature extraction module, and tested in two feature-poor unstructured areas. Regarding the results, the proposed architecture provides a mAP (mean Average Precision) in a level of 0.95 in terms of keypoint description, outperforming well-known handcrafted algorithms while the proposed SLAM achieved two times lower RMSE error in a poor-featured area with low illumination, compared with ORB-SLAM2. To the best of the authors’ knowledge, this is the first study that investigates the potential of keypoint detection and description through deep learning in unstructured and planetary environments.
特征提取在计算机视觉和自主导航中起着至关重要的作用，为实时定位和场景理解提供了有价值的信息。然而，尽管有许多研究对城市和室内环境中的关键点检测和描述算法进行了研究，但集中在非结构化环境中的研究要少得多。在本研究中，开发了一种多任务深度学习架构，用于关键点检测和描述，重点关注低照度或不断变化的低特征非结构化和行星场景。使用地球和行星场景的训练和基准数据集对所提出的架构进行了训练和评估。此外，将训练好的模型作为特征提取模块集成到视觉SLAM (Simultaneous Localization and mapping)系统中，并在两个特征缺乏的非结构化区域进行测试。结果表明，在关键点描述方面，本文提出的架构提供了0.95的mAP (mean Average Precision)，优于知名的手工算法，而在低光照条件下特征较差的区域，与ORB-SLAM2相比，本文提出的SLAM的RMSE误差降低了两倍。据作者所知，这是第一项通过深度学习在非结构化和行星环境中调查关键点检测和描述潜力的研究。
{"title":"Keypoint Detection and Description through Deep Learning in Unstructured Environments","authors":"Georgios Petrakis, Panagiotis Partsinevelos","doi":"10.3390/robotics12050137","DOIUrl":"https://doi.org/10.3390/robotics12050137","url":null,"abstract":"Feature extraction plays a crucial role in computer vision and autonomous navigation, offering valuable information for real-time localization and scene understanding. However, although multiple studies investigate keypoint detection and description algorithms in urban and indoor environments, far fewer studies concentrate in unstructured environments. In this study, a multi-task deep learning architecture is developed for keypoint detection and description, focused on poor-featured unstructured and planetary scenes with low or changing illumination. The proposed architecture was trained and evaluated using a training and benchmark dataset with earthy and planetary scenes. Moreover, the trained model was integrated in a visual SLAM (Simultaneous Localization and Maping) system as a feature extraction module, and tested in two feature-poor unstructured areas. Regarding the results, the proposed architecture provides a mAP (mean Average Precision) in a level of 0.95 in terms of keypoint description, outperforming well-known handcrafted algorithms while the proposed SLAM achieved two times lower RMSE error in a poor-featured area with low illumination, compared with ORB-SLAM2. To the best of the authors’ knowledge, this is the first study that investigates the potential of keypoint detection and description through deep learning in unstructured and planetary environments.","PeriodicalId":37568,"journal":{"name":"Robotics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136343642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.3390/robotics12050134
Sherif Mostafa, Alejandro Ramirez-Serrano
To deploy Unmanned Aerial Vehicles (UAVs) inside heterogeneous GPS-denied confined (potentially unknown) spaces, such as those encountered in mining and Urban Search and Rescue (USAR), requires the enhancement of numerous technologies. Of special interest is for UAVs to identify collision-freeSafe Flight Corridors (SFC+) within highly cluttered convex- and non-convex-shaped environments, which requires UAVs to perform advanced flight maneuvers while exploiting their flying capabilities. Within this paper, a novel auxiliary occupancy checking process that augments traditional 3D flight corridor generation is proposed. The 3D flight corridor is established as a topological structure based on a hand-crafted path either derived from a computer-generated environment or provided by the human operator, which captures humans’ preferences and desired flight intentions for the given space. This corridor is formulated as a series of interconnected overlapping convex polyhedra bounded by the perceived environmental geometries, which facilitates the generation of suitable 3D flight paths/trajectories that avoid local minima within the corridor boundaries. An occupancy check algorithm is employed to reduce the search space needed to identify 3D obstacle-free spaces in which their constructed polyhedron geometries are replaced with alternate convex polyhedra. To assess the feasibility and efficiency of the proposed SFC+ methodology, a comparative study is conducted against the Star-Convex Method (SCM), a prominent algorithm in the field. The results reveal the superiority of the proposed SFC+ methodology in terms of its computational efficiency and reduced search space for UAV maneuvering solutions. Various challenging confined-environment scenarios, each with different obstacle densities (confined scenarios), are utilized to verify the obtained outcomes.
