Guidance, Navigation And Control System Research Articles

A multi-platform Guidance, Navigation and Control system for the autosub family of Autonomous Underwater Vehicles

Over the last decade, there has been a proliferation of marine robots such as Unmanned Surface Vehicles (USVs), Autonomous Underwater Vehicles (AUVs) and underwater gliders. The variety of vehicles’ capabilities and styles has led to numerous strategies to address the Guidance, Navigation and Control (GNC) tasks. In particular, a recent trend in the advancements of GNC systems is to develop modular, multi-platform solutions. This paper illustrates the approach followed in the development of the GNC system for the different types of AUV of the Autosub family. The presented system is decomposed into several interconnected components, each implemented as a standalone software module. Each component is highly-reconfigurable and easily extensible, and the interactions between the modules rely on generic-purpose interfaces. Such a design enables the execution of a broad range of autonomous missions, as well as the integration and deployment of the system on marine platforms with very diverse characteristics, not limited to the vehicles of the Autosub class. Experimental results obtained in real-time during in water campaigns are provided to demonstrate the effectiveness of the proposed system and its versatility on a wide range of platforms and missions.

Visual based GNC system from prototype to flight software

Juventas is a 6U CubeSat which is part of HERA planetary defense mission and takes advantage of an innovative visual based guidance, navigation and control (GNC) system to perform autonomous navigation in the proximity of the Didymain system. The GNC system is designed to ensure safe navigation in the harsh and unpredictable environment of deep space and finally to take more risks by landing on the surface of Dimorphos. To achieve a qualitative software (SW) product, a dedicated procedure of SW lifecycle is developed by starting with GNC and image processing design, which concludes with the final embedded system that will perform the visual navigation task. A Design, Development, Verification and Validation (DDVV) approach is developed to achieve the flight software: model in the loop (MIL), auto-coding, software in the loop (SIL), processor in the loop (PIL) and finally hardware in the loop (HIL). The DDVV is developed by having as guideline the ECSS standards for SW. The flight software reaches maturity by performing dynamic/static code analysis and code coverage. To ensure an optimal process, a waterfall life-cycle is considered, where dedicated MIL, SIL, PIL and HIL test benches are developed to fully support the activity and to reduce to minimum the development costs.[7]

Kinetic impactor for a short warning asteroid deflection

In this paper, GMV as a major AOCS (Attitude Orbit Control System)/GNC (Guidance, Navigation and Control) system provider presents its work on the development of a GNC system for a Kinetic Impact mission. Asteroid impacts on Earth are a known source of extinction and played an important role in the evolution of life on Earth. This comes as no surprise given the high number of objects orbiting in Earth’s vicinity—asteroid impacts become a question of “when” rather than “if”.This comes as no surprise given the high number of objects orbiting in Earth’s vicinity—asteroid impacts become a question of “when” rather than “if”. Under this motivation, thousands of potentially hazardous asteroids (PHAs) are monitored around the globe and naturally the question on the next step rose: What can we do when an incoming asteroid is identified as being on collision course with Earth? This is the motivation behind the field of Planetary Defence. Several mitigation strategies are being studied, but most of these have technology readiness levels still far off from the required. The one that comes closest is the kinetic impactor concept, which is the focus of this work. The concept is simple from a theoretical standpoint - a spacecraft (impactor) is sent into a collision course against the hazard NEO transferring enough momentum through kinetic energy to slightly change the NEO’s trajectory and causes it to miss the Earth.The main component of kinetic impactors is the GNC, due to the necessity of a fully autonomous system. The major elements are the camera and the guidance, since they will allow detecting the target and modifying its trajectory to have a successful impact, respectively. This study includes the implementation of the required algorithms as well as an analysis of their performance in the impact scenario.The main variables that control the simulations have been examined in order to determine the design limits. The sensitivity analysis illustrates that the errors introduced in the model were chosen conservatively, inasmuch as the impact could be reached introducing higher uncertainties and errors in the systems considered. In general, even with the not excessively complex algorithms employed, the performance of the GNC is good. This study opens the door for the development of a kinetic impactor mission.

