Pub Date : 2024-10-11DOI: 10.1016/j.robot.2024.104830
Timur Akhtyamov , Aleksandr Kashirin , Aleksey Postnikov , Ivan Sosin , Gonzalo Ferrer
This paper provides an empirical evaluation, in both simulation and real scenarios, of the social navigation problem when considering human motion prediction and its stochastic effects. To this end, we study several different optimization criteria and constraints related to the uncertainty of predicting pedestrians’ motion, embedded into the Model Predictive Control (MPC) scheme.
The main research question of this work is the following: what are the most important uncertainty-based criteria for the social MPC both in simulated and real-world environments? In order to achieve a solid answer to this question, we extend the results previously obtained from our work (Akhtyamov et al., 2023) in the simulated environments and provide a real-world setting that mimics similar conditions, for a fair comparison of the qualitative and quantitative results.
The main conclusions supported by both of the evaluation environments are the advantages of using adaptive constraints as a clear undisputed enhancement and the problems raised when considering uncertainty-aware criteria. We hope this paper is of interest to the community for deciding and designing uncertainty-aware approaches for social robot navigation.
{"title":"Social robot navigation through constrained optimization: A comprehensive study of uncertainty-based objectives and constraints in the simulated and real world","authors":"Timur Akhtyamov , Aleksandr Kashirin , Aleksey Postnikov , Ivan Sosin , Gonzalo Ferrer","doi":"10.1016/j.robot.2024.104830","DOIUrl":"10.1016/j.robot.2024.104830","url":null,"abstract":"<div><div>This paper provides an empirical evaluation, in both simulation and real scenarios, of the social navigation problem when considering human motion prediction and its stochastic effects. To this end, we study several different optimization criteria and constraints related to the uncertainty of predicting pedestrians’ motion, embedded into the Model Predictive Control (MPC) scheme.</div><div>The main research question of this work is the following: what are the most important uncertainty-based criteria for the social MPC both in simulated and real-world environments? In order to achieve a solid answer to this question, we extend the results previously obtained from our work (Akhtyamov et al., 2023) in the simulated environments and provide a real-world setting that mimics similar conditions, for a fair comparison of the qualitative and quantitative results.</div><div>The main conclusions supported by both of the evaluation environments are the advantages of using <em>adaptive constraints</em> as a clear undisputed enhancement and the problems raised when considering uncertainty-aware criteria. We hope this paper is of interest to the community for deciding and designing uncertainty-aware approaches for social robot navigation.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"183 ","pages":"Article 104830"},"PeriodicalIF":4.3,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-11DOI: 10.1016/j.robot.2024.104826
Xinyan Tan , Lingxuan Xiong , Weimin Zhang , Zhengqing Zuo , Xiaohai He , Yi Xu , Fangxing Li
Automation technology can replace manual work in the traditional construction industry, improve quality and efficiency, and reduce costs. This paper developed a rebar-tying robot for tying the intersection of rebars. It proposed a Hough transform multi-segment fitting method to detect the intersections of rebars in real-time acquired RGB-D images. To cover the surface of the rebar net as much as possible under the condition of limited camera FOV, this paper designed a coverage path planning method to plan the path of the photo positions and the detected intersections of rebars efficiently and orderly. The experimental results show that the robot achieved an accuracy rate of 99.4 % in intersection detection, the detection error is within 2.8 mm, the single tying time is 1.85 s, and the average tying time is 5.5 s, which is faster than most robots. The robot realizes the task of automatically tying the intersection of rebars, which is robust and efficient, without duplication or omission.
