Large commercial complex projects have the characteristics of large roof area and high electricity price, and the development of distributed photovoltaic power generation has great potential. In this paper, a feasibil...
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Optical topological insulators, as an emerging type of photonic material, present substantial benefits for optical communication. The advanced pattern recognition capabilities of deep learning have propelled the inver...
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This article studies the time-varying formation (TVF) problem of multiagent systems (MASs) with different time delays. By designing the control protocol, the followers could achieve the desired TVF. Considering differ...
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The actuator, serving as the fundamental power source of a soft robot, functions as its central component. The field of soft robotics has garnered increasing research attention since its inception. Pneumatic crawling ...
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This paper is concerned with the distributed resilient fusion filtering(DRFF)problem for a class of time-varying multi-sensor nonlinear stochastic systems(MNSSs)with random sensor delays(RSDs).The phenomenon of the RS...
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This paper is concerned with the distributed resilient fusion filtering(DRFF)problem for a class of time-varying multi-sensor nonlinear stochastic systems(MNSSs)with random sensor delays(RSDs).The phenomenon of the RSDs is modeled by a set of random variables with certain statistical *** addition,the nonlinear function is handled via Taylor expansion in order to deal with the nonlinear fusion filtering *** aim of the addressed issue is to propose a DRFF scheme for MNSSs such that,for both RSDs and estimator gain perturbations,certain upper bounds of estimation error covariance(EEC)are given and locally minimized at every sample *** the light of the obtained local filters,a new DRFF algorithm is developed via the matrix-weighted fusion ***,a sufficient condition is presented,which can guarantee that the local upper bound of the EEC is ***,a numerical example is provided,which can show the usefulness of the developed DRFF approach.
Path planning is one of the most critical links in mobile robots. Its timeliness, security and accessibility are crucial to the development and wide application of mobile robots. However, in solving the problem of pat...
Path planning is one of the most critical links in mobile robots. Its timeliness, security and accessibility are crucial to the development and wide application of mobile robots. However, in solving the problem of path planning, the most popular A* algorithm has some problems, such as heuristic function cannot be estimated accurately, node redundancy, path is not smooth, and obstacle avoidance cannot be achieved in real time. To solve these problems, A fusion algorithm of improved A* combined with reverse path and dynamic window method(DWA-IMP-A*) was proposed. The algorithm refines the heuristic function by incorporating the reverse path. The node optimization algorithm is used to further reduce the path length. The generated trajectories are smoothed by cubic spline interpolation. At the same time, it is integrated with the improved DWA algorithm to improve the efficiency and safety of robot path planning. The algorithm takes ROS mobile robot as the carrier and is tested under typical road conditions. Compared with A* algorithm, the planning time is reduced by 54.6% and the path length is reduced by 6.37%. Experimental results verify the effectiveness and robustness of the algorithm. The research results have certain reference significance for the path planning of various types of mobile robots and the research of driverless vehicles.
作者:
Zhou, YanXiong, YonghuaSchool of Automation
China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China
The widespread application of unmanned aerial vehicle (UAV) has made the coverage path planning problem for multiple UAV systems a research hotspot. In this paper, we propose a multi-UAV solution to achieve complete c...
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This paper investigates the optimal tracking performance (OTP) of multiple-input multiple-output (MIMO) discrete networked controlsystems (NCSs) under the influence of Denial of Service (DoS) attack, channel noise, a...
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In order to improve the efficiency of tea picking,a scheme combining ant colony algorithm and tea picking technology is proposed to plan the picking *** this scheme,k-means clustering algorithm is used to divide the t...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
In order to improve the efficiency of tea picking,a scheme combining ant colony algorithm and tea picking technology is proposed to plan the picking *** this scheme,k-means clustering algorithm is used to divide the tea picking regions with irregular *** ant colony algorithm is used to carry out path planning for tea in different picking areas,and the best picking effect is selected according to the simulation *** solve the problem of long searching time of ant colony algorithm,the condition of iteration termination is changed to adaptive value,and the optimal route after the last iteration is recorded as the initial value of the next *** simulation results show that the best effect is to divide two picking *** improved ant colony algorithm reduces the operation time and the planned picking path is shorter,which can enhance the real-time tea picking and improve the efficiency of tea picking.
This study delves into the critical role of attitude control in downhole directional drilling tools, focusing on the complex coupling between inclination and azimuth in the motion model, particularly the time-varying ...
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