Application of Decision Tree on Collision Avoidance System Design and Verification for Quadcopter

Abstract

ABSTRACT:The purpose of the research is to build a collision avoidance system with decision tree algorithm used for quadcopters. While the ultrasonic range finder judges the distance is in collision avoidance interval, the access will be replaced from operator to the system to control the altitude of the UAV. According to the former experiences on operating quadcopters, we can obtain the appropriate pitch angle. The UAS implement the following three motions to avoid collisions. Case1: initial slow avoidance stage, Case2: slow avoidance stage and Case3: Rapid avoidance stage. Then the training data of collision avoidance test will be transmitted to the ground station via wireless transmission module to further analysis. The entire decision tree algorithm of collision avoidance system, transmission data, and ground station have been verified in some flight tests. In the flight test, the quadcopter can implement avoidance motion in real-time and move away from obstacles steadily. In the avoidance area, the authority of the collision avoidance system is higher than the operator and implements the avoidance process. The quadcopter can successfully fly away from the obstacles in 1.92 meter per second and the minimum distance between the quadcopter and the obstacle is 1.05 meters.

The Impact of LiDAR Configuration on Goal-Based Navigation within a Deep Reinforcement Learning Framework

“…Collision avoidance and path planning problems have been investigated and solved using many techniques, such as RRT, A, A*, RRT*, and decision trees [ 11 , 12 , 13 , 14 ]. These techniques are mostly suitable for applications where the environment state is known and not changing.…”