{"title":"Three-Dimensional Flight Corridor: An Occupancy Checking Process for Unmanned Aerial Vehicle Motion Planning Inside Confined Spaces","authors":"Sherif Mostafa, Alejandro Ramirez-Serrano","doi":"10.3390/robotics12050134","DOIUrl":"https://doi.org/10.3390/robotics12050134","url":null,"abstract":"To deploy Unmanned Aerial Vehicles (UAVs) inside heterogeneous GPS-denied confined (potentially unknown) spaces, such as those encountered in mining and Urban Search and Rescue (USAR), requires the enhancement of numerous technologies. Of special interest is for UAVs to identify collision-freeSafe Flight Corridors (SFC+) within highly cluttered convex- and non-convex-shaped environments, which requires UAVs to perform advanced flight maneuvers while exploiting their flying capabilities. Within this paper, a novel auxiliary occupancy checking process that augments traditional 3D flight corridor generation is proposed. The 3D flight corridor is established as a topological structure based on a hand-crafted path either derived from a computer-generated environment or provided by the human operator, which captures humans’ preferences and desired flight intentions for the given space. This corridor is formulated as a series of interconnected overlapping convex polyhedra bounded by the perceived environmental geometries, which facilitates the generation of suitable 3D flight paths/trajectories that avoid local minima within the corridor boundaries. An occupancy check algorithm is employed to reduce the search space needed to identify 3D obstacle-free spaces in which their constructed polyhedron geometries are replaced with alternate convex polyhedra. To assess the feasibility and efficiency of the proposed SFC+ methodology, a comparative study is conducted against the Star-Convex Method (SCM), a prominent algorithm in the field. The results reveal the superiority of the proposed SFC+ methodology in terms of its computational efficiency and reduced search space for UAV maneuvering solutions. Various challenging confined-environment scenarios, each with different obstacle densities (confined scenarios), are utilized to verify the obtained outcomes.","PeriodicalId":37568,"journal":{"name":"Robotics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135246697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recent advancements in artificial intelligence have enabled reinforcement learning (RL) agents to exceed human-level performance in various gaming tasks. However, despite the state-of-the-art performance demonstrated by model-free RL algorithms, they suffer from high sample complexity. Hence, it is uncommon to find their applications in robotics, autonomous navigation, and self-driving, as gathering many samples is impractical in real-world hardware systems. Therefore, developing sample-efficient learning algorithms for RL agents is crucial in deploying them in real-world tasks without sacrificing performance. This paper presents an advisor-based learning algorithm, incorporating prior knowledge into the training by modifying the deep deterministic policy gradient algorithm to reduce the sample complexity. Also, we propose an effective method of employing an advisor in data collection to train autonomous navigation agents to maneuver physical platforms, minimizing the risk of collision. We analyze the performance of our methods with the support of simulation and physical experimental setups. Experiments reveal that incorporating an advisor into the training phase significantly reduces the sample complexity without compromising the agent’s performance compared to various benchmark approaches. Also, they show that the advisor’s constant involvement in the data collection process diminishes the agent’s performance, while the limited involvement makes training more effective.
