Study on Collision avoidance of UAV with Vision-based Sensor in Outdoor Environments
Hoijo Jeaong, Seungbin Lee, Seungkeun Kim, Jinyoung Suk · Journal of Institute of Control Robotics and Systems · 2021
This study investigates real-time path planning for UAVs (Unmanned Aerial Vehicles) to avoid obstacles in an outdoor environment in a three-dimensional space. First, we implement an algorithm to convert from Octomap to a grid map to implement a global grid map. Secondly, the ESDF (Euclidean Signed-Distance Field) algorithm is integrated into the path planning obtained through the JPS (Jump Point Search) algorithm, and the B-Spline algorithm is applied to modify the path to consider the dynamic constraint of UAVs. Finally, path planning algorithms are verified in real-time through simulation and flight testing. The simulation is based on the Gazebo environment using the open-source autopilot PX4 with the ROS. A depth camera performance is compared for an outdoor flight test to select a depth camera mounted on the drone. Moreover, the practical obstacle-avoidance performance of the proposed real-time route planning in an outdoor space is confirmed through a flight test.