UAV Path Planning Based on Multi-Layer Reinforcement Learning Technique

Unmanned aerial vehicles (UAVs) have been widely used in many applications due to its small size, swift mobility and low cost. Therefore, the study of guidance, navigation and control (GNC) system of UAV has becoming a popular research direction. Path planning plays an important role in the GNC system. In this paper, a multi-layer path planning algorithm based on reinforcement learning (RL) technique is proposed. Compared to the classic Q-learning, the proposed multi-layer algorithm has a distinct advantage that it collects both global and local information which greatly improves overall performance. The proposed RL algorithm has two layers, the higher layer deals with the local information, which could be considered as a short-term strategy. The lower layer deals with the global information, which could be considered as a long-term strategy. Both the higher layer and lower layer are working in harmony to plan a collision-free path. B-spline curve approach is applied for on-line path smoothing. Simulation results in different scenarios prove the effectiveness of multi-layer Q-learning algorithm.

Applying Neural Networks in Aerial Vehicle Guidance to Simplify Navigation Systems

The Guidance, Navigation and Control (GNC) of air and space vehicles has been one of the spearheads of research in the aerospace field in recent times. Using Global Navigation Satellite Systems (GNSS) and inertial navigation systems, accuracy may be detached from range. However, these sensor-based GNC systems may cause significant errors in determining attitude and position. These effects can be ameliorated using additional sensors, independent of cumulative errors. The quadrant photodetector semiactive laser is a good candidate for such a purpose. However, GNC systems’ development and construction costs are high. Reducing costs, while maintaining safety and accuracy standards, is key for development in aerospace engineering. Advanced algorithms for getting such standards while eliminating sensors are cornerstone. The development and application of machine learning techniques to GNC poses an innovative path for reducing complexity and costs. Here, a new nonlinear hybridization algorithm, which is based on neural networks, to estimate the gravity vector is presented. Using a neural network means that once it is trained, the physical-mathematical foundations of flight are not relevant; it is the network that returns dynamics to be fed to the GNC algorithm. The gravity vector, which can be accurately predicted, is used to determine vehicle attitude without calling for gyroscopes. Nonlinear simulations based on real flight dynamics are used to train the neural networks. Then, the approach is tested and simulated together with a GNC system. Monte Carlo analysis is conducted to determine performance when uncertainty arises. Simulation results prove that the performance of the presented approach is robust and precise in a six-degree-of-freedom simulation environment.

X-ray pulsar-based GNC system for formation flying in high Earth orbits

In this paper, comprehensive pulsar-based Guidance, Navigation and Control (GNC) system is designed and applied to satellites formation flying. The complete autonomy of the X-ray pulsar navigation technology provides both absolute and relative positioning information for spacecraft in or even beyond the solar system, and provides an interesting alternative solution to classical navigation techniques such as Global Navigation Satellite System (GNSS). The navigation measurements are studied using a relative time of arrival (RTOA) estimating method, which takes advantage of the noise-filtered pulsar profiles in the cross-correlation estimator to achieve robustness. An adaptive Kalman filter is exploited to minimise the effect of processing noises caused by the primary satellite. A linear Quadratic Gaussian regulator is then applied to control the formation. Two different configurations are studied in high Earth orbits (HEOs). Simulation results show that the designed GNC algorithms can fulfill the required accuracy (10% of the baseline) of the Magnetospheric Multiscale Mission, with the position root-mean-square error of ~1.6 km. . The excellent robustness of the designed GNC system on the positioning errors of the primary satellite suggests a role for X-ray pulsar-based formation flying technique in HEOs and the solar system.

Lunar Flashlight CubeSat GNC system development

JPL is developing the Lunar Flashlight (LF) CubeSat mission, a 6U 14 kg spacecraft whose objective is to demonstrate new technology and measure potential surface water ice deposits in the permanently shadowed region (PSR) of the moon in preparation of future possible human lunar exploration. This mission will become the first interplanetary CubeSat to orbit the Moon. It uses a new green propulsion system as well as an instrument with spectrally tuned IR laser technology to search for volatiles in a specific region of the moon. The Guidance, Navigation and Control (GNC) system is crucial for delivering