{"title":"An Advisor-Based Architecture for a Sample-Efficient Training of Autonomous Navigation Agents with Reinforcement Learning","authors":"Rukshan Darshana Wijesinghe, Dumindu Tissera, Mihira Kasun Vithanage, Alex Xavier, Subha Fernando, Jayathu Samarawickrama","doi":"10.3390/robotics12050133","DOIUrl":"https://doi.org/10.3390/robotics12050133","url":null,"abstract":"Recent advancements in artificial intelligence have enabled reinforcement learning (RL) agents to exceed human-level performance in various gaming tasks. However, despite the state-of-the-art performance demonstrated by model-free RL algorithms, they suffer from high sample complexity. Hence, it is uncommon to find their applications in robotics, autonomous navigation, and self-driving, as gathering many samples is impractical in real-world hardware systems. Therefore, developing sample-efficient learning algorithms for RL agents is crucial in deploying them in real-world tasks without sacrificing performance. This paper presents an advisor-based learning algorithm, incorporating prior knowledge into the training by modifying the deep deterministic policy gradient algorithm to reduce the sample complexity. Also, we propose an effective method of employing an advisor in data collection to train autonomous navigation agents to maneuver physical platforms, minimizing the risk of collision. We analyze the performance of our methods with the support of simulation and physical experimental setups. Experiments reveal that incorporating an advisor into the training phase significantly reduces the sample complexity without compromising the agent’s performance compared to various benchmark approaches. Also, they show that the advisor’s constant involvement in the data collection process diminishes the agent’s performance, while the limited involvement makes training more effective.","PeriodicalId":37568,"journal":{"name":"Robotics","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135387723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-27DOI: 10.3390/robotics12050132
Sandra Drolshagen, Max Pfingsthorn, Andreas Hein
People with disabilities are severely underrepresented in the open labor market. Yet, pursuing a job has a positive impact in many aspects of life. This paper presents a possible approach to improve inclusion by including a robotic manipulator into context-aware Assistive Systems. This expands the assistance possibilities tremendously by adding gesture-based feedback and aid. The system presented is based on the intelligent control system of behavior trees, which—together with a depth camera, specifically designed policies, and a collaborative industrial robotic manipulator—can assist workers with disabilities in the workplace. A developed assistance node generates personalized action sequences. These include different robotic pointing gestures, from simple waving, to precisely indicating the target position of the workpiece during assembly tasks. This paper describes the design challenges and technical implementation of the first Context-Aware Robotic Assistive System. Moreover, an in-field user study in a Sheltered Workshop was performed to verify the concept and developed algorithms. In the assembly task under consideration, almost three times as many parts could be assembled with the developed system than with the baseline condition. In addition, the reactions and statements of the participants showed that the robot was considered and accepted as a tutor.
{"title":"Context-Aware Robotic Assistive System: Robotic Pointing Gesture-Based Assistance for People with Disabilities in Sheltered Workshops","authors":"Sandra Drolshagen, Max Pfingsthorn, Andreas Hein","doi":"10.3390/robotics12050132","DOIUrl":"https://doi.org/10.3390/robotics12050132","url":null,"abstract":"People with disabilities are severely underrepresented in the open labor market. Yet, pursuing a job has a positive impact in many aspects of life. This paper presents a possible approach to improve inclusion by including a robotic manipulator into context-aware Assistive Systems. This expands the assistance possibilities tremendously by adding gesture-based feedback and aid. The system presented is based on the intelligent control system of behavior trees, which—together with a depth camera, specifically designed policies, and a collaborative industrial robotic manipulator—can assist workers with disabilities in the workplace. A developed assistance node generates personalized action sequences. These include different robotic pointing gestures, from simple waving, to precisely indicating the target position of the workpiece during assembly tasks. This paper describes the design challenges and technical implementation of the first Context-Aware Robotic Assistive System. Moreover, an in-field user study in a Sheltered Workshop was performed to verify the concept and developed algorithms. In the assembly task under consideration, almost three times as many parts could be assembled with the developed system than with the baseline condition. In addition, the reactions and statements of the participants showed that the robot was considered and accepted as a tutor.","PeriodicalId":37568,"journal":{"name":"Robotics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135579746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-20DOI: 10.3390/robotics12050131
Victoria E. Abarca, Dante A. Elias
This review article presents an in-depth examination of research and development in the fields of rehabilitation, assistive technologies, and humanoid robots. It focuses on parallel robots designed for human body joints with three degrees of freedom, specifically the neck, shoulder, wrist, hip, and ankle. A systematic search was conducted across multiple databases, including Scopus, Web of Science, PubMed, IEEE Xplore, ScienceDirect, the Directory of Open Access Journals, and the ASME Journal. This systematic review offers an updated overview of advancements in the field from 2012 to 2023. After applying exclusion criteria, 93 papers were selected for in-depth review. This cohort included 13 articles focusing on the neck joint, 19 on the shoulder joint, 22 on the wrist joint, 9 on the hip joint, and 30 on the ankle joint. The article discusses the timeline and advancements of parallel robots, covering technology readiness levels (TRLs), design, the number of degrees of freedom, kinematics structure, workspace assessment, functional capabilities, performance evaluation methods, and material selection for the development of parallel robotics. It also examines critical technological challenges and future prospects in rehabilitation, assistance, and humanoid robots.
