Amidst the increasing deployment of Autonomous Aerial Vehicles (AAVs), ensuring robust hazard detection and avoidance mechanisms is impera-tive for safe operations. This study proposes the integration of ORB (Oriented FAST and Rotated BRIEF) with ROS (Robot Operating System) to support AAVs’ ability to perceive and navigate complex environments, thereby enhancing overall safety and reliability. The integration of ORB with ROS presents a novel approach to enhance hazard detection and avoidance capabilities in Autonomous Aerial Vehicles (AAVs). By seamlessly incorporating ORB within the ROS framework, this integration enables real-time perception of hazards in the AAV’s environment. Additionally, simulations conducted using the Gazebo simulator validate the efficacy of the proposed approach. In tandem with hazard detection using ORB, the landing trajectory prediction leverages a combination of A* algorithm and RRT algorithm, ensuring efficient and safe path planning. This paper also discusses the technical details of the integration process, including theoretical foundations and implementation methodologies for both hazard detection and landing trajectory prediction. Experimental results showcase the effectiveness of the integrated system in improving AAV autonomy and safety. This approach holds promise for advancing AAV technology and fostering safer and more reliable autonomous aerial operations across various applications.