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In this paper, we propose an autonomous UAV path planning framework using deep reinforcement learning approach. The objective is to employ a self-trained UAV as a flying mobile unit to reach spatially distributed moving or static targets in…

机器人学 · 计算机科学 2020-03-25 Omar Bouhamed , Hakim Ghazzai , Hichem Besbes , Yehia Massoud

Urban Air Mobility, the scenario where hundreds of manned and Unmanned Aircraft System (UAS) carry out a wide variety of missions (e.g. moving humans and goods within the city), is gaining acceptance as a transportation solution of the…

系统与控制 · 电气工程与系统科学 2021-01-27 Alëna Rodionova , Yash Vardhan Pant , Connor Kurtz , Kuk Jang , Houssam Abbas , Rahul Mangharam

A novel framework is proposed for the trajectory design of multiple unmanned aerial vehicles (UAVs) based on the prediction of users' mobility information. The problem of joint trajectory design and power control is formulated for…

信号处理 · 电气工程与系统科学 2019-06-05 Xiao Liu , Yuanwei Liu , Yue Chen , Lajos Hanzo

The rapid development of unmanned aerial vehicles (UAV) puts forward a higher requirement for autonomous obstacle avoidance. Due to the limited payload and power supply, small UAVs such as quadrotors usually carry simple sensors and…

系统与控制 · 电气工程与系统科学 2020-03-03 Jiajun Ou , Xiao Guo , Ming Zhu , Wenjie Lou

With the rapid development of unmanned aerial vehicles (UAVs), it is paramount to ensure safe and efficient operations in open airspaces. The remote identification (Remote ID) is deemed an effective real-time UAV monitoring system by the…

信号处理 · 电气工程与系统科学 2025-08-12 Ziye Jia , Yian Zhu , Qihui Wu , Lei Zhang , Sen Yang , Zhu Han

In unseen and complex outdoor environments, collision avoidance navigation for unmanned aerial vehicle (UAV) swarms presents a challenging problem. It requires UAVs to navigate through various obstacles and complex backgrounds. Existing…

机器人学 · 计算机科学 2024-07-16 Jiafan Zhuang , Gaofei Han , Zihao Xia , Boxi Wang , Wenji Li , Dongliang Wang , Zhifeng Hao , Ruichu Cai , Zhun Fan

This paper presents a multi-agent reinforcement learning (MARL) framework for cooperative collision avoidance of UAV swarms leveraging domain knowledge-driven reward. The reward is derived from knowledge in the domain of image processing,…

多智能体系统 · 计算机科学 2025-07-16 Shuangyao Huang , Haibo Zhang , Zhiyi Huang

This letter proposes a distributed 3D leader-follower formation (3D-LFF) control framework for multi-UAV systems that achieves formation tracking while enforcing perception safety constraints. Maintaining safe, vision-based 3D-LFF is…

系统与控制 · 电气工程与系统科学 2026-05-19 Immanuel R. Santjoko , Richie R. Suganda , Miao Pan , Bin Hu

This article proposes a novel framework for unmaned aerial vehicle (UAV) networks with massive access capability supported by non-orthogonal multiple access (NOMA). In order to better understand NOMA enabled UAV networks, three case studies…

信号处理 · 电气工程与系统科学 2018-09-18 Yuanwei Liu , Zhijin Qin , Yunlong Cai , Yue Gao , Geoffrey Ye Li , Arumugam Nallanathan

This article presents a three-dimensional nonlinear trajectory tracking control strategy for unmanned aerial vehicles (UAVs) in the presence of spatial constraints. As opposed to many existing control strategies, which do not consider…

系统与控制 · 电气工程与系统科学 2024-07-16 Saurabh Kumar , Shashi Ranjan Kumar , Abhinav 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

A novel autonomous chunk-based aerial additive manufacturing framework is presented, supported with experimental demonstration advancing aerial 3D printing. An optimization-based decomposition algorithm transforms structures into…

This paper investigates a novel active-sensing-based obstacle avoidance paradigm for flying robots in dynamic environments. Instead of fusing multiple sensors to enlarge the field of view (FOV), we introduce an alternative approach that…

机器人学 · 计算机科学 2021-02-18 Gang Chen , Wei Dong , Xinjun Sheng , Xiangyang Zhu , Han Ding

In this work, we present a pragmatic approach to enable unmanned aerial vehicle (UAVs) to autonomously perform highly complicated tasks of object pick and place. This paper is largely inspired by challenge-2 of MBZIRC 2020 and is primarily…

机器人学 · 计算机科学 2021-01-19 Ashish Kumar , Mohit Vohra , Ravi Prakash , L. Behera

Unmanned aerial vehicles (UAVs) are often used for navigating dangerous terrains, however they are difficult to pilot. Due to complex input-output mapping schemes, limited perception, the complex system dynamics and the need to maintain a…

机器人学 · 计算机科学 2021-03-02 Kal Backman , Dana Kulić , Hoam Chung

In this paper we study the problem of steering a team of Unmanned Aerial Vehicles (UAVs) toward a static configuration which maximizes the visibility of a 3D environment. The UAVs are assumed to be equipped with visual sensors constrained…

机器人学 · 计算机科学 2019-01-31 Alessandro Renzaglia , Jilles Dibangoye , Vincent Le Doze , Olivier Simonin

This paper addresses the three-dimensional path-following guidance problem for unmanned aerial vehicles under explicit actuator constraints. Unlike conventional approaches that assume unbounded control inputs or handle saturation…

系统与控制 · 电气工程与系统科学 2026-03-31 Vinay Kathiriya , Saurabh Kumar , Shashi Ranjan Kumar

This paper proposes a perception-shared and swarm trajectory global optimal (STGO) algorithm fused UAVs formation motion planning framework aided by an active sensing system. First, the point cloud received by each UAV is fit by the…

机器人学 · 计算机科学 2022-03-01 Peng Peng , Wei Dong , Gang Chen , Xiangyang Zhu

This work presents a novel data-driven multi-layered planning and control framework for the safe navigation of a class of unmanned ground vehicles (UGVs) in the presence of unknown stationary obstacles and additive modeling uncertainties.…

机器人学 · 计算机科学 2024-03-06 Skylar X. Wei , Lu Gan , Joel W. Burdick

This article proposes a novel control architecture using a centralized nonlinear model predictive control (CNMPC) scheme for controlling multiple micro aerial vehicles (MAVs). The control architecture uses an augmented state system to…

机器人学 · 计算机科学 2021-09-03 Björn Lindqvist , Sina Sharif Mansouri , Pantelis Sopasakis , George Nikolakopoulos