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Recently, there have been numerous advances in the development of biologically inspired lightweight Micro Aerial Vehicles (MAVs). While autonomous navigation is fairly straight-forward for large UAVs as expensive sensors and monitoring…

This paper presents our method for enabling a UAV quadrotor, equipped with a monocular camera, to autonomously avoid collisions with obstacles in unstructured and unknown indoor environments. When compared to obstacle avoidance in ground…

Robotics · Computer Science 2019-11-20 Abhik Singla , Sindhu Padakandla , Shalabh Bhatnagar

In practical applications, autonomous quadrotors are still facing significant challenges, such as the detection and avoidance of very small and even dynamic obstacles (e.g., tree branches, power lines). In this paper, we propose a compact,…

Robotics · Computer Science 2021-03-02 Fanze Kong , Wei Xu , Fu Zhang

Autonomous unmanned aerial vehicle (UAV) navigation in orchards presents significant challenges due to obstacles and GPS-deprived environments. In this work, we introduce a learning-based approach to achieve vision-based navigation of UAVs…

Robotics · Computer Science 2025-08-11 Peng Wei , Prabhash Ragbir , Stavros G. Vougioukas , Zhaodan Kong

Cameras provide a rich source of information while being passive, cheap and lightweight for small and medium Unmanned Aerial Vehicles (UAVs). In this work we present the first implementation of receding horizon control, which is widely used…

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…

Systems and Control · Electrical Eng. & Systems 2020-03-03 Jiajun Ou , Xiao Guo , Ming Zhu , Wenjie Lou

Navigating unmanned aerial vehicles (UAVs) through cluttered and dynamic environments remains a significant challenge, particularly when dealing with fast-moving or sudden-appearing obstacles. This paper introduces a complete LiDAR-based…

Robotics · Computer Science 2025-04-25 Huajie Wu , Wenyi Liu , Yunfan Ren , Zheng Liu , Hairuo Wei , Fangcheng Zhu , Haotian Li , Fu Zhang

Performing rescuing and surveillance operations with autonomous ground and aerial vehicles become more and more apparent task. Involving unmanned robot systems allows making these operations more efficient, safe and reliable especially in…

Robotics · Computer Science 2011-11-03 Serge Kernbach , Kristof Jebens

Unmanned aerial vehicles (UAV) are commonly used for missions in unknown environments, where an exact mathematical model of the environment may not be available. This paper provides a framework for using reinforcement learning to allow the…

Robotics · Computer Science 2018-01-17 Huy X. Pham , Hung M. La , David Feil-Seifer , Luan V. Nguyen

High speed navigation through unknown environments is a challenging problem in robotics. It requires fast computation and tight integration of all the subsystems on the robot such that the latency in the perception-action loop is as small…

We present a micro aerial vehicle (MAV) system, built with inexpensive off-the-shelf hardware, for autonomously following trails in unstructured, outdoor environments such as forests. The system introduces a deep neural network (DNN) called…

Robotics · Computer Science 2017-07-25 Nikolai Smolyanskiy , Alexey Kamenev , Jeffrey Smith , Stan Birchfield

Micro aerial vehicles (MAVs) have high potential for information gathering tasks to support situation awareness in search and rescue scenarios. Manually controlling MAVs in such scenarios requires experienced pilots and is error-prone,…

Robotics · Computer Science 2022-08-15 Daniel Schleich , Marius Beul , Jan Quenzel , Sven Behnke

A collision avoidance system based on simple digital cameras would help enable the safe integration of small UAVs into crowded, low-altitude environments. In this work, we present an obstacle avoidance system for small UAVs that uses a…

Robotics · Computer Science 2021-11-04 Kyle Hatch , John Mern , Mykel Kochenderfer

Micro Air Vehicles (MAVs) are increasingly being used for complex or hazardous tasks in enclosed and cluttered environments such as surveillance or search and rescue. With this comes the necessity for sensors that can operate in poor…

Robotics · Computer Science 2021-03-04 Nikhil Wessendorp , Raoul Dinaux , Julien Dupeyroux , Guido de Croon

Reliable deployment of Unmanned Aerial Vehicles (UAVs) in cluttered unknown environments requires accurate sensors for Global Navigation Satellite System (GNSS)-denied localization and obstacle avoidance. Such a requirement limits the usage…

This letter describes a method for autonomous aerial cinematography with distributed lighting by a team of unmanned aerial vehicles (UAVs). Although camera-carrying multi-rotor helicopters have become commonplace in cinematography, their…

Autonomous flight of micro air vehicles (MAVs) in unknown, cluttered environments remains challenging for time-critical missions due to conservative maneuvering strategies. This article presents an integrated planning and control framework…

Robotics · Computer Science 2026-01-13 Xin Guan , Fangguo Zhao , Qianyi Wang , Chengcheng Zhao , Jiming Chen , Shuo Li

Quadrotors are agile. Unlike most other machines, they can traverse extremely complex environments at high speeds. To date, only expert human pilots have been able to fully exploit their capabilities. Autonomous operation with on-board…

As the market for commercially available unmanned aerial vehicles (UAVs) booms, there is an increasing number of small, teleoperated or autonomous aircraft found in protected or sensitive airspace. Existing solutions for removal of these…

Robotics · Computer Science 2021-07-06 Anish Bhattacharya

Interest in utilizing autonomous uncrewed aerial vehicles (UAVs) for under-canopy forest remote sensing has increased in recent years, resulting in the publication of numerous autonomous flight algorithms in the scientific literature. To…

Robotics · Computer Science 2026-05-28 Aleksi Karhunen , Teemu Hakala , Väinö Karjalainen , Eija Honkavaara
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