C-SADDLES: A Cyber Physical System Enabled Self Adaptable Drone Landing Pad for Rapid Battery Charging of Small Unmanned Aerial Systems

With the proliferation of drones and considerable growth of the drone application market, several areas related to the drone platform have shown promise of innovative approaches for enabling and furthering drone technology. One interesting and trending area is related to increasing the uptime of drones, which has proven to be a challenge for Small Unmanned Aircraft Systems (SUAS). One of the ground side approaches would be to provide a service that enables an adaptable system that could be quickly deployed in the field to deliver a fast and efficient battery charging system that caters to a wide variety of nano and small category of drones. This article outlines a simple, safe, and yet a novel method: contact-based drone charging station using image detection driving a control system that automatically aligns itself with an incoming drone performing a touchdown on the drone charging landing pad. An attendant QR code-based system enables correct battery charging via a database driven parameter marshaling. The entire system is internet enabled (Cyber Physical System) to provide an enhanced user interaction experience. The proposed method provides an improvement in energy efficiency and charging time compared to wireless charging methods.

Authors

Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/ssitcon62437.2024.10797136
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

C-SADDLES: A Cyber Physical System Enabled Self Adaptable Drone Landing Pad for Rapid Battery Charging of Small Unmanned Aerial Systems

Raveendra Nagaraj, D Nishchay, Paras Vanajole
UAV Applications and Optimization
article

C-SADDLES: A Cyber Physical System Enabled Self Adaptable Drone Landing Pad for Rapid Battery Charging of Small Unmanned Aerial Systems

Raveendra Nagaraj, D Nishchay, Paras Vanajole
article en

Abstract

With the proliferation of drones and considerable growth of the drone application market, several areas related to the drone platform have shown promise of innovative approaches for enabling and furthering drone technology. One interesting and trending area is related to increasing the uptime of drones, which has proven to be a challenge for Small Unmanned Aircraft Systems (SUAS). One of the ground side approaches would be to provide a service that enables an adaptable system that could be quickly deployed in the field to deliver a fast and efficient battery charging system that caters to a wide variety of nano and small category of drones. This article outlines a simple, safe, and yet a novel method: contact-based drone charging station using image detection driving a control system that automatically aligns itself with an incoming drone performing a touchdown on the drone charging landing pad. An attendant QR code-based system enables correct battery charging via a database driven parameter marshaling. The entire system is internet enabled (Cyber Physical System) to provide an enhanced user interaction experience. The proposed method provides an improvement in energy efficiency and charging time compared to wireless charging methods.

Affordable and clean energy
Openalex Percentile: Top 61%
UAV Applications and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

C-SADDLES: A Cyber Physical System Enabled Self Adaptable Drone Landing Pad for Rapid Battery Charging of Small Unmanned Aerial Systems — Raveendra Nagaraj, D Nishchay, et al. · (2024) | TGRS Research Map | TGRS