{"title":"Rebar-tying Robot based on machine vision and coverage path planning","authors":"Xinyan Tan , Lingxuan Xiong , Weimin Zhang , Zhengqing Zuo , Xiaohai He , Yi Xu , Fangxing Li","doi":"10.1016/j.robot.2024.104826","DOIUrl":"10.1016/j.robot.2024.104826","url":null,"abstract":"<div><div>Automation technology can replace manual work in the traditional construction industry, improve quality and efficiency, and reduce costs. This paper developed a rebar-tying robot for tying the intersection of rebars. It proposed a Hough transform multi-segment fitting method to detect the intersections of rebars in real-time acquired RGB-D images. To cover the surface of the rebar net as much as possible under the condition of limited camera FOV, this paper designed a coverage path planning method to plan the path of the photo positions and the detected intersections of rebars efficiently and orderly. The experimental results show that the robot achieved an accuracy rate of 99.4 % in intersection detection, the detection error is within 2.8 mm, the single tying time is 1.85 s, and the average tying time is 5.5 s, which is faster than most robots. The robot realizes the task of automatically tying the intersection of rebars, which is robust and efficient, without duplication or omission.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"182 ","pages":"Article 104826"},"PeriodicalIF":4.3,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-10DOI: 10.1016/j.robot.2024.104821
Ali Noormohammadi-Asl, Kevin Fan, Stephen L. Smith, Kerstin Dautenhahn
Achieving effective and seamless human–robot collaboration requires two key outcomes: enhanced team performance and fostering a positive human perception of both the robot and the collaboration. This paper investigates the capability of the proposed task planning framework to realize these objectives by integrating human leading/following preferences and performance into its task allocation and scheduling processes. We designed a collaborative scenario wherein the robot autonomously collaborates with participants. The outcomes of the user study indicate that the proactive task planning framework successfully attains the aforementioned goals. We also explore the impact of participants’ leadership and followership styles on their collaboration. The results reveal intriguing relationships between these factors which warrant further investigation in future studies.
{"title":"Human leading or following preferences: Effects on human perception of the robot and the human–robot collaboration","authors":"Ali Noormohammadi-Asl, Kevin Fan, Stephen L. Smith, Kerstin Dautenhahn","doi":"10.1016/j.robot.2024.104821","DOIUrl":"10.1016/j.robot.2024.104821","url":null,"abstract":"<div><div>Achieving effective and seamless human–robot collaboration requires two key outcomes: enhanced team performance and fostering a positive human perception of both the robot and the collaboration. This paper investigates the capability of the proposed task planning framework to realize these objectives by integrating human leading/following preferences and performance into its task allocation and scheduling processes. We designed a collaborative scenario wherein the robot autonomously collaborates with participants. The outcomes of the user study indicate that the proactive task planning framework successfully attains the aforementioned goals. We also explore the impact of participants’ leadership and followership styles on their collaboration. The results reveal intriguing relationships between these factors which warrant further investigation in future studies.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"183 ","pages":"Article 104821"},"PeriodicalIF":4.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527724","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}
Vehicle being at fault in a crash has extensively been associated with its driver's behaviors and other human errors for human-driven vehicles (HDV). The introduction of automated vehicles (AVs) is expected to eliminate such human errors due to the ability of AVs to communicate with the external environment. However, various reports have documented AVs being at fault in collisions. This study applied text mining and mixed-effects logistic regression (MELR) on crash data involving AVs collected between 2017 and 2022 in California to explore the likelihood of an AV being at fault during a collision. It was found that among 497 crashes, a relatively small percentage (14.29 %) involved AVs being at fault. The text network results revealed patterns of keywords associated with the AVs being at fault. Such patterns include conventional mode of operation, area of impact, and resulting injuries. Furthermore, with about a 93 % prediction accuracy and an 83 % sensitivity score, the MELR results revealed that the likelihood of AVs being at fault increases when they are operated in conventional mode or when disengagement is involved. Moreover, turning, merging, or changing lane movements, unclear weather conditions, and operating on roadways with four or more lanes significantly increased the odds of an AV being at fault during a crash. Conversely, AVs were less likely to be at fault in commercial land use than residential land use, at intersection locations, and when the crash involved a truck. The practical implications of the findings are presented to improve AV operations.
