The path planning algorithm plays a pivotal role in the field of intelligent robotics. However, in certain scenarios, the A-star algorithm exhibits drawbacks such as excessive redundant nodes and prolonged path length...
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The path planning algorithm plays a pivotal role in the field of intelligent robotics. However, in certain scenarios, the A-star algorithm exhibits drawbacks such as excessive redundant nodes and prolonged path lengths. Consequently, this paper introduces a path planning algorithm employing a heuristic approach, which will be briefly elucidated in the subsequent sections. If the straight-line path from the starting point to the destination is unobstructed, iterative calculations for pathplanning are unnecessary. Should the straight-line path intersect obstacles, the proposed heuristic algorithm is employed for local pathplanning to circumvent obstacles, and the obtained path is subsequently integrated with the overall trajectory. In the same context, we compare this algorithm with other path planning algorithms, revealing that the enhanced algorithm presented in this paper achieves a reduction in path length this study.
It is particularly important to develop efficient air-rail intermodal pathplanning methods for making full use of the advantages of air-rail intermodal networks and providing passengers with richer and more reasonabl...
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It is particularly important to develop efficient air-rail intermodal pathplanning methods for making full use of the advantages of air-rail intermodal networks and providing passengers with richer and more reasonable travel options. A Time-Expanded Graph (TEG) is used to model the timetable information of public transportation providing a theoretical basis for public transportation pathplanning. However, if the TEG includes a large amount of data such as train stations, airports, train and air schedules, the network scale will become very large, making pathplanning extremely time-consuming. This study proposes an XGBoost-based heuristic path planning algorithm (XGB-HPPA) for large scale air-rail intermodal networks, which use the XGBoost model to predict transfer stations before pathplanning, and quickly eliminate unreasonable transfer edges by adding a heuristic factor, reducing the network scale, thus accelerating the computation speed. Comparative results indicate that XGB-HPPA can markedly enhance computational speed within large-scale networks, while obtaining as many valid solutions as possible and approximating the optimal solution.
In the operation of a broad range of industrial processes, the uses of robots whose trajectories are constrained by the velocity of the parts actuated (tools, end effectors, joints and the like) more often than not pl...
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In the operation of a broad range of industrial processes, the uses of robots whose trajectories are constrained by the velocity of the parts actuated (tools, end effectors, joints and the like) more often than not play a significant role. Keeping our focus on systems for material deposition such as painting, glueing, aerosol spraying but nowadays also additive manufacturing techniques like FDM processes, it is noticeable that a key parameter is the control of the flow of material in accordance with the trajectory velocity of the parts being actuated. According to the specific requirements and goals of different technology, it is possible to generate different trajectories. In this paper, we propose an original path planning algorithm based on the use of Bezier curves aimed at assuring regulation of the velocity and a uniform distribution of the extruded material referring to an innovative additive manufacturing technology. In particular, the paper presents a pathplanning technology developed for an application where it is necessary to maintain a constant velocity along the length of the trajectory aimed at improving the technological processes on the basis of an innovative additive technology. The paper further presents a working application with a machine prototype so as to demonstrate the viability and performance of the work under consideration. (C) 2017 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
Energy management is a fundamental task and challenge of plug-in split hybrid electric vehicle (PSHEV) research field because of the complicated powertrain and variable driving conditions. Motivated by the foresight o...
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Energy management is a fundamental task and challenge of plug-in split hybrid electric vehicle (PSHEV) research field because of the complicated powertrain and variable driving conditions. Motivated by the foresight of intelligent vehicle and the breakthroughs of deep reinforcement learning framework, an energy management strategy of intelligent plug-in split hybrid electric vehicle (IPSHEV) based on optimized Dijkstra's path planning algorithm (ODA) and reinforcement learning Deep-Q-Network (DQN) is proposed to cope with the challenge. Firstly, a gray model is used to predict the traffic congestion of each road and the length of each road calculated in the traditional Dijkstra's algorithm (DA) is modified for pathplanning. Secondly, on the basis of the predicted velocity of each road, the planned velocity is constrained by the vehicle dynamics to ensure the driving security. Finally, the planning information is inputted to DQN to control the working mode of IPSHEV, so as to achieve energy saving of the vehicle. The simulation results show the optimized path planning algorithm and proposed energy management strategy is feasible and effective.