这篇综述文章介绍了在康复、辅助技术和类人机器人领域的研究和发展的深入检查。它的重点是为人体关节设计的三自由度并联机器人，即颈部、肩部、手腕、臀部和脚踝。系统检索了多个数据库，包括Scopus、Web of Science、PubMed、IEEE Xplore、ScienceDirect、Open Access Journals Directory和ASME Journal。本系统综述提供了2012年至2023年该领域进展的最新概述。应用排除标准后，选择93篇论文进行深入审查。该队列包括13篇关于颈部关节的文章，19篇关于肩关节的文章，22篇关于腕关节的文章，9篇关于髋关节的文章，30篇关于踝关节的文章。本文讨论了并联机器人的时间线和进展，涵盖了技术准备水平(trl)、设计、自由度数量、运动学结构、工作空间评估、功能能力、性能评估方法和并联机器人开发的材料选择。它还探讨了关键的技术挑战和未来的前景在康复，援助和人形机器人。
{"title":"A Review of Parallel Robots: Rehabilitation, Assistance, and Humanoid Applications for Neck, Shoulder, Wrist, Hip, and Ankle Joints","authors":"Victoria E. Abarca, Dante A. Elias","doi":"10.3390/robotics12050131","DOIUrl":"https://doi.org/10.3390/robotics12050131","url":null,"abstract":"This review article presents an in-depth examination of research and development in the fields of rehabilitation, assistive technologies, and humanoid robots. It focuses on parallel robots designed for human body joints with three degrees of freedom, specifically the neck, shoulder, wrist, hip, and ankle. A systematic search was conducted across multiple databases, including Scopus, Web of Science, PubMed, IEEE Xplore, ScienceDirect, the Directory of Open Access Journals, and the ASME Journal. This systematic review offers an updated overview of advancements in the field from 2012 to 2023. After applying exclusion criteria, 93 papers were selected for in-depth review. This cohort included 13 articles focusing on the neck joint, 19 on the shoulder joint, 22 on the wrist joint, 9 on the hip joint, and 30 on the ankle joint. The article discusses the timeline and advancements of parallel robots, covering technology readiness levels (TRLs), design, the number of degrees of freedom, kinematics structure, workspace assessment, functional capabilities, performance evaluation methods, and material selection for the development of parallel robotics. It also examines critical technological challenges and future prospects in rehabilitation, assistance, and humanoid robots.","PeriodicalId":37568,"journal":{"name":"Robotics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136312833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-14DOI: 10.3390/robotics12050130
Javier González Huarte, Maite Ortiz de Zarate, Aitor Ibarguren
Wire harness manufacturing in the aeronautic sector is highly manual work, with production defined by multiple references and small batches. Although complete automation of the production process is not feasible, a robot-assisted approach could increase the efficiency of the existing production means. This paper presents a novel dual-arm robotic solution for workbench configuration and cable routing during the initial steps of wire harness manufacturing. Based on the CAD information of the wire harness, the proposed framework generates trajectories in real-time to complete the initial manufacturing tasks, dividing automatically the whole job between both robots. The presented approach has been validated in a production environment using different wire harness references, obtaining promising results and metrics.