{"title":"Navigating the blame game: Investigating automated vehicle fault in collisions under mixed traffic conditions","authors":"Boniphace Kutela , Jimoku Hinda Salum , Seif Rashidi Seif , Subasish Das , Emmanuel Kidando","doi":"10.1016/j.robot.2024.104831","DOIUrl":"10.1016/j.robot.2024.104831","url":null,"abstract":"<div><div>Vehicle being at fault in a crash has extensively been associated with its driver's behaviors and other human errors for human-driven vehicles (HDV). The introduction of automated vehicles (AVs) is expected to eliminate such human errors due to the ability of AVs to communicate with the external environment. However, various reports have documented AVs being at fault in collisions. This study applied text mining and mixed-effects logistic regression (MELR) on crash data involving AVs collected between 2017 and 2022 in California to explore the likelihood of an AV being at fault during a collision. It was found that among 497 crashes, a relatively small percentage (14.29 %) involved AVs being at fault. The text network results revealed patterns of keywords associated with the AVs being at fault. Such patterns include conventional mode of operation, area of impact, and resulting injuries. Furthermore, with about a 93 % prediction accuracy and an 83 % sensitivity score, the MELR results revealed that the likelihood of AVs being at fault increases when they are operated in conventional mode or when disengagement is involved. Moreover, turning, merging, or changing lane movements, unclear weather conditions, and operating on roadways with four or more lanes significantly increased the odds of an AV being at fault during a crash. Conversely, AVs were less likely to be at fault in commercial land use than residential land use, at intersection locations, and when the crash involved a truck. The practical implications of the findings are presented to improve AV operations.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"182 ","pages":"Article 104831"},"PeriodicalIF":4.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142432325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-10DOI: 10.1016/j.robot.2024.104829
Mohammad Farajtabar, Marie Charbonneau
With the advancements in human–robot interaction (HRI), robots are now capable of operating in close proximity and engaging in physical interactions with humans (pHRI). Likewise, contact-based pHRI is becoming increasingly common as robots are equipped with a range of sensors to perceive human motions. Despite the presence of surveys exploring various aspects of HRI and pHRI, there is presently a gap in comprehensive studies that collect, organize and relate developments across all aspects of contact-based pHRI. It has become challenging to gain a comprehensive understanding of the current state of the field, thoroughly analyze the aspects that have been covered, and identify areas needing further attention. Hence, the present survey. While it includes key developments in pHRI, a particular focus is placed on contact-based interaction, which has numerous applications in industrial, rehabilitation and medical robotics. Across the literature, a common denominator is the importance to establish a safe, compliant and human intention-oriented interaction. This endeavour encompasses aspects of perception, planning and control, and how they work together to enhance safety and reliability. Notably, the survey highlights the application of data-driven techniques: backed by a growing body of literature demonstrating their effectiveness, approaches like reinforcement learning and learning from demonstration have become key to improving robot perception and decision-making within complex and uncertain pHRI scenarios. This survey also stresses how little attention has yet been dedicated to ethical considerations surrounding pHRI, including the development of contact-based pHRI systems that are appropriate for people and society. As the field is yet in its early stage, these observations may help guide future developments and steer research towards the responsible integration of physically interactive robots into workplaces, public spaces, and elements of private life.
{"title":"The path towards contact-based physical human–robot interaction","authors":"Mohammad Farajtabar, Marie Charbonneau","doi":"10.1016/j.robot.2024.104829","DOIUrl":"10.1016/j.robot.2024.104829","url":null,"abstract":"<div><div>With the advancements in human–robot interaction (HRI), robots are now capable of operating in close proximity and engaging in physical interactions with humans (pHRI). Likewise, contact-based pHRI is becoming increasingly common as robots are equipped with a range of sensors to perceive human motions. Despite the presence of surveys exploring various aspects of HRI and pHRI, there is presently a gap in comprehensive studies that collect, organize and relate developments across all aspects of contact-based pHRI. It has become challenging to gain a comprehensive understanding of the current state of the field, thoroughly analyze the aspects that have been covered, and identify areas needing further attention. Hence, the present survey. While it includes key developments in pHRI, a particular focus is placed on contact-based interaction, which has numerous applications in industrial, rehabilitation and medical robotics. Across the literature, a common denominator is the importance to establish a safe, compliant and human intention-oriented interaction. This endeavour encompasses aspects of perception, planning and control, and how they work together to enhance safety and reliability. Notably, the survey highlights the application of data-driven techniques: backed by a growing body of literature demonstrating their effectiveness, approaches like reinforcement learning and learning from demonstration have become key to improving robot perception and decision-making within complex and uncertain pHRI scenarios. This survey also stresses how little attention has yet been dedicated to ethical considerations surrounding pHRI, including the development of contact-based pHRI systems that are appropriate for people and society. As the field is yet in its early stage, these observations may help guide future developments and steer research towards the responsible integration of physically interactive robots into workplaces, public spaces, and elements of private life.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"182 ","pages":"Article 104829"},"PeriodicalIF":4.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142432324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.robot.2024.104827
Enrico Mingo Hoffman , Andrea Curti , Narcis Miguel , Sai Kishor Kothakota , Alberto Molina , Adria Roig , Luca Marchionni
This paper presents the modeling and numerical analysis of the Kangaroo lower body prototype, a novel bipedal humanoid robot developed and manufactured by PAL Robotics. Kangaroo features high-power linear electric actuators combined with unique serial–parallel hybrid chains, which allow for the positioning of all the leg actuators near the base of the robot to improve the overall mass distribution. To model and analyze such complex nonlinear mechanisms, we employ a constrained formulation that is extended to account for floating-base systems in contact with the environment. A comparison is made to demonstrate the significant improvements achieved with TALOS, another humanoid bipedal robot designed by PAL Robotics, in terms of equivalent Cartesian inertia at the feet and centroidal angular momentum. Finally, the paper includes numerical experiments conducted through simulation and preliminary tests performed on the actual Kangaroo platform.
