Real-Time Terrain-Following of an Autonomous Quadrotor by Multi-Sensor Fusion and Control

Abstract

For the application of the autonomous guidance of a quadrotor from confined undulant ground, terrain-following is the major issue for flying at a low altitude. This study has modified the open-source autopilot based on the integration of a multi-sensor receiver (a Global Navigation Satellite System (GNSS)), a Lidar-lite (a laser-range-finder device), a barometer and a low-cost inertial navigation system (INS)). These automatically control the position, attitude and height (a constant clearance above the ground) to allow terrain-following and avoid obstacles based on multi-sensors that maintain a constant height above flat ground or with obstacles. The INS/Lidar-lite integration is applied for the attitude and the height stabilization, respectively. The height control is made by the combination of an extended Kalman filter (EKF) estimator and a cascade proportional-integral-derivative (PID) controller that is designed appropriately for the noise characteristics of low accuracy sensors. The proposed terrain-following is tested by both simulations and real-world experiments. The results indicate that the quadrotor can continuously navigate and avoid obstacles at a real-time response of reliable height control with the adjustment time of the cascade PID controller improving over 50% than that of the PID controller.

Research on multi-sensor-based online inspection technology for electric vehicle charging pile transfer type equipment

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A Docking Mechanism Based on a Stewart Platform and Its Tracking Control Based on Information Fusion Algorithm

“…[ 38 ] used the sensor fusion algorithm of the Kalman filter to enable ground vehicles to obtain continuous error information from GPS. Yang Yuan and Huang Yongjiang [ 39 ] used the multi-sensor fusion algorithm of Global Navigation Satellite System (GNSS), Lidar-Lite (laser rangefinder equipment), barometer and low-cost inertial navigation system (INS) to control and track the quadrotor aircraft in real time so that it can respond to real-time continuous navigation and obstacle avoidance. Studying the multi-sensor data fusion algorithm, Setareh Yazdkhasti [ 40 ] proposed an integration algorithm based on the combination of fuzzy logic controller and Kalman filter, which further enhanced the reliability and accuracy of data.…”

Stabilization and Tracking of a Quadrotor Using Modified Sigmoid Sliding Mode Control

“…Accurate attitude information is obtained through an additional inertia measurement unit along with gyroscope. Continuous direction update of quadrotor can also improve flight performance by using a magnetometer [ 29 , 30 ]. The simulation compared the performance of CSMC, BS-SMC, and MS-SMC presented in this paper.…”