Fault information of rotating machinery is often drowned in strong noise signals, so it is crucial to accurately identify faults from high-intensity noise signals. In this article, an end-to-end fault diagnosis model ...
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Aiming at the charging and navigation strategy of electric vehicles in the road-electricity coupling scenario,this paper proposes a hybrid planning travel scheme based on the pre-charging and charging warning model ba...
Aiming at the charging and navigation strategy of electric vehicles in the road-electricity coupling scenario,this paper proposes a hybrid planning travel scheme based on the pre-charging and charging warning model based on the road traffic congestion predicted by the big data of the Internet of *** model integrally balances the interests of users and power grid in the coupled road-electric network,and solves the optimal path scheme under different travel scenarios based on collaborative filtering algorithm and user feedback,considering the influence of vehicle departure time and remaining power in short time *** is experimentally demonstrated that the proposed route hybrid recommendation model has better planning effect compared with the single travel model.
In this article, an robust nonlinear observer-based visual servo adaptive control strategy is investigated for a multirotor for stable tracking of targets. This article uses the Newton Euler equation to model the dyna...
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This paper deals with the problem of combining task and motion planning for a manipulator system. We propose a linear temporal logic (LTL) approach which follows the traditional hierarchical planning process, includin...
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ISBN:
(数字)9798350372601
ISBN:
(纸本)9798350372618
This paper deals with the problem of combining task and motion planning for a manipulator system. We propose a linear temporal logic (LTL) approach which follows the traditional hierarchical planning process, including task planning and motion planning. Firstly, the feasible network topology graph is obtained from the high-level task planning module, and the planning algorithm of search is used to obtain the task sequence. Secondly, the coordination module receives the task sequence to extract the manipulator’s action sequence to make planning suggestions. Furthermore, a lower level planning module is used to receive the suggestions and motion planning is performed using sampled planning algorithms to generate and output the motion trajectory. Finally, we verified the feasibility of our method through simulations and physical experiments. Our method has smoother trajectories and is about 10% more efficient than the traditional method of setting way points.
This paper addresses the formation tracking control problem of quadrotor UAV swarms, considering the situation where the linear velocity of quadrotor UAVs cannot be directly measured during actual flight and is suscep...
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ISBN:
(数字)9789887581598
ISBN:
(纸本)9798331540845
This paper addresses the formation tracking control problem of quadrotor UAV swarms, considering the situation where the linear velocity of quadrotor UAVs cannot be directly measured during actual flight and is susceptible to external time-varying disturbances. A distributed robust formation control scheme is developed within a directed graph communication topology to conserve communication resources. In this scheme, controllers based on
$\mathcal{L}_control$
adaptive control strategy and differ-entiator are designed for the position subsystem and attitude subsystem of each quadrotor, enhancing the system's stability, reliability, and safety performance (resistance to matched and unmatched disturbances). Numerical experiments validate the effectiveness and performance of the proposed formation control scheme.
As an crucial component of power line, the timely check for the state of insulator is necessary for the normal running of transmission lines. In view of debasement of insulator segmentation accuracy in current transmi...
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In recent years, researches on Hybrid Terrestrial-Aerial Vehicles (HTAVs) have received a lot of attention. However, most of the existing researches focus on achieving basic motion control in both modes, thus neglecti...
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ISBN:
(数字)9798331518493
ISBN:
(纸本)9798331518509
In recent years, researches on Hybrid Terrestrial-Aerial Vehicles (HTAVs) have received a lot of attention. However, most of the existing researches focus on achieving basic motion control in both modes, thus neglecting the situation of encountering obstacles during motion. To fill this research gap and achieve accurate trajectory tracking with collision avoidance, we proposes the use of Nonlinear Model Predictive control (NMPC). In this paper, we firstly focus on passive-wheeled HTAVs as the target platform. Subsequently, we introduce distance constraint function and dynamics models for both aerial and terrestrial modes, along with three motion constraints specific to the terrestrial mode. Then we designed the NMPC controller base on distance constraint function and the dynamics models for each mode, incorporating the motion constraint in the terrestrial controller to ensure smooth movement on the ground. At the end of this paper, we conduct simulation experiments to evaluate the effectiveness of trajectory tracking. The results of simulations demonstrate that regardless of the mode, the HTAV achieves a relatively high tracking accuracy and avoid collision when following a nonlinear trajectory with fixed initial position and orientation. Additionally, the position error converges rapidly and exhibits minimal fluctuation, highlighting the significant role played by the added constraints in control.
The working state of fasteners is closely related to the safe and stable operation of the power grid. However, the performance of the existing fastener defect detection models is not enough to meet the requirements, b...
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In this paper, we propose a motion planning method for mobile robots in order to satisfy task requirements specified in linear temporal logic (LTL). The proposed method follows the traditional hierarchical planning wo...
In this paper, we propose a motion planning method for mobile robots in order to satisfy task requirements specified in linear temporal logic (LTL). The proposed method follows the traditional hierarchical planning workflow, including path planning and trajectory planning. Firstly, we propose a path planning method based on rapidly exploring random trees (RRT*) and Dubins curve. The tree derived from RRT* is expanded with the help of Buchi automaton converted by an LTL formula. The proposed method can automatically adjust the iterations of sampling according to the scale of Buchi automata. Then, we formulate an optimization problem for the generation of trajectory. We use Bezier curve to express the trajectory and use differential flatness of mobile robots to simplify the optimization problem. Finally, we validate the practicality of our method through simulations and real-world experiments.
To enable robots to use tools, the initial step is teaching robots to employ dexterous gestures for touching specific areas precisely where tasks are performed. Affordance features of objects serve as a bridge in the ...
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To enable robots to use tools, the initial step is teaching robots to employ dexterous gestures for touching specific areas precisely where tasks are performed. Affordance features of objects serve as a bridge in the functional interaction between agents and objects. However, leveraging these affordance cues to help robots achieve functional tool grasping remains unresolved. To address this, we propose a granularity-aware affordance feature extraction method for locating functional affordance areas and predicting dexterous coarse gestures. We study the intrinsic mechanisms of human tool use. On one hand, we use fine-grained affordance features of object-functional finger contact areas to locate functional affordance regions. On the other hand, we use highly activated coarse-grained affordance features in hand-object interaction regions to predict grasp gestures. Additionally, we introduce a model-based post-processing module that includes functional finger coordinate localization, finger-to-end coordinate transformation, and force feedback-based coarse-to-fine grasping. This forms a complete dexterous robotic functional grasping framework GAAF-Dex, which learns Granularity-Aware Affordances from human-object interaction for tool-based Functional grasping in Dexterous robotics. Unlike fully-supervised methods that require extensive data annotation, we employ a weakly supervised approach to extract relevant cues from exocentric (Exo) images of hand-object interactions to supervise feature extraction in egocentric (Ego) images. Correspondingly, we have constructed a small-scale dataset, FAH, which includes near 6K images of functional hand-object interaction Exo images and Ego images of 18 commonly used tools performing 6 tasks. Extensive experiments on the dataset demonstrate that our method outperforms state-of-the-art methods, and real-world localization and grasping experiments validate the practical applicability of our approach. The source code and the establishe
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