Results 11 to 20 of about 738 (165)

Robot obstacle avoidance optimization by A* and DWA fusion algorithm. [PDF]

open access: yesPLoS One
The current robot path planning methods only use global or local methods, which is difficult to meet the real-time and integrity requirements, and can not avoid dynamic obstacles. Based on this, this study will use the improved A-star global planning algorithm to design a hybrid robot obstacle avoidance path planning algorithm that integrates sliding ...
Li P, Hao L, Zhao Y, Lu J.
europepmc   +5 more sources

An Enhanced A*-DWA Fusion Algorithm for Robot Navigation in Complex Environments. [PDF]

open access: yesBiomimetics (Basel)
To tackle the navigation challenge in dynamic and complex environments, this study designs a fusion planning framework that synergistically integrates enhanced A* algorithm with improved DWA, inspired by the biological dual-layer navigation mechanism of global path planning and local real-time obstacle avoidance.
Bao H   +5 more
europepmc   +3 more sources

A hybrid RRT-DWA path planning framework for UAVs in dynamic environments [PDF]

open access: yesScientific Reports
To address the limitations of single-path planning algorithms in dynamic and complex environments, this paper proposes a hybrid planning framework that integrates global and local planning using a combination of Rapidly-exploring Random Tree (RRT) and ...
Qiang Han   +5 more
doaj   +2 more sources

A Path Planning Method Based on Improved A* and Fuzzy Control DWA of Underground Mine Vehicles

open access: yesApplied Sciences
In order to solve the problem of low safety and efficiency of underground mine vehicles, a path planning method for underground mine vehicles based on an improved A star (A*) and fuzzy control Dynamic Window Approach (DWA) is proposed.
Chuanwei Zhang   +3 more
doaj   +3 more sources

Port environmental path planning based on key obstacles [PDF]

open access: yesScientific Reports
This paper proposes an improved hybrid algorithm for automated guided vehicles (AGVs) in port environments based on the concept of key obstacles for the JPS and DWA algorithms.
Guoliang Yang, Wenkai Xiong
doaj   +2 more sources

Path Planning of Deep-Sea Landing Vehicle Based on the Safety Energy-Dynamic Window Approach Algorithm

open access: yesJournal of Marine Science and Engineering, 2023
To ensure the safety and energy efficiency of autonomous sampling operations for a deep-sea landing vehicle (DSLV), the Safety Energy-Dynamic Window Approach (SE-DWA) algorithm was proposed.
Zuodong Pan   +4 more
doaj   +1 more source

Path Planning of Robot Combing Safety A* Algorithm and Dynamic Window Approach [PDF]

open access: yesJisuanji gongcheng, 2022
The A* algorithm relies on heuristic information to guide the search direction and is widely used for path planning of mobile robots.However, the search path of this algorithm has redundant nodes that are similar to obstacles, which prevent the algorithm
ZHAN Jingwu, HUANG Yiqing
doaj   +1 more source

Multi-UAV Cooperative Obstacle Avoidance of 3D Vector Field Histogram Plus and Dynamic Window Approach

open access: yesDrones, 2023
In this paper, we propose a fusion algorithm that integrates the 3D vector field histogram plus (VFH+) algorithm and the improved dynamic window approach (DWA) algorithm.
Xinhua Wang   +3 more
doaj   +1 more source

Electric Logistics Vehicle Path Planning Based on the Fusion of the Improved A-Star Algorithm and Dynamic Window Approach

open access: yesWorld Electric Vehicle Journal, 2023
The study of path-planning algorithms is crucial for an electric logistics vehicle to reach its target point quickly and safely. In light of this, this work suggests a novel path-planning technique based on the improved A-star (A*) fusion dynamic window ...
Mengxue Yu   +3 more
doaj   +1 more source

Robot Path Planning Research Incorporating Improved A* Algorithm and DWA Algorithm

open access: yesInformation Technology and Control, 2023
For the traditional A* algorithm has problems such as long paths, large number of nodes, and the demand for dynamic obstacle cannot be avoided in complex environment. A mobile robot dynamic path avoidance method will be improved to improve the A * algorithm and improve DWA algorithm Two map environments are used for simulation verification.
Shiya Qu   +5 more
openaire   +1 more source

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