Relative Positioning for Aerial Robot Path Planning in GPS Denied Environment
- URL: http://arxiv.org/abs/2409.10193v1
- Date: Mon, 16 Sep 2024 11:35:39 GMT
- Title: Relative Positioning for Aerial Robot Path Planning in GPS Denied Environment
- Authors: Farzad Sanati,
- Abstract summary: This paper tackles one of the most important factors in autonomous UAV navigation, namely Initial Positioning sometimes called Localisation.
It will enable a team of autonomous UAVs to establish a relative position to their base of operation to be able to commence a team search and reconnaissance in a bushfire-affected area.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: One of the most useful applications of intelligent aerial robots sometimes called Unmanned Aerial Vehicles (UAV) in Australia is known to be in bushfire monitoring and prediction operations. A swarm of autonomous drones/UAVs programmed to work in real-time observing the fire parameters using their onboard sensors would be valuable in reducing the life-threatening impact of that fire. However autonomous UAVs face serious challenges in their positioning and navigation in critical bushfire conditions such as remoteness and severe weather conditions where GPS signals could also be unreliable. This paper tackles one of the most important factors in autonomous UAV navigation, namely Initial Positioning sometimes called Localisation. The solution provided by this paper will enable a team of autonomous UAVs to establish a relative position to their base of operation to be able to commence a team search and reconnaissance in a bushfire-affected area and find their way back to their base without the help of GPS signals.
Related papers
- Long-Range Vision-Based UAV-assisted Localization for Unmanned Surface Vehicles [7.384309568198598]
Global positioning system (GPS) has become an indispensable navigation method for field operations with unmanned surface vehicles (USVs) in marine environments.
GPS may not always be available outdoors because it is vulnerable to natural interference and malicious jamming attacks.
We present a novel method that utilizes an Unmanned Aerial Vehicle (UAV) to assist in localizing USVs in restricted marine environments.
arXiv Detail & Related papers (2024-08-21T08:37:37Z) - MSight: An Edge-Cloud Infrastructure-based Perception System for
Connected Automated Vehicles [58.461077944514564]
This paper presents MSight, a cutting-edge roadside perception system specifically designed for automated vehicles.
MSight offers real-time vehicle detection, localization, tracking, and short-term trajectory prediction.
Evaluations underscore the system's capability to uphold lane-level accuracy with minimal latency.
arXiv Detail & Related papers (2023-10-08T21:32:30Z) - Efficient Real-time Smoke Filtration with 3D LiDAR for Search and Rescue
with Autonomous Heterogeneous Robotic Systems [56.838297900091426]
Smoke and dust affect the performance of any mobile robotic platform due to their reliance on onboard perception systems.
This paper proposes a novel modular computation filtration pipeline based on intensity and spatial information.
arXiv Detail & Related papers (2023-08-14T16:48:57Z) - Autonomous Systems: Autonomous Systems: Indoor Drone Navigation [0.0]
The system creates a simulated quadcopter capable of travelling autonomously in an indoor environment.
The goal is to use the slam toolbox for ROS and the Nav2 navigation system framework to construct a simulated drone.
arXiv Detail & Related papers (2023-04-18T10:40:00Z) - UAV-aided RF Mapping for Sensing and Connectivity in Wireless Networks [52.14281905671453]
The use of unmanned aerial vehicles (UAV) as flying radio access network (RAN) nodes offers a promising complement to traditional fixed terrestrial deployments.
Radio mapping is one of the challenges related to this task, referred here as radio mapping.
The advantages induced by radio-mapping in terms of connectivity, sensing, and localization performance are illustrated.
arXiv Detail & Related papers (2022-05-06T16:16:08Z) - ADAPT: An Open-Source sUAS Payload for Real-Time Disaster Prediction and
Response with AI [55.41644538483948]
Small unmanned aircraft systems (sUAS) are becoming prominent components of many humanitarian assistance and disaster response operations.
We have developed the free and open-source ADAPT multi-mission payload for deploying real-time AI and computer vision onboard a sUAS.
We demonstrate the example mission of real-time, in-flight ice segmentation to monitor river ice state and provide timely predictions of catastrophic flooding events.
arXiv Detail & Related papers (2022-01-25T14:51:19Z) - Autonomous Aerial Robot for High-Speed Search and Intercept Applications [86.72321289033562]
A fully-autonomous aerial robot for high-speed object grasping has been proposed.
As an additional sub-task, our system is able to autonomously pierce balloons located in poles close to the surface.
Our approach has been validated in a challenging international competition and has shown outstanding results.
arXiv Detail & Related papers (2021-12-10T11:49:51Z) - A Multi-UAV System for Exploration and Target Finding in Cluttered and
GPS-Denied Environments [68.31522961125589]
We propose a framework for a team of UAVs to cooperatively explore and find a target in complex GPS-denied environments with obstacles.
The team of UAVs autonomously navigates, explores, detects, and finds the target in a cluttered environment with a known map.
Results indicate that the proposed multi-UAV system has improvements in terms of time-cost, the proportion of search area surveyed, as well as successful rates for search and rescue missions.
arXiv Detail & Related papers (2021-07-19T12:54:04Z) - AutoSOS: Towards Multi-UAV Systems Supporting Maritime Search and Rescue
with Lightweight AI and Edge Computing [27.15999421608932]
This paper presents the research directions of the AutoSOS project, where we work in the development of an autonomous multi-robot search and rescue assistance platform.
The platform is meant to perform reconnaissance missions for initial assessment of the environment using novel adaptive deep learning algorithms.
When drones find potential objects, they will send their sensor data to the vessel to verity the findings with increased accuracy.
arXiv Detail & Related papers (2020-05-07T12:22:15Z) - Dynamic Radar Network of UAVs: A Joint Navigation and Tracking Approach [36.587096293618366]
An emerging problem is to track unauthorized small unmanned aerial vehicles (UAVs) hiding behind buildings.
This paper proposes the idea of a dynamic radar network of UAVs for real-time and high-accuracy tracking of malicious targets.
arXiv Detail & Related papers (2020-01-13T23:23:09Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.