Zobrazeno 1 - 10
of 408
pro vyhledávání: '"Local path planning"'
Publikováno v:
Gong-kuang zidonghua, Vol 50, Iss 6, Pp 112-119 (2024)
In order to improve the operational efficiency, search precision, and obstacle avoidance flexibility of the path planning algorithm for coal mine foot robot, a path planning method for coal mine foot robots is proposed, which integrates the improved
Externí odkaz:
https://doaj.org/article/66b77b8173da4b7a918359983130cd28
Publikováno v:
In Engineering Applications of Artificial Intelligence 1 February 2025 141
Publikováno v:
Applied Sciences, Vol 14, Iss 23, p 11195 (2024)
Path planning is a key task in mobile robots, and the application of Deep Q Network (DQN) algorithm for mobile robot path planning has become a hotspot and challenge in current research. In order to solve the obstacle avoidance limitations faced by t
Externí odkaz:
https://doaj.org/article/b041a0ce1cd04a46af521cbd857f958e
Publikováno v:
Gong-kuang zidonghua, Vol 49, Iss 12, Pp 40-46 (2023)
The existing local path planning algorithms only achieve free movement of mobile robots in the scenario. But local path generation does not consider road constraints in the scenario, which is not applicable to some regularized structured roads. The O
Externí odkaz:
https://doaj.org/article/2bdb09d8706d43e8999cd011cb21ff4d
Publikováno v:
Vehicles, Vol 5, Iss 4, Pp 1423-1451 (2023)
Path planning is the most fundamental necessity for autonomous mobile robots. Traditionally, the path planning problem was solved using analytical methods, but these methods need perfect localization in the environment, a fully developed map to plan
Externí odkaz:
https://doaj.org/article/2773335a5438497c8c0a94682033a954
Publikováno v:
Engineering Computations, 2023, Vol. 40, Issue 5, pp. 1266-1286.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/EC-11-2022-0672
Publikováno v:
Sensors, Vol 24, Iss 11, p 3573 (2024)
Path planning creates the shortest path from the source to the destination based on sensory information obtained from the environment. Within path planning, obstacle avoidance is a crucial task in robotics, as the autonomous operation of robots needs
Externí odkaz:
https://doaj.org/article/fb78b150c7e54b1793f8a132d3d2cc86
Publikováno v:
Sensors, Vol 24, Iss 11, p 3604 (2024)
The artificial potential field method has efficient obstacle avoidance ability, but this traditional method suffers from local minima, unreasonable paths, and sudden changes in heading angles during obstacle avoidance, leading to rough paths and incr
Externí odkaz:
https://doaj.org/article/38578b8d320b4e89aec71f7c7299d87e
An Overview of Machine Learning Techniques in Local Path Planning for Autonomous Underwater Vehicles
Autor:
Chinonso E. Okereke, Mohd Murtadha Mohamad, Nur Haliza Abdul Wahab, Olakunle Elijah, Abdulaziz Al-Nahari, S. Zaleha.H
Publikováno v:
IEEE Access, Vol 11, Pp 24894-24907 (2023)
Autonomous underwater vehicles (AUVs) have become attractive and essential for underwater search and exploration because of the advantages they offer over manned underwater vehicles. Hence the need to improve AUV technologies. One crucial area of AUV
Externí odkaz:
https://doaj.org/article/9235dc9fb5104e1a8ef6a3d65ce7c132
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