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Autonomous ground vehicle systems have found extensive potential and practical applications in the modern world. The development of an autonomous ground vehicle poses a significant challenge, particularly in identifying the best path plan,…

机器人学 · 计算机科学 2023-10-24 Aziz ur Rehman , Ahsan Tanveer , M. Touseef Ashraf , Umer Khan

In this paper we address the problem of path planning in an unknown environment with an aerial robot. The main goal is to safely follow the planned trajectory by avoiding obstacles. The proposed approach is suitable for aerial vehicles…

机器人学 · 计算机科学 2023-06-29 Ana Batinovic , Jurica Goricanec , Lovro Markovic , Stjepan Bogdan

Motion planning in an autonomous agent is responsible for providing smooth, safe and efficient navigation. Many solutions for dealing this problem have been offered, one of which is, Artificial Potential Fields (APF). APF is a simple and…

机器人学 · 计算机科学 2020-05-11 Javad Amiryan , Mansour Jamzad

Today, low-altitude fixed-wing Unmanned Aerial Vehicles (UAVs) are largely limited to primitively follow user-defined waypoints. To allow fully-autonomous remote missions in complex environments, real-time environment-aware navigation is…

机器人学 · 计算机科学 2017-12-12 Philipp Oettershagen , Florian Achermann , Benjamin Müller , Daniel Schneider , Roland Siegwart

Path planning is critical for autonomous vehicles (AVs) to determine the optimal route while considering constraints and objectives. The potential field (PF) approach has become prevalent in path planning due to its simple structure and…

机器人学 · 计算机科学 2023-06-13 Pengfei Lin , Ehsan Javanmardi , Jin Nakazato , Manabu Tsukada

Global path planning is the key technology in the design of unmanned surface vehicles. This paper establishes global environment modelling based on electronic charts and hexagonal grids which are proved to be better than square grids in…

机器人学 · 计算机科学 2018-07-24 Yanlong Wang , Xuemin Yu , Xu Liang

The conventional Artificial Potential Field (APF) is fundamentally limited by the local minima issue and its inability to account for the kinematics of moving obstacles. This paper addresses the critical challenge of autonomous collision…

系统与控制 · 电气工程与系统科学 2025-12-10 Nikita Vaibhav Pavle , Shrreya Rajneesh , Rakesh Kumar Sahoo , Manoranjan Sinha

An important capability of autonomous Unmanned Aerial Vehicles (UAVs) is autonomous landing while avoiding collision with obstacles in the process. Such capability requires real-time local trajectory planning. Although trajectory-planning…

机器人学 · 计算机科学 2021-11-19 Yossi Magrisso , Ehud Rivlin , Hector Rotstein

The unmanned aerial vehicles (UAVs) are efficient tools for diverse tasks such as electronic reconnaissance, agricultural operations and disaster relief. In the complex three-dimensional (3D) environments, the path planning with obstacle…

机器人学 · 计算机科学 2025-01-17 Junteng Mao , Ziye Jia , Hanzhi Gu , Chenyu Shi , Haomin Shi , Lijun He , Qihui Wu

In this paper, we study path planning algorithms of resource constrained mobile agents in unknown cluttered environments, which include but are not limited to various terrestrial missions e.g., search and rescue missions by drones in…

系统与控制 · 电气工程与系统科学 2023-08-31 Mosab Diab , Mostafa Mohammadkarimi , Raj Thilak Rajan

Human awareness in robot motion planning is crucial for seamless interaction with humans. Many existing techniques slow down, stop, or change the robot's trajectory locally to avoid collisions with humans. Although using the information on…

机器人学 · 计算机科学 2022-10-24 Marco Faroni , Manuel Beschi , Nicola Pedrocchi

This paper addresses path planning of an unmanned aerial vehicle (UAV) with remote sensing capabilities (or wireless communication capabilities). The goal of the path planning is to find a minimum-flight-time closed tour of the UAV visiting…

机器人学 · 计算机科学 2016-12-20 Dae-Sung Jang , Hyeok-Joo Chae , Han-Lim Choi

Obstacle avoidance and path planning are essential for guiding unmanned ground vehicles (UGVs) through environments that are densely populated with dynamic obstacles. This paper develops a novel approach that combines tangentbased path…

机器人学 · 计算机科学 2025-11-12 Okan Arif Guvenkaya , Selim Ahmet Iz , Mustafa Unel

The problem of mixed static and dynamic obstacle avoidance is essential for path planning in highly dynamic environment. However, the paths formed by grid edges can be longer than the true shortest paths in the terrain since their headings…

人工智能 · 计算机科学 2021-03-01 Junxiao Xue , Xiangyan Kong , Bowei Dong , Mingliang Xu

Increase in the number of space exploration missions has led to the accumulation of space debris, posing risk of collision with the operational satellites. Addressing this challenge is crucial for the sustainability of space operations. To…

系统与控制 · 电气工程与系统科学 2025-10-10 Rakesh Kumar Sahoo , Paridhi Choudhary , Manoranjan Sinha

This paper presents an integrated approach that combines trajectory optimization and Artificial Potential Field (APF) method for real-time optimal Unmanned Aerial Vehicle (UAV) trajectory planning and dynamic collision avoidance. A…

机器人学 · 计算机科学 2023-03-06 D. M. K. K. Venkateswara Rao , Hamed Habibi , Jose Luis Sanchez-Lopez , Holger Voos

For rapid growth in technology and automation, human tasks are being taken over by robots as robots have proven to be better with both speed and precision. One of the major and widespread usages of these robots is in the industrial…

机器人学 · 计算机科学 2020-06-11 Ashutosh Kumar Tiwari , Sandeep Varma Nadimpalli

Unmanned Surface Vehicle (USV) is a new type of intelligent surface craft, and global path planning is the key technology of USV research, which can reflect the intelligent level of USV. In order to solve the problem of global path planning…

机器人学 · 计算机科学 2018-02-12 Yanlong Wang , Xu Liang , Baoan Li , Xuemin Yu

Motion planning is a crucial aspect of robot autonomy as it involves identifying a feasible motion path to a destination while taking into consideration various constraints, such as input, safety, and performance constraints, without…

机器人学 · 计算机科学 2023-06-14 Dengyu Zhang , Guobin Zhu , Qingrui Zhang

Estimating collision probabilities between robots and environmental obstacles or other moving agents is crucial to ensure safety during path planning. This is an important building block of modern planning algorithms in many application…

机器人学 · 计算机科学 2024-09-09 Felix Herrmann , Sebastian Zach , Jacopo Banfi , Jan Peters , Georgia Chalvatzaki , Davide Tateo
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