本文介绍了袋鼠下半身原型的建模和数值分析，袋鼠下半身原型是由 PAL 机器人公司开发和制造的新型双足仿人机器人。Kangaroo 采用大功率线性电动致动器，结合独特的串并联混合链，使所有腿部致动器都位于机器人底部附近，从而改善了整体质量分布。为了对这种复杂的非线性机制进行建模和分析，我们采用了一种约束公式，并对其进行了扩展，以考虑与环境接触的浮动基座系统。通过与 PAL Robotics 公司设计的另一款仿人双足机器人 TALOS 进行比较，证明了在脚部等效笛卡尔惯性和中心角动量方面取得的显著改进。最后，论文包括通过模拟进行的数值实验和在实际袋鼠平台上进行的初步测试。
{"title":"Modeling and numerical analysis of Kangaroo lower body based on constrained dynamics of hybrid serial–parallel floating-base systems","authors":"Enrico Mingo Hoffman , Andrea Curti , Narcis Miguel , Sai Kishor Kothakota , Alberto Molina , Adria Roig , Luca Marchionni","doi":"10.1016/j.robot.2024.104827","DOIUrl":"10.1016/j.robot.2024.104827","url":null,"abstract":"<div><div>This paper presents the modeling and numerical analysis of the Kangaroo lower body prototype, a novel bipedal humanoid robot developed and manufactured by PAL Robotics. Kangaroo features high-power linear electric actuators combined with unique serial–parallel hybrid chains, which allow for the positioning of all the leg actuators near the base of the robot to improve the overall mass distribution. To model and analyze such complex nonlinear mechanisms, we employ a constrained formulation that is extended to account for floating-base systems in contact with the environment. A comparison is made to demonstrate the significant improvements achieved with TALOS, another humanoid bipedal robot designed by PAL Robotics, in terms of equivalent Cartesian inertia at the feet and centroidal angular momentum. Finally, the paper includes numerical experiments conducted through simulation and preliminary tests performed on the actual Kangaroo platform.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"182 ","pages":"Article 104827"},"PeriodicalIF":4.3,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.robot.2024.104828
Zhuanzhuan Ma , Li Chen , Tian Liang , Jinguo Liu
A purely geometric planning method for a mobile robot in unknown environments is proposed to ensure collision avoidance with obstacles within the safety time interval while moving toward the goal. The robot initially detects a point cloud of obstacles using a 2D LiDAR. Euclidean clustering is employed to classify the point cloud into distinct point classes. Each point class is then identified as a directed closed-loop rectangle representing the obstacle. A relative orientation kd-tree is designed to store the vertices of the obstacles and determine which obstacles should be considered in the obstacle avoidance algorithm. A velocity divider is introduced to obtain a linear convex area of possible obstacle avoidance velocities. Linear planning is then used to calculate the optimal obstacle avoidance velocity for control. A virtual reference point method is proposed to address the problem of an unreachable goal in a singular configuration. Experimental results show that the directed closed-loop rectangle and relative orientation kd-tree facilitate rapid updates of required obstacle points with low-cost sensor equipment. A deterministic path for a given scenario is demonstrated, confirming the reliability of the geometric planning method for the obstacle avoidance velocity region and the optimal obstacle avoidance velocity. The proposed algorithm is further validated in scenarios with multiple obstacles and dynamic environments involving moving obstacles.