{"title":"CAD-Based Robot Programming Solution for Wire Harness Manufacturing in Aeronautic Sector","authors":"Javier González Huarte, Maite Ortiz de Zarate, Aitor Ibarguren","doi":"10.3390/robotics12050130","DOIUrl":"https://doi.org/10.3390/robotics12050130","url":null,"abstract":"Wire harness manufacturing in the aeronautic sector is highly manual work, with production defined by multiple references and small batches. Although complete automation of the production process is not feasible, a robot-assisted approach could increase the efficiency of the existing production means. This paper presents a novel dual-arm robotic solution for workbench configuration and cable routing during the initial steps of wire harness manufacturing. Based on the CAD information of the wire harness, the proposed framework generates trajectories in real-time to complete the initial manufacturing tasks, dividing automatically the whole job between both robots. The presented approach has been validated in a production environment using different wire harness references, obtaining promising results and metrics.","PeriodicalId":37568,"journal":{"name":"Robotics","volume":"254 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134914423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-11DOI: 10.3390/robotics12050128
Safeh Clinton Mawah, Yong-Jai Park
In recent times, the soft robotics field has been attracting significant research focus owing to its high level of manipulation capabilities unlike traditional rigid robots, which gives room for increasing use in other areas. However, compared to traditional rigid gripper robots, being capable of controlling/obtaining overall body stiffness when required is yet to be further explored since soft gripper robots have inherently less-rigid properties. Unlike previous designs with very complex variable-stiffness systems, this paper demonstrates a soft gripper design with minimum system complexity while being capable of varying the stiffness of a continuum soft robotic actuator and proves to have potential applications in gripping objects of various shapes, weights, and sizes. The soft gripper actuator comprises two separate mechanisms: the pneumatic mechanism for bending control and the mechanical structure for stiffness variation by pulling tendons using stepper motors which compresses the actuator, thereby changing the overall stiffness. The pneumatic mechanism was first fabricated and then embedded into another silicon layer during which it was also merged with the mechanical structure for stiffness control. By first pneumatically actuating the actuator which causes bending and then pulling the tendons, we found out that the actuator stiffness value can be increased up to 145% its initial value, and the gripper can grasp and lift a weight of up to 2.075 kg.
{"title":"Tendon-Driven Variable-Stiffness Pneumatic Soft Gripper Robot","authors":"Safeh Clinton Mawah, Yong-Jai Park","doi":"10.3390/robotics12050128","DOIUrl":"https://doi.org/10.3390/robotics12050128","url":null,"abstract":"In recent times, the soft robotics field has been attracting significant research focus owing to its high level of manipulation capabilities unlike traditional rigid robots, which gives room for increasing use in other areas. However, compared to traditional rigid gripper robots, being capable of controlling/obtaining overall body stiffness when required is yet to be further explored since soft gripper robots have inherently less-rigid properties. Unlike previous designs with very complex variable-stiffness systems, this paper demonstrates a soft gripper design with minimum system complexity while being capable of varying the stiffness of a continuum soft robotic actuator and proves to have potential applications in gripping objects of various shapes, weights, and sizes. The soft gripper actuator comprises two separate mechanisms: the pneumatic mechanism for bending control and the mechanical structure for stiffness variation by pulling tendons using stepper motors which compresses the actuator, thereby changing the overall stiffness. The pneumatic mechanism was first fabricated and then embedded into another silicon layer during which it was also merged with the mechanical structure for stiffness control. By first pneumatically actuating the actuator which causes bending and then pulling the tendons, we found out that the actuator stiffness value can be increased up to 145% its initial value, and the gripper can grasp and lift a weight of up to 2.075 kg.","PeriodicalId":37568,"journal":{"name":"Robotics","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135979750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-11DOI: 10.3390/robotics12050129
Liping Wang, Mengyu Li, Guang Yu
Geometric errors are the main factors affecting the output accuracy of the parallel spindle head, and it is necessary to perform a sensitivity analysis to extract the critical geometric errors. The traditional sensitivity analysis method analyzes the output position and orientation errors independently, defining multiple sensitivity indices and making it difficult to determine critical geometric errors. In this paper, we propose sensitivity indices that can comprehensively consider position and orientation errors. First, the configuration of the hybrid machine tool is introduced, and the TCP position error model is derived. Then, the tool radius and the effective cutting length are introduced, and the sensitivity indices are defined. After that, the sensitivity analysis of the 3-DOF parallel spindle head is performed using the proposed sensitivity indices, and six critical geometric errors are extracted. The machining accuracy of the parallel spindle head can be greatly improved by improving the critical geometric errors. The proposed sensitivity analysis method can provide important guidance for machine tool accuracy design.
