A Compact Guidance, Navigation, and Control System for Unmanned Aerial Vehicles

Abstract

The Flight Control System 20 (FCS20) is a compact, self-contained Guidance, Navigation, and Control system that has recently been developed to enable advanced autonomous behavior in a wide range of Unmanned Aerial Vehicles (UAVs). The FCS20 uses a floating point Digital Signal Processor (DSP) for high level serial processing, a Field Programmable Gate Array (FPGA) for low level parallel processing, and GPS and Micro Electro Mechanical Systems (MEMS) sensors. In addition to guidance, navigation, and control functions, the FCS20 is capable of supporting advanced algorithms such as automated reasoning, artificial vision, and multi-vehicle interaction. The unique contribution of this paper is that it gives a complete overview of the FCS20 GN&C system, including computing, communications, and information aspects. Computing aspects of the FCS20 include details about the design process, hardware components, and board configurations, and specifications. Communications aspects of the FCS20 include descriptions of internal and external data flow. The information section describes the FCS20 Operating System (OS), the Support Vehicle Interface Library (SVIL) software, the navigation Extended Kalman Filter, and the neural network based adaptive controller. Finally, simulation-based results as well as actual flight test results that demonstrate the operation of the guidance, navigation, and control algorithms on a real Unmanned Aerial Vehicle (UAV) are presented.

Concurrent Learning for Improved Convergence in Adaptive Flight Control

“…The FCS 20 embedded autopilot system comes with an integrated navigation solution that fuses information using an extended Kalman filter from six degree of freedom inertial measurement sensors, Global Positioning System, air data sensor, and magnetometer to provide accurate state information. 12 The available state information includes velocity and position in global and body reference frames, accelerations along the body x, y, z axes, roll, pitch, yaw rates and attitude, barometric altitude, and air speed information. These measurements can be further used to determine the aircraft's velocity with respect to the air mass, and the flight path angle.…”

Integrated Guidance Navigation and Control for a Fully Autonomous Indoor UAS

“…The process model, given by Equations 28-31 below, is a set of nonlinear differential equations describing the vehicle motion as described in detail in [2,22]. The residual of the SLAM pose measurements (Equation 32) is the pose error (∆x, ∆y, ∆θ), which is expressed in the inertial frame.…”

“…2 In this implementation, the IMU measurements are incorporated at a fixed rate of 100Hz. In lieu of GPS position measurements and magnetometer heading measurements, the SLAM pose estimate and sonar altitude measurements are used, with updates at 10Hz and 20Hz respectively.…”

High-Frequency Sensor Data Acquisition System (SDAC) for Flight Control and Aerodynamic Data Collection

“…In 2003, Higashino and Sakurai developed a testbed vehicle, which included a data acquisition system and associated sensor units, to estimate aerodynamic characteristics. 25 27 NASA's EAV 28 and AirSTAR 29 programs produced testbed platforms that included avionics systems which are able to perform data collection and control. Finally in 2011, Brusov et al developed the PRP-J5 flight data acquisition system for small UAVs.…”