Rapidly-Exploring Adaptive Sampling Tree*: A Sample-Based Path-Planning Algorithm for Unmanned Marine Vehicles Information Gathering in Variable Ocean Environments
This research presents a novel sample-based path planning algorithm for adaptive sampling. The goal is to find a near-optimal path for unmanned marine vehicles (UMVs) that maximizes information gathering over a scientific interest area, while satisfying constraints on collision avoidance and pre-spe...
Main Authors: | Chengke Xiong, Hexiong Zhou, Di Lu, Zheng Zeng, Lian Lian, Caoyang Yu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-04-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/9/2515 |
Similar Items
-
FF-RRT*: a sampling-improved path planning algorithm for mobile robots against concave cavity obstacle
by: Jiping Cong, et al.
Published: (2023-06-01) -
FC-RRT*: An Improved Path Planning Algorithm for UAV in 3D Complex Environment
by: Yicong Guo, et al.
Published: (2022-02-01) -
Exploration–Exploitation Tradeoff in the Adaptive Information Sampling of Unknown Spatial Fields with Mobile Robots
by: Aiman Munir, et al.
Published: (2023-12-01) -
HPO-RRT*: a sampling-based algorithm for UAV real-time path planning in a dynamic environment
by: Yicong Guo, et al.
Published: (2023-06-01) -
Dubins Path-Oriented Rapidly Exploring Random Tree* for Three-Dimensional Path Planning of Unmanned Aerial Vehicles
by: Youyoung Yang, et al.
Published: (2022-07-01)