The purpose is to study the role and influence of football robots on the actual football training in the current popularity of football robot competition. The theoretical basis and key technologies of the football rob...
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The purpose is to study the role and influence of football robots on the actual football training in the current popularity of football robot competition. The theoretical basis and key technologies of the football robot system are deeply studied. The design of the wireless communication subsystem, vision subsystem, decision subsystem and fuzzy PID (port ID) control system of the football robot is completed. The application of edge computing in wireless communication subsystem is discussed. The Immune algorithm (IA), Particle Swarm Optimisation (PSO) algorithm and Immune PSO (IPSO) algorithm are compared and analysed. IPSO algorithm is used for pathplanning of football robots. In the comparison of the three algorithms, the convergence stability of the IPSO algorithm is significantly higher than that of IA and PSO algorithm. This research can arouse the common concern and thinking of the scientific and technological circles and the traditional football circles. It is a new field, and a challenge to traditional football. It plays an important role in the research and development of intelligent robot technology and traditional football training, especially the college football team.
UGV has widely used in the battlefield, thus UGV's survivability technique has become one of the main issue on the path planning algorithm. In this study, 3D survivability map is suggested for UGV survivability, a...
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ISBN:
(纸本)9781479911974;9781479911950
UGV has widely used in the battlefield, thus UGV's survivability technique has become one of the main issue on the path planning algorithm. In this study, 3D survivability map is suggested for UGV survivability, and the optimal path planning algorithm on this map is also suggested. 3D survivability map is a grid map on which the 3D terrain data is combined with the battle field data, and each grid node on the map has UGV's survival probability value. The suggested path planning algorithm finds the optimal path by comparing the survival probability value of the grid nodes. At last, the simulation program has been developed, and the results are shown to verify the suggested algorithm.
As the population is get increases the lightweight materials based vehicles are also get increases. When the people wants to move from the once place to another place they use the transport. As the number of vehicles ...
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As the population is get increases the lightweight materials based vehicles are also get increases. When the people wants to move from the once place to another place they use the transport. As the number of vehicles increases the accident are happening day to day in different place. So the safety in the road is decreases. This paper proposes the VANET'S method which is the vehicle and hoc routing. This method can sends the information about the traffic congestion, road path etc to the mobile network. By using the routing method the safety is increased. In transmitting the data the traffic may happen in the message passing path. Due to this traffic in the routing system a novel path data planning is implemented. The traffic may affect the QOS (Quality of security). So the message transmission is made within a period of time. And this proposed system the supports security measure over the data path. This system is more helpful to the people and it solves a current problem which is taking place. This system is mainly depends on the social problem. (c) 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the 12th National Conference on Recent Advancements in Biomedical Engineering.
After the development of fusion technology of mechanics, electronics and IT, there are a lot of researches about the autonomous vehicle. For this kind of vehicle to move automatically, it needs the reference input tha...
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ISBN:
(纸本)9783642339257
After the development of fusion technology of mechanics, electronics and IT, there are a lot of researches about the autonomous vehicle. For this kind of vehicle to move automatically, it needs the reference input that the vehicle can follow, and this reference input comes from a path planning algorithm. A* is one of the well-known global path planning algorithm that finds the optimal path on the given map using the heuristic cost function. However, A* algorithm gives the vehicle some reference points on the path not the continuous reference path. And A* may not guarantee the path will not collide the corner of the obstacle. To overcome this problem, in this paper, the hybrid path planning algorithm is suggested using B-spline equation and new heuristic cost function with survival probability. At last, we developed the simulation program and the results are shown.
In this paper, based on the existing path planning algorithms for virtual assembly used in other countries, a path planning algorithm for virtual assembly of power battery packs in new energy automobiles based on engi...
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ISBN:
(纸本)9781509041558
In this paper, based on the existing path planning algorithms for virtual assembly used in other countries, a path planning algorithm for virtual assembly of power battery packs in new energy automobiles based on engineering semantics is put forward in combination with actual characteristics of virtual assembly of power battery packs in new energy automobiles, and such assembly paths for power battery packs can be categorized into linear path, revolving path and mixed path. The path planning algorithm for virtual assembly based on engineering semantic improves planning efficiency for assembly of parts of power battery pack in new energy automobiles.
In this paper, a UAV path planning algorithm based on improved rapidly-exploring random tree(RRT) is proposed to solve the problem of high randomness of sampling points and poor smoothness of planned path in the RRT p...
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