Autonomous Navigation and Object Detection Using ROS 2 and YOLOv8

Surveillance is a critical component of national security. Design and creation of a prototype Autonomous Mobile Robot (AMR) for surveillance using a YOLO v8 model consist of innovative aspects for quick surveillance operations across different terrain. The AMR with camouflage-like features to blend in with the environment uses ROS for autonomous navigation and YOLO for precise object detection. camera, face recognition, and motion detection with OpenCV, the AMR also incorporates an alarm notification system. The highly advanced obstacle detection and navigation guiding of the AMR. Field trials demonstrated that the AMR was able to move around without assistance while executing surveillance operations with ease, which demonstrated its prospects as an invaluable tool for use in the military and security services. The project introduces dramatic advancements in autonomous surveillance, with constant real-time monitoring involving limited human intervention. Its pairing with advanced detection systems and long-lasting hardware optimizes its performance in operations, rendering it a suitable option for hostile surveillance. Key Words: AMR, Surveillance, Open-Cv, YOLO v8, ROS2, Real Time Detection, Google Cloud, Twilio.

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-03-14
DOI
https://doi.org/10.55041/ijsrem42857
Primary Topic
Advanced Neural Network Applications
Type
article
Field-Weighted Citation Impact
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article

Autonomous Navigation and Object Detection Using ROS 2 and YOLOv8

Kedar M. Kulkarni, Himmat Tukaram Jadhav, Yash Bhaskar, Kartik Dolaskar et al.
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Advanced Neural Network Applications
article

Autonomous Navigation and Object Detection Using ROS 2 and YOLOv8

Kedar M. Kulkarni, Himmat Tukaram Jadhav, Yash Bhaskar, Kartik Dolaskar, Mahesh Shirke
article en

Abstract

Surveillance is a critical component of national security. Design and creation of a prototype Autonomous Mobile Robot (AMR) for surveillance using a YOLO v8 model consist of innovative aspects for quick surveillance operations across different terrain. The AMR with camouflage-like features to blend in with the environment uses ROS for autonomous navigation and YOLO for precise object detection. camera, face recognition, and motion detection with OpenCV, the AMR also incorporates an alarm notification system. The highly advanced obstacle detection and navigation guiding of the AMR. Field trials demonstrated that the AMR was able to move around without assistance while executing surveillance operations with ease, which demonstrated its prospects as an invaluable tool for use in the military and security services. The project introduces dramatic advancements in autonomous surveillance, with constant real-time monitoring involving limited human intervention. Its pairing with advanced detection systems and long-lasting hardware optimizes its performance in operations, rendering it a suitable option for hostile surveillance. Key Words: AMR, Surveillance, Open-Cv, YOLO v8, ROS2, Real Time Detection, Google Cloud, Twilio.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(03)
Openalex Percentile: Top 96%
Advanced Neural Network Applications
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