Obstacle Detection using Binocular Stereo Vision in Trajectory Planning for Quadcopter Navigation

Abstract

Quadcopters are one of the most versatile unmanned aerial vehicles due to its vertical take-off and landing as well as hovering capabilities. This research uses the Sum of Absolute Differences (SAD) block matching algorithm for stereo vision. A complementary filter was used in sensor fusion to combine obtained quadcopter orientation data from the accelerometer and the gyroscope. PID control was implemented for the motor control and VFH+ algorithm was implemented for trajectory planning. Results show that the quadcopter was able to consistently actuate itself in the roll, yaw and z-axis during obstacle avoidance but was however found to be inconsistent in the pitch axis during forward and backward maneuvers due to the significant noise present in the pitch axis angle outputs compared to the roll and yaw axes.