{"title":"Collision-free tracking for a mobile robot based on purely geometric planning","authors":"Zhuanzhuan Ma , Li Chen , Tian Liang , Jinguo Liu","doi":"10.1016/j.robot.2024.104828","DOIUrl":"10.1016/j.robot.2024.104828","url":null,"abstract":"<div><div>A purely geometric planning method for a mobile robot in unknown environments is proposed to ensure collision avoidance with obstacles within the safety time interval while moving toward the goal. The robot initially detects a point cloud of obstacles using a 2D LiDAR. Euclidean clustering is employed to classify the point cloud into distinct point classes. Each point class is then identified as a directed closed-loop rectangle representing the obstacle. A relative orientation <em>k</em>d-tree is designed to store the vertices of the obstacles and determine which obstacles should be considered in the obstacle avoidance algorithm. A velocity divider is introduced to obtain a linear convex area of possible obstacle avoidance velocities. Linear planning is then used to calculate the optimal obstacle avoidance velocity for control. A virtual reference point method is proposed to address the problem of an unreachable goal in a singular configuration. Experimental results show that the directed closed-loop rectangle and relative orientation <em>k</em>d-tree facilitate rapid updates of required obstacle points with low-cost sensor equipment. A deterministic path for a given scenario is demonstrated, confirming the reliability of the geometric planning method for the obstacle avoidance velocity region and the optimal obstacle avoidance velocity. The proposed algorithm is further validated in scenarios with multiple obstacles and dynamic environments involving moving obstacles.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"183 ","pages":"Article 104828"},"PeriodicalIF":4.3,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-08DOI: 10.1016/j.robot.2024.104818
Xiaolei Ren , Hui Liu , Yechen Qin , Lijin Han , Shida Nie , Jingshuo Xie
The trend of intelligent vehicles is currently expanding, and a new class of unmanned intelligent vehicles known as wheel-legged vehicles (WLVs) is emerging. WLVs excel in transportation on unstructured terrain by offering a unique combination of the efficiency of wheels on flat ground and the versatility of legs to tackle obstacles. To enhance the locomotion performance of WLVs on unstructured terrains, this paper presents a novel framework for improving their locomotion through nonlinear programming-based (NLP) trajectory optimization and stability control. The framework optimizes the vehicle’s body and wheel positioning while incorporating terrain information and employs a linear rigid body dynamic model for efficient motion planning. The stability control framework combines feedforward control using ground reaction forces with feedback control through joint PD control and utilizes model predictive control (MPC) to adjust the wheel slip ratio to prevent slip on steep slopes. Experimental validation on the real vehicle with torque-controlled wheels demonstrated the capability of driving over a 1 m height with a 30°slope at an average speed of 0.7 m/s and a maximum speed of 1.03 m/s. Our approach also enables the WLV to overcome obstacles, such as inclines, while dynamically negotiating these challenging terrains.
{"title":"Trajectory optimization and stability control for a novel unmanned intelligent wheel-legged vehicles on unstructured terrains","authors":"Xiaolei Ren , Hui Liu , Yechen Qin , Lijin Han , Shida Nie , Jingshuo Xie","doi":"10.1016/j.robot.2024.104818","DOIUrl":"10.1016/j.robot.2024.104818","url":null,"abstract":"<div><div>The trend of intelligent vehicles is currently expanding, and a new class of unmanned intelligent vehicles known as wheel-legged vehicles (WLVs) is emerging. WLVs excel in transportation on unstructured terrain by offering a unique combination of the efficiency of wheels on flat ground and the versatility of legs to tackle obstacles. To enhance the locomotion performance of WLVs on unstructured terrains, this paper presents a novel framework for improving their locomotion through nonlinear programming-based (NLP) trajectory optimization and stability control. The framework optimizes the vehicle’s body and wheel positioning while incorporating terrain information and employs a linear rigid body dynamic model for efficient motion planning. The stability control framework combines feedforward control using ground reaction forces with feedback control through joint PD control and utilizes model predictive control (MPC) to adjust the wheel slip ratio to prevent slip on steep slopes. Experimental validation on the real vehicle with torque-controlled wheels demonstrated the capability of driving over a 1 m height with a 30°slope at an average speed of 0.7 m/s and a maximum speed of 1.03 m/s. Our approach also enables the WLV to overcome obstacles, such as inclines, while dynamically negotiating these challenging terrains.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"182 ","pages":"Article 104818"},"PeriodicalIF":4.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-02DOI: 10.1016/j.robot.2024.104819
