A comprehensive review of path planning for agricultural ground robots

S Chakraborty, D Elangovan, PL Govindarajan… - Sustainability, 2022 - mdpi.com
The population of the world is predicted to reach nine billion by 2050, implying that
agricultural output must continue to rise. To deal with population expansion, agricultural …

Energy efficient local path planning algorithm based on predictive artificial potential field

R Szczepanski, T Tarczewski, K Erwinski - IEEE Access, 2022 - ieeexplore.ieee.org
Energy efficiency is one of the most important parameters in transportation electrification. It
allows to improve the production rate due to longer operation without charging or decrease …

Route planning for an autonomous robotic vehicle employing a weight-controlled particle swarm-optimized Dijkstra algorithm

S Sundarraj, RVK Reddy, MB Basam, GH Lokesh… - IEEE …, 2023 - ieeexplore.ieee.org
An autonomous robotic vehicle (ARVs) is a self-driving vehicle that uses advanced
technologies to navigate through the environment without human intervention. These …

A multiagent deep reinforcement learning approach for path planning in autonomous surface vehicles: The Ypacaraí lake patrolling case

SY Luis, DG Reina, SLT Marín - IEEE Access, 2021 - ieeexplore.ieee.org
Autonomous surfaces vehicles (ASVs) excel at monitoring and measuring aquatic nutrients
due to their autonomy, mobility, and relatively low cost. When planning paths for such …

A Review of Path Planning Methods for Marine Autonomous Surface Vehicles

Y Wu, T Wang, S Liu - Journal of Marine Science and Engineering, 2024 - mdpi.com
A marine autonomous surface vehicle (ASV) is a kind of autonomous marine robot with
intelligent and flexible use advantages. They are mainly divided into two categories …

A deep reinforcement learning approach for the patrolling problem of water resources through autonomous surface vehicles: The ypacarai lake case

SY Luis, DG Reina, SLT Marín - IEEE Access, 2020 - ieeexplore.ieee.org
Autonomous Surfaces Vehicles (ASV) are incredibly useful for the continuous monitoring
and exploring task of water resources due to their autonomy, mobility, and relative low cost …

Reinforcement learning of optimal active particle navigation

M Nasiri, B Liebchen - New Journal of Physics, 2022 - iopscience.iop.org
The development of self-propelled particles at the micro-and the nanoscale has sparked a
huge potential for future applications in active matter physics, microsurgery, and targeted …

A bayesian optimization approach for water resources monitoring through an autonomous surface vehicle: The ypacarai lake case study

FP Samaniego, DG Reina, SLT Marín… - IEEE …, 2021 - ieeexplore.ieee.org
Bayesian Optimization is a sequential method for obtaining the maximum of an unknown
function that has gained much popularity in recent years. Bayesian Optimization is …

Two-level vehicle path planning model for multi-warehouse robots with conflict solution strategies and improved ACO

P Wu, L Zhong, J Xiong, Y Zeng… - Journal of Intelligent and …, 2023 - ieeexplore.ieee.org
With the rapid development of warehouse robots in logistics and other industries, research
on their path planning has become increasingly important. Based on the analysis of various …

[HTML][HTML] A coverage path planning approach for environmental monitoring using an unmanned surface vehicle

SKR Sudha, D Mishra, IA Hameed - Ocean Engineering, 2024 - Elsevier
Monitoring and surveillance using autonomous vehicles offer a low-cost and efficient
solution compared to conventional methods that require manual surveys. Monitoring water …