An Algorithm for Local Dynamic Map Generation for Safe UAV Navigation

Abstract

For safe UAV navigation and to avoid collision, it is essential to have accurate and real-time perception of the environment surrounding the UAV, such as free area detection and recognition of dynamic and static obstacles. The perception system of the UAV needs to recognize information such as the position and velocity of all objects in the surrounding local area regardless of the type of object. At the same time, a probability based representation taking into account the noise of the sensor is also essential. In addition, a software design with efficient memory usage and operation time is required in consideration of the hardware limitations of the UAVs. In this paper, we propose a 3D Local Dynamic Map (LDM) generation algorithm for a perception system for UAVs. The proposed LDM uses a circular buffer as a data structure to ensure low memory usage and fast operation speed. A probability based occupancy map is created using sensor data and the position and velocity of each object are calculated through clustering between grid voxels using the occupancy map and velocity estimation based on a particle filter. The objects are predicted using the position and velocity of each object and this is reflected in the occupancy map. This process is continuously repeated and the flying environment of the UAV can be expressed in a three-dimensional grid map and the state of each object. For the evaluation of the proposed LDM, we constructed simulation environments and the UAV for outdoor flying. As an evaluation factor, the occupancy grid is accuracy evaluated and the ground truth velocity and the estimated velocity are compared.