Results 11 to 20 of about 937 (157)

The analysis of pedestrian flow in the smart city by improved DWA with robot assistance [PDF]

open access: yesScientific Reports
With the acceleration of urbanization in China, the urban population continues to grow, leading to frequent occurrences of crowded public spaces, which in turn trigger traffic congestion and even safety accidents.
Yingyue Hu, Huizhen Long, Min Chen
doaj   +5 more sources

ASL-DWA: An Improved A-Star Algorithm for Indoor Cleaning Robots

open access: yesIEEE Access, 2022
The traditional A-star algorithm has many search nodes, and the obtained path has polylines and cannot avoid local unknown obstacles. In response to these problems, this paper proposes a new improved A-star algorithm suitable for indoor cleaning robots ...
Haoxin Liu, Yonghui Zhang
doaj   +2 more sources

Research on multi-UAV autonomous obstacle avoidance algorithm integrating improved dynamic window approach and ORCA [PDF]

open access: yesScientific Reports
To address the issue that traditional UAV obstacle-avoidance algorithms had low efficiency in unknown and complex environments, an improved DWA (Dynamic Window Approach) fusion algorithm was proposed. Regarding the lack of a global perspective in the DWA
Xucheng Chang   +4 more
doaj   +2 more sources

LLM-DWA: a hybrid path planning framework combining large language models with the dynamic window approach [PDF]

open access: yesScientific Reports
This research addresses the local minima problem in the Dynamic Window Approach (DWA) algorithm. The conventional DWA, which does not incorporate prior environmental knowledge, often exhibits degraded goal-reaching performance in complex scenarios, such ...
Jeonghee Seo   +2 more
doaj   +2 more sources

Autonomous Navigation of Robots Based on the Improved Informed-RRT∗ Algorithm and DWA

open access: yesJournal of Robotics, 2022
An improved method is proposed in this investigation to solve the problems of poor path quality and low navigation efficiency of the Informed-RRT∗ algorithm in robot autonomous navigation.
Jun Dai   +3 more
doaj   +3 more sources

A Safe Maritime Path Planning Fusion Algorithm for USVs Based on Reinforcement Learning A* and LSTM-Enhanced DWA [PDF]

open access: yesSensors
In complex maritime environments, the safety of path planning for Unmanned Surface Vehicles (USVs) remains a significant challenge. Existing methods for handling dynamic obstacles often suffer from inadequate predictability and generate non-smooth ...
Zhenxing Zhang   +3 more
doaj   +2 more sources

Research on autonomous navigation of mobile robots based on IA-DWA algorithm [PDF]

open access: yesScientific Reports
To improve the efficiency of mobile robot movement, this paper investigates the fusion of the A* algorithm with the Dynamic Window Approach (DWA) algorithm (IA-DWA) to quickly search for globally optimal collision-free paths and avoid unknown obstacles ...
Quanling He   +4 more
doaj   +2 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 Hybrid Ant Colony Optimization and Dynamic Window Method for Real-Time Navigation of USVs [PDF]

open access: yesSensors
Unmanned surface vehicles (USVs) rely on multi-sensor perception, such as radar, LiDAR, GPS, and vision, to ensure safe and efficient navigation in complex maritime environments.
Yuquan Xue   +7 more
doaj   +2 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

Home - About - Disclaimer - Privacy