Ensuring robust tracking of controllers’ movement is critical for human-robot interaction in virtual reality (VR) scenarios. This paper proposes a robust tracking algorithm based on a novel wearable ring-shaped contr...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
Ensuring robust tracking of controllers’ movement is critical for human-robot interaction in virtual reality (VR) scenarios. This paper proposes a robust tracking algorithm based on a novel wearable ring-shaped controller equipped with an inertial measurement unit (IMU) and a light-emitting diode (LED). This novel controller design allows users to free up their hands for more immersive experiences. To track the controller’s motion accurately and robustly, we resort to various forms of visual measurements, including 6 DoF and 5 DoF pose measurements from hand gesture detection, as well as 3 DoF position measurement and 2 DoF image measurement derived from the LED. We theoretically analyze the performances of these observation models and propose an optimal observation model combination scheme. Moreover, the necessity and rationale of online estimating system gravity are illustrated. The effectiveness of our tracking method is validated through extensive experiments.
Spiking neural networks (SNNs) have captured apparent interest over the recent years, stemming from neuroscience and reaching the field of artificial intelligence. However, due to their nature SNNs remain far behind i...
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This paper tackles the challenge of autonomous target search using unmanned aerial vehicles (UAVs) in complex unknown environments. To fill the gap in systematic approaches for this task, we introduce Star-Searcher, a...
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The evaluation of regional geological hazard susceptibility is of great significance to the prevention and control of geological hazard. In this paper, the "4-20" Lushan earthquake disaster area as the resea...
The evaluation of regional geological hazard susceptibility is of great significance to the prevention and control of geological hazard. In this paper, the "4-20" Lushan earthquake disaster area as the research area, combined with GIS and characteristics of the research area, through correlation analysis, selected 9 influencing factors as the evaluation factors. The study was conducted using a weighted information volume-logistic regression model (WI-LR). The results were classified into five sensitivity levels: very low, low, medium, high and very high. The results show that the landslide prone areas in Lushan County are concentrated in the area below the middle of the county seat, mostly near rivers, faults and areas with peak acceleration greater than 0.4. Among them, WI-LR model (AUC=0.918) > deterministic factor model (CF =0.908) > weighted information quantity model (WI) (AUC=0.896) > information quantity model I (AUC=0.853) > information quantity logistic regression model I-LR (AUC=0.799). It indicates that WI-LR model has high evaluation accuracy.
Diffuse horizontal irradiance (DHI) forecasts are critical for adopting solar photovoltaic technology. Yet, they can lack reliability given the limited and uncertain meteorological data available for desert areas. Thi...
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Using artificial intelligence and intelligent pathway planning, drones are revolutionizing healthcare logistics by enabling efficient delivery of critical medical supplies to remote areas. This study presents an AI-dr...
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ISBN:
(数字)9798331524005
ISBN:
(纸本)9798331524012
Using artificial intelligence and intelligent pathway planning, drones are revolutionizing healthcare logistics by enabling efficient delivery of critical medical supplies to remote areas. This study presents an AI-driven optimization model that schedules drone trips, selects charging station locations, avoid obstacles and weather zone and assigns provider to patients' location to minimize delivery time. By employing a hybrid genetic-simulated annealing algorithm, the system ensures timely, efficient medical deliveries. Validated through experiments and a case study in Southwestern suburb of Riyadh, SA, the approach highlights the potential of AI-powered drone delivery systems with the incorporation of recharging platforms to enhance healthcare logistics.
In traditional control methods, Series Elastic Actuator (SEA) joint manipulators are limited by their hardware and can only perform simple tasks with low stiffness. To address this issue, we propose a stiffness adjust...
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ISBN:
(数字)9798350358513
ISBN:
(纸本)9798350358520
In traditional control methods, Series Elastic Actuator (SEA) joint manipulators are limited by their hardware and can only perform simple tasks with low stiffness. To address this issue, we propose a stiffness adjustment control strategy for SEA manipulators based on Dynamic systems (DS) with good generalization performance. By enhancing the generalization capability of DS in complex tasks and combining posture control, the SEA manipulators can autonomously adjust control gains and postures according to task requirements to achieve higher stiffness at the end-effector. Experimental results involving the activation of air switches with different stiffness levels and installation angles have demonstrated the effectiveness of our proposed method. The results indicate that compared to traditional methods of adjusting the control gain and retraining DS for similar tasks, our approach exhibits superior generalization performance while maintaining end-effector stiffness during interactions.
作者:
Zhang, YiXie, YajingWang, LijiaLiwang, MinghuiWang, XianbinXiamen University
Ministry of Education of China Department of Information and Communication Engineering Key Laboratory of Multimedia Trusted Perception and Efficient Computing Xiamen China Tongji University
Shanghai Research Institute for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai China Western University
Department of Electrical and Computer Engineering ON Canada
Recently, unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) have merged as important enabling technologies for localization coverage extension and localization accuracy improvement under s...
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Optimal control of constrained unmanned aerial vehicle (UAV) trajectory optimization problem is one of the frontiers and hotspots of UAV research. The various constraints generated by physical limitations and obstacle...
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ISBN:
(数字)9798350368604
ISBN:
(纸本)9798350368611
Optimal control of constrained unmanned aerial vehicle (UAV) trajectory optimization problem is one of the frontiers and hotspots of UAV research. The various constraints generated by physical limitations and obstacles in the environment increase the difficulties of solving the trajectory optimization problem, especially when the limited sensing ability is taken into consideration. This paper presents the receding horizon optimization method to obtain optimal control for the UAV with limited sensing range in a complex environment with obstacles. To improve efficiency, a path constraint processing method is proposed to reduce the number of constraints in the nonlinear programming problem (NLP). The proposed main structure and detailed algorithm are also given. The numerical results demonstrate the effectiveness of the proposed method compared with the classical Gauss pseudospectral method.
With the rise of Embodied Foundation Models (EFMs), most notably Small Language Models (SLMs), adapting Transformers for edge applications has become a very active field of research. However, achieving end-to-end depl...
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