Xueyi Li , Daiyou Li , Peng Yuan , Yining Xie , Zhiliang Wang , Zhijie Xie , Xiangwei Kong , Fulei Chu
Bearings and gears are critical components in modern industry, and cross-domain diagnosis of these elements is of great significance. However, in practical applications, challenges such as insufficient training data and variability between equipment arise. To address this issue, this study proposes an innovative neural network structure, ConvNeXt, and a Multi-Scale Dilated Attention (MSDA) mechanism to improve the accuracy problem caused by inadequate feature extraction. ConvNeXt improves upon traditional convolutional neural networks by introducing a multi-scale attention mechanism to enhance the model's performance and expressiveness. Through parallel multi-channel convolution operations, ConvNeXt can capture dependencies between different channels and reduce the number of parameters. Meanwhile, the MSDA mechanism allows signals to interact and exchange information at different scales, effectively extracting complex features in one-dimensional signals. Experimental results demonstrate a significant performance improvement in one-dimensional signal processing using ConvNeXt and MSDA, better capturing relationships between global and local features in one-dimensional signals and enhancing model accuracy. The joint application of ConvNeXt and MSDA brings new solutions to one-dimensional signal processing, offering potential opportunities for effective monitoring of critical components in rotating machinery. Experimental results show that this method achieves high diagnostic accuracy in various transfer tasks, with an average accuracy of 94.28%, providing reliable support for bearing fault diagnosis.
{"title":"Fusion innovation: Multi-scale dilated collaborative model of ConvNeXt and MSDA for fault diagnosis","authors":"Xueyi Li , Daiyou Li , Peng Yuan , Yining Xie , Zhiliang Wang , Zhijie Xie , Xiangwei Kong , Fulei Chu","doi":"10.1016/j.robot.2024.104819","DOIUrl":"10.1016/j.robot.2024.104819","url":null,"abstract":"<div><div>Bearings and gears are critical components in modern industry, and cross-domain diagnosis of these elements is of great significance. However, in practical applications, challenges such as insufficient training data and variability between equipment arise. To address this issue, this study proposes an innovative neural network structure, ConvNeXt, and a Multi-Scale Dilated Attention (MSDA) mechanism to improve the accuracy problem caused by inadequate feature extraction. ConvNeXt improves upon traditional convolutional neural networks by introducing a multi-scale attention mechanism to enhance the model's performance and expressiveness. Through parallel multi-channel convolution operations, ConvNeXt can capture dependencies between different channels and reduce the number of parameters. Meanwhile, the MSDA mechanism allows signals to interact and exchange information at different scales, effectively extracting complex features in one-dimensional signals. Experimental results demonstrate a significant performance improvement in one-dimensional signal processing using ConvNeXt and MSDA, better capturing relationships between global and local features in one-dimensional signals and enhancing model accuracy. The joint application of ConvNeXt and MSDA brings new solutions to one-dimensional signal processing, offering potential opportunities for effective monitoring of critical components in rotating machinery. Experimental results show that this method achieves high diagnostic accuracy in various transfer tasks, with an average accuracy of 94.28%, providing reliable support for bearing fault diagnosis.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"182 ","pages":"Article 104819"},"PeriodicalIF":4.3,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-02DOI: 10.1016/j.robot.2024.104823
Daniel Gnad , Hubert Gattringer , Andreas Müller , Wolfgang Höbarth , Roland Riepl , Lukas Meßner
Model-based control schemes, forward dynamics simulations, constraint force computation and time-optimal motion planning have one major thing in common, they all depend on the dynamics parameters of the system. Physical consistency of the dynamics parameters ensures a positive definite mass matrix and correct constraint forces. The most common inverse dynamics identification method – the base-parameters – lack physical consistency. This paper proposes an identification method to identify physically consistent dynamics parameters for Delta-like robots while further showing the effects of friction in passive joints. A tailored model to compute the crucial constraint forces appearing in the mechanism based on the identified dynamics parameters is derived. This model is used to additionally consider constraint forces besides actuation torques for time-optimal motion planning of a typical pick and place task. This is done without any prior CAD data of the robot from the manufacturer.
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