This thesis is the result of a six-months research activity conducted at University of Denver (DU) Unmanned Systems Research Institute (DU2SRI), Colorado, USA. The objective of the thesis is the design of a bio-inspired 3D local path planning strategy for obstacle avoidance based on the optical flow field obtained by a frontal monocular camera mounted on a quadrotor UAV, with the requirement of being real-time implementable and runnable by onboard embedded hardware. Assuming the quadrotor is controlled in position and its path is defined in term of a list of waypoints, the strategy consists in generating an intermediate waypoint in order to avoid obstacles based on optical flow horizontal and vertical unbalance for horizontal and vertical avoidance, while for frontally approaching obstacles avoidance the concept of expansion of optical flow field is used.