Autonomous Navigation and Object Detection Using ROS 2 and YOLOv8
Yash Bhaskar1, Kartik Dolaskar2, Harshal Jadhav3, Mahesh Shirke4 , Prof. Kedar Kulkarni5
ybbhaskar19@gmail.com, kartikdolaskar.1106@gmail.com, harshaljadhav6565@gmail.com, maheshshirke1921@gmail.com, kedar.kulkarni@zealeducation.com
1,2,3,4 Undergraduate Student, Department of Robotics and Automation, Zeal College of Engineering and Research, Pune(MH), India
5 Assistant Professor, Department of Robotics and Automation, Zeal College of Engineering and Research, Pune(MH), India
---------------------------------------------------------------------***---------------------------------------------------------------------
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.