{"title":"A Novel Error Sensitivity Analysis Method for a Parallel Spindle Head","authors":"Liping Wang, Mengyu Li, Guang Yu","doi":"10.3390/robotics12050129","DOIUrl":"https://doi.org/10.3390/robotics12050129","url":null,"abstract":"Geometric errors are the main factors affecting the output accuracy of the parallel spindle head, and it is necessary to perform a sensitivity analysis to extract the critical geometric errors. The traditional sensitivity analysis method analyzes the output position and orientation errors independently, defining multiple sensitivity indices and making it difficult to determine critical geometric errors. In this paper, we propose sensitivity indices that can comprehensively consider position and orientation errors. First, the configuration of the hybrid machine tool is introduced, and the TCP position error model is derived. Then, the tool radius and the effective cutting length are introduced, and the sensitivity indices are defined. After that, the sensitivity analysis of the 3-DOF parallel spindle head is performed using the proposed sensitivity indices, and six critical geometric errors are extracted. The machining accuracy of the parallel spindle head can be greatly improved by improving the critical geometric errors. The proposed sensitivity analysis method can provide important guidance for machine tool accuracy design.","PeriodicalId":37568,"journal":{"name":"Robotics","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136023685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-26DOI: 10.3390/robotics12040108
Alejandro Magaña, Jonas Dirr, Philipp Bauer, Gunther Reinhart
The efficient computation of viewpoints while considering various system and process constraints is a common challenge that any robot vision system is confronted with when trying to execute a vision task. Although fundamental research has provided solid and sound solutions for tackling this problem, a holistic framework that poses its formal description, considers the heterogeneity of robot vision systems, and offers an integrated solution remains unaddressed. Hence, this publication outlines the generation of viewpoints as a geometrical problem and introduces a generalized theoretical framework based on Feature-Based Constrained Spaces (C-spaces) as the backbone for solving it. A C-space can be understood as the topological space that a viewpoint constraint spans, where the sensor can be positioned for acquiring a feature while fulfilling the constraint. The present study demonstrates that many viewpoint constraints can be efficiently formulated as C-spaces, providing geometric, deterministic, and closed solutions. The introduced C-spaces are characterized based on generic domain and viewpoint constraints models to ease the transferability of the present framework to different applications and robot vision systems. The effectiveness and efficiency of the concepts introduced are verified on a simulation-based scenario and validated on a real robot vision system comprising two different sensors.
{"title":"Viewpoint Generation Using Feature-Based Constrained Spaces for Robot Vision Systems","authors":"Alejandro Magaña, Jonas Dirr, Philipp Bauer, Gunther Reinhart","doi":"10.3390/robotics12040108","DOIUrl":"https://doi.org/10.3390/robotics12040108","url":null,"abstract":"The efficient computation of viewpoints while considering various system and process constraints is a common challenge that any robot vision system is confronted with when trying to execute a vision task. Although fundamental research has provided solid and sound solutions for tackling this problem, a holistic framework that poses its formal description, considers the heterogeneity of robot vision systems, and offers an integrated solution remains unaddressed. Hence, this publication outlines the generation of viewpoints as a geometrical problem and introduces a generalized theoretical framework based on Feature-Based Constrained Spaces (C-spaces) as the backbone for solving it. A C-space can be understood as the topological space that a viewpoint constraint spans, where the sensor can be positioned for acquiring a feature while fulfilling the constraint. The present study demonstrates that many viewpoint constraints can be efficiently formulated as C-spaces, providing geometric, deterministic, and closed solutions. The introduced C-spaces are characterized based on generic domain and viewpoint constraints models to ease the transferability of the present framework to different applications and robot vision systems. The effectiveness and efficiency of the concepts introduced are verified on a simulation-based scenario and validated on a real robot vision system comprising two different sensors.","PeriodicalId":37568,"journal":{"name":"Robotics","volume":"652 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135800789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.3390/robotics12030066
Mohammad Shushtari, Arash Arami
Accurate interaction force estimation can play an important role in optimizing human–robot interaction in an exoskeleton. In this work, we propose a novel approach for the system identification of exoskeleton dynamics in the presence of interaction forces as a whole multibody system without imposing any constraints on the exoskeleton dynamics. We hung the exoskeleton through a linear spring and excited the exoskeleton joints with chirp commands while measuring the exoskeleton–environment interaction force. Several structures of neural networks were trained to model the exoskeleton passive dynamics and estimate the interaction force. Our testing results indicated that a deep neural network with 250 neurons and 10 time–delays could obtain a sufficiently accurate estimation of the interaction force, resulting in an RMSE of 1.23 on Z–normalized applied torques and an adjusted R2 of 0.89.
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