Pub Date : 2023-10-01DOI: 10.1007/s10846-023-01972-6
Qingjun Yang, Congfei Li, Rui Zhu, Yulong Li, Dianxin Wang, Xuan Wang
{"title":"Push Recovery Control Based on Model Predictive Control of Hydraulic Quadruped Robots","authors":"Qingjun Yang, Congfei Li, Rui Zhu, Yulong Li, Dianxin Wang, Xuan Wang","doi":"10.1007/s10846-023-01972-6","DOIUrl":"https://doi.org/10.1007/s10846-023-01972-6","url":null,"abstract":"","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"45 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":"135763026","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/s10846-023-01937-9
Zifei Jiang, Mohamed Al Lawati, Alan Lynch
{"title":"Quasi-Static State Feedback Output Tracking for a Slung Load System with Rotor Drag Compensation: PX4-SITL Validation","authors":"Zifei Jiang, Mohamed Al Lawati, Alan Lynch","doi":"10.1007/s10846-023-01937-9","DOIUrl":"https://doi.org/10.1007/s10846-023-01937-9","url":null,"abstract":"","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"121 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":"135810085","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/s10846-023-01973-5
Tuğba Zeybek, Ufuk Sakarya
Human-machine interaction (HMI) has been an important research area in many scientific fields for many years with the development of sensor technologies. With the general use of unmanned aerial vehicles (UAVs) in recent years, the gesture recognition concept for HMI has become a considerable study in UAVs. They can be used in different domains and for different purposes. The main motivation for this paper is to create as simple a human-machine interface design for UAVs as possible. The vector-based features can be arranged in low memory size and the low-complexity decision process on them can be aimed. The gesture recognition problem for HMI in UAVs can be modeled as a pattern recognition problem in a multi-sensor system with vectorial data from various types of sensors. The speed of the action and the magnitude of the action can be different even within the same class of gesture action. In other words, user-independent gesture action recognition is difficult due to large intra-class differences in gesture action patterns. This paper introduces the wavelet-based vectorial feature extraction and the discriminant function-based decision in the supervised-based reduced vectorial dimension. According to experimental studies, the promising method is put forward for gesture recognition in the control of UAVs.
{"title":"Wavelet-Based Gesture Recognition Method for Human-Machine Interaction in Aviation","authors":"Tuğba Zeybek, Ufuk Sakarya","doi":"10.1007/s10846-023-01973-5","DOIUrl":"https://doi.org/10.1007/s10846-023-01973-5","url":null,"abstract":"Human-machine interaction (HMI) has been an important research area in many scientific fields for many years with the development of sensor technologies. With the general use of unmanned aerial vehicles (UAVs) in recent years, the gesture recognition concept for HMI has become a considerable study in UAVs. They can be used in different domains and for different purposes. The main motivation for this paper is to create as simple a human-machine interface design for UAVs as possible. The vector-based features can be arranged in low memory size and the low-complexity decision process on them can be aimed. The gesture recognition problem for HMI in UAVs can be modeled as a pattern recognition problem in a multi-sensor system with vectorial data from various types of sensors. The speed of the action and the magnitude of the action can be different even within the same class of gesture action. In other words, user-independent gesture action recognition is difficult due to large intra-class differences in gesture action patterns. This paper introduces the wavelet-based vectorial feature extraction and the discriminant function-based decision in the supervised-based reduced vectorial dimension. According to experimental studies, the promising method is put forward for gesture recognition in the control of UAVs.","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"124 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":"134935914","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}
Abstract Mobile robots are desired with resilience to safely interact with prior-unknown environments and finally accomplish given tasks. This paper utilizes instantaneous local sensory data to stimulate the safe feedback motion planning (SFMP) strategy with adaptability to diverse prior-unknown environments without building a global map. This is achieved by the numerical optimization with the constraints, referred to as instantaneous local control barrier functions (IL-CBFs) and goal-driven control Lyapunov functions (GD-CLFs), learned from perceptional signals. In particular, the IL-CBFs reflecting potential collisions and GD-CLFs encoding incrementally discovered subgoals are first online learned from local perceptual data. Then, the learned IL-CBFs are united with GD-CLFs in the context of quadratic programming (QP) to generate the safe feedback motion planning strategy. Rather importantly, an optimization over the admissible control space of IL-CBFs is conducted to enhance the solution feasibility of QP. The SFMP strategy is developed with theoretically guaranteed collision avoidance and convergence to destinations. Numerical simulations are conducted to reveal the effectiveness of the proposed SFMP strategy that drives mobile robots to safely reach the destination incrementally in diverse prior-unknown environments.
