Pub Date : 2023-10-31DOI: 10.1007/s10846-023-01983-3
Yue Wang, Huajian Song, Yingxue Du, Jianlong Qiu, Ancai Zhang
{"title":"A Complete Analytical Solution to Hand-Eye Calibration Using Quaternions and Eigenvector-Eigenvalue Identity","authors":"Yue Wang, Huajian Song, Yingxue Du, Jianlong Qiu, Ancai Zhang","doi":"10.1007/s10846-023-01983-3","DOIUrl":"https://doi.org/10.1007/s10846-023-01983-3","url":null,"abstract":"","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135870919","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 : 2023-10-31DOI: 10.1007/s10846-023-01970-8
Grzegorz Bartyzel, Wojciech Półchłopek, Dominik Rzepka
Abstract In modern manufacturing, assembly tasks are a major challenge for robotics. In the manufacturing industry, a wide range of insertion tasks can be found, from peg-in-hole insertion to electronic parts assembly. Robotic stations designed for this problem often use conventional hybrid force-position control to perform preprogrammed trajectories, such as e.g. a spiral path. However, electronic parts require more sophisticated techniques due to their complex geometry and susceptibility to damage. Production line assembly tasks require high robustness to initial position and rotation variations due to component grip imperfections. Robustness to partially obscured camera view is also mandatory due to multi stage assembly process. We propose a stereo-view method based on reinforcement learning (RL) for the robust assembly of electronic parts. Applicability of our method to real-world production lines is verified through test scenarios. Our approach is the most robust to applied perturbations of all tested methods and can potentially be transferred to environments unseen during learning.
{"title":"Reinforcement Learning With Stereo-View Observation for Robust Electronic Component Robotic Insertion","authors":"Grzegorz Bartyzel, Wojciech Półchłopek, Dominik Rzepka","doi":"10.1007/s10846-023-01970-8","DOIUrl":"https://doi.org/10.1007/s10846-023-01970-8","url":null,"abstract":"Abstract In modern manufacturing, assembly tasks are a major challenge for robotics. In the manufacturing industry, a wide range of insertion tasks can be found, from peg-in-hole insertion to electronic parts assembly. Robotic stations designed for this problem often use conventional hybrid force-position control to perform preprogrammed trajectories, such as e.g. a spiral path. However, electronic parts require more sophisticated techniques due to their complex geometry and susceptibility to damage. Production line assembly tasks require high robustness to initial position and rotation variations due to component grip imperfections. Robustness to partially obscured camera view is also mandatory due to multi stage assembly process. We propose a stereo-view method based on reinforcement learning (RL) for the robust assembly of electronic parts. Applicability of our method to real-world production lines is verified through test scenarios. Our approach is the most robust to applied perturbations of all tested methods and can potentially be transferred to environments unseen during learning.","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135813608","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 : 2023-10-26DOI: 10.1007/s10846-023-01969-1
Donald Costello, Levi DeVries, Caleb Mauldin, Benjamin Ross
{"title":"DNN Based Ranging in Support of Autonomous Aerial Refueling","authors":"Donald Costello, Levi DeVries, Caleb Mauldin, Benjamin Ross","doi":"10.1007/s10846-023-01969-1","DOIUrl":"https://doi.org/10.1007/s10846-023-01969-1","url":null,"abstract":"","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134908542","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 : 2023-10-26DOI: 10.1007/s10846-023-01985-1
Zhaozhen Jiang, Wenlong Wang, Wenqi Sun, Lianglong Da
{"title":"Path Planning Method for Mobile Robot Based on a Hybrid Algorithm","authors":"Zhaozhen Jiang, Wenlong Wang, Wenqi Sun, Lianglong Da","doi":"10.1007/s10846-023-01985-1","DOIUrl":"https://doi.org/10.1007/s10846-023-01985-1","url":null,"abstract":"","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"3 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134909428","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 : 2023-10-26DOI: 10.1007/s10846-023-01979-z
Haolin Chen, Ruidong Wu, Wenshuai Lu, Xinglong Ji, Tao Wang, Haolun Ding, Yuxiang Dai, Bing Liu
{"title":"Fully Onboard Single Pedestrian Tracking on Nano-UAV Platform","authors":"Haolin Chen, Ruidong Wu, Wenshuai Lu, Xinglong Ji, Tao Wang, Haolun Ding, Yuxiang Dai, Bing Liu","doi":"10.1007/s10846-023-01979-z","DOIUrl":"https://doi.org/10.1007/s10846-023-01979-z","url":null,"abstract":"","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"113 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136381911","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 : 2023-10-21DOI: 10.1007/s10846-023-01971-7
Binh T. Nguyen, Linh Nguyen, Tanveer A. Choudhury, Kathleen Keogh, Manzur Murshed
Abstract By utilizing only depth information, the paper introduces a novel two-stage planning approach that enhances computational efficiency and planning performances for memoryless local planners. First, a depth-based sampling technique is proposed to identify and eliminate a specific type of in-collision trajectories among sampled candidates. Specifically, all trajectories that have obscured endpoints are found through querying the depth values and will then be excluded from the sampled set, which can significantly reduce the computational workload required in collision checking. Subsequently, we apply a tailored local planning algorithm that employs a direction cost function and a depth-based steering mechanism to prevent the robot from being trapped in local minima. Our planning algorithm is theoretically proven to be complete in convex obstacle scenarios. To validate the effectiveness of our DEpth-based both Sampling and Steering (DESS) approaches, we conducted experiments in simulated environments where a quadrotor flew through cluttered regions with multiple various-sized obstacles. The experimental results show that DESS significantly reduces computation time in local planning compared to the uniform sampling method, resulting in the planned trajectory with a lower minimized cost. More importantly, our success rates for navigation to different destinations in testing scenarios are improved considerably compared to the fixed-yawing approach.
{"title":"Depth-based Sampling and Steering Constraints for Memoryless Local Planners","authors":"Binh T. Nguyen, Linh Nguyen, Tanveer A. Choudhury, Kathleen Keogh, Manzur Murshed","doi":"10.1007/s10846-023-01971-7","DOIUrl":"https://doi.org/10.1007/s10846-023-01971-7","url":null,"abstract":"Abstract By utilizing only depth information, the paper introduces a novel two-stage planning approach that enhances computational efficiency and planning performances for memoryless local planners. First, a depth-based sampling technique is proposed to identify and eliminate a specific type of in-collision trajectories among sampled candidates. Specifically, all trajectories that have obscured endpoints are found through querying the depth values and will then be excluded from the sampled set, which can significantly reduce the computational workload required in collision checking. Subsequently, we apply a tailored local planning algorithm that employs a direction cost function and a depth-based steering mechanism to prevent the robot from being trapped in local minima. Our planning algorithm is theoretically proven to be complete in convex obstacle scenarios. To validate the effectiveness of our DEpth-based both Sampling and Steering (DESS) approaches, we conducted experiments in simulated environments where a quadrotor flew through cluttered regions with multiple various-sized obstacles. The experimental results show that DESS significantly reduces computation time in local planning compared to the uniform sampling method, resulting in the planned trajectory with a lower minimized cost. More importantly, our success rates for navigation to different destinations in testing scenarios are improved considerably compared to the fixed-yawing approach.","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"109 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135513230","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 : 2023-10-01DOI: 10.1007/s10846-023-01956-6
Yue Lu, Chao Guo, Yong Dou, Xingyuan Dai, Fei-Yue Wang
{"title":"Could ChatGPT Imagine: Content Control for Artistic Painting Generation Via Large Language Models","authors":"Yue Lu, Chao Guo, Yong Dou, Xingyuan Dai, Fei-Yue Wang","doi":"10.1007/s10846-023-01956-6","DOIUrl":"https://doi.org/10.1007/s10846-023-01956-6","url":null,"abstract":"","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135762714","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}
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