We describe a new framework for computer vision-based cooperative uav-assisted path planning for autonomous ground vehicles. In recent years, unmanned aerial vehicles (UAVs) have proved to be beneficial in many applications and services including path planning for autonomous vehicles. Most of the path planning applications assumes the availability of a digital map that allows a vehicle, be it ground or aerial, to navigate through landmarks and obstacles. However, in the scenario of unavailable maps especially during a natural disaster or a in war zone, it becomes extremely handy to have a drone that serves as an eye in the sky that explores the surrounding environment, and generates in real-time a trajectory guiding the vehicles on the ground around obstacles and obstructions. In this research, the UAV, serving as the eye in the sky is equipped with a camera that collects images of the surroundings and assists the ground vehicle in planning its path towards its final destination. Our approach includes the use of a vision-based algorithm which recognizes roads, pathways and obstacles, and calculates a path around them towards the destination. Simultaneously, the UAV keeps track of the ground vehicle progress towards the destination by monitoring and tracking its movement. The generation of the trajectory is based on an enhanced version of the A∗algorithm. The experimental setup includes a robot and a drone, and an ultra-wide band (UWB) indoor positioning system which allows the vehicles to know their current location.