{"title":"Safe Feedback Motion Planning in Unknown Environments: An Instantaneous Local Control Barrier Function Approach","authors":"Cong Li, Zengjie Zhang, Nesrin Ahmed, Qingchen Liu, Fangzhou Liu, Martin Buss","doi":"10.1007/s10846-023-01962-8","DOIUrl":"https://doi.org/10.1007/s10846-023-01962-8","url":null,"abstract":"Abstract Mobile robots are desired with resilience to safely interact with prior-unknown environments and finally accomplish given tasks. This paper utilizes instantaneous local sensory data to stimulate the safe feedback motion planning (SFMP) strategy with adaptability to diverse prior-unknown environments without building a global map. This is achieved by the numerical optimization with the constraints, referred to as instantaneous local control barrier functions (IL-CBFs) and goal-driven control Lyapunov functions (GD-CLFs), learned from perceptional signals. In particular, the IL-CBFs reflecting potential collisions and GD-CLFs encoding incrementally discovered subgoals are first online learned from local perceptual data. Then, the learned IL-CBFs are united with GD-CLFs in the context of quadratic programming (QP) to generate the safe feedback motion planning strategy. Rather importantly, an optimization over the admissible control space of IL-CBFs is conducted to enhance the solution feasibility of QP. The SFMP strategy is developed with theoretically guaranteed collision avoidance and convergence to destinations. Numerical simulations are conducted to reveal the effectiveness of the proposed SFMP strategy that drives mobile robots to safely reach the destination incrementally in diverse prior-unknown environments.","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"109 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":"135762713","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}
{"title":"Hierarchical Goal-Guided Learning for the Evasive Maneuver of Fixed-Wing UAVs based on Deep Reinforcement Learning","authors":"Yinlong Yuan, Jian Yang, Zhu Liang Yu, Yun Cheng, Pengpeng Jiao, Liang Hua","doi":"10.1007/s10846-023-01953-9","DOIUrl":"https://doi.org/10.1007/s10846-023-01953-9","url":null,"abstract":"","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"64 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":"135850253","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/s10846-023-01930-2
Ignacio de Loyola Páez-Ubieta, Julio Castaño-Amorós, Santiago T. Puente, Pablo Gil
Abstract The accumulation of litter is increasing in many places and is consequently becoming a problem that must be dealt with. In this paper, we present a manipulator robotic system to collect litter in outdoor environments. This system has three functionalities. Firstly, it uses colour images to detect and recognise litter comprising different materials. Secondly, depth data are combined with pixels of waste objects to compute a 3D location and segment three-dimensional point clouds of the litter items in the scene. The grasp in 3 Degrees of Freedom (DoFs) is then estimated for a robot arm with a gripper for the segmented cloud of each instance of waste. Finally, two tactile-based algorithms are implemented and then employed in order to provide the gripper with a sense of touch. This work uses two low-cost visual-based tactile sensors at the fingertips. One of them addresses the detection of contact (which is obtained from tactile images) between the gripper and solid waste, while another has been designed to detect slippage in order to prevent the objects grasped from falling. Our proposal was successfully tested by carrying out extensive experimentation with different objects varying in size, texture, geometry and materials in different outdoor environments (a tiled pavement, a surface of stone/soil, and grass). Our system achieved an average score of 94% for the detection and Collection Success Rate (CSR) as regards its overall performance, and of 80% for the collection of items of litter at the first attempt.
{"title":"Vision and Tactile Robotic System to Grasp Litter in Outdoor Environments","authors":"Ignacio de Loyola Páez-Ubieta, Julio Castaño-Amorós, Santiago T. Puente, Pablo Gil","doi":"10.1007/s10846-023-01930-2","DOIUrl":"https://doi.org/10.1007/s10846-023-01930-2","url":null,"abstract":"Abstract The accumulation of litter is increasing in many places and is consequently becoming a problem that must be dealt with. In this paper, we present a manipulator robotic system to collect litter in outdoor environments. This system has three functionalities. Firstly, it uses colour images to detect and recognise litter comprising different materials. Secondly, depth data are combined with pixels of waste objects to compute a 3D location and segment three-dimensional point clouds of the litter items in the scene. The grasp in 3 Degrees of Freedom (DoFs) is then estimated for a robot arm with a gripper for the segmented cloud of each instance of waste. Finally, two tactile-based algorithms are implemented and then employed in order to provide the gripper with a sense of touch. This work uses two low-cost visual-based tactile sensors at the fingertips. One of them addresses the detection of contact (which is obtained from tactile images) between the gripper and solid waste, while another has been designed to detect slippage in order to prevent the objects grasped from falling. Our proposal was successfully tested by carrying out extensive experimentation with different objects varying in size, texture, geometry and materials in different outdoor environments (a tiled pavement, a surface of stone/soil, and grass). Our system achieved an average score of 94% for the detection and Collection Success Rate (CSR) as regards its overall performance, and of 80% for the collection of items of litter at the first attempt.","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"24 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":"135761210","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/s10846-023-01966-4
Kleio Baxevani, Herbert G. Tanner
{"title":"Multi-modal Swarm Coordination via Hopf Bifurcations","authors":"Kleio Baxevani, Herbert G. Tanner","doi":"10.1007/s10846-023-01966-4","DOIUrl":"https://doi.org/10.1007/s10846-023-01966-4","url":null,"abstract":"","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"64 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":"134934720","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/s10846-023-01993-1
Kimon P. Valavanis
{"title":"JIRS Editorial, October 2023","authors":"Kimon P. Valavanis","doi":"10.1007/s10846-023-01993-1","DOIUrl":"https://doi.org/10.1007/s10846-023-01993-1","url":null,"abstract":"","PeriodicalId":404612,"journal":{"name":"Journal of Intelligent and Robotic Systems","volume":"66 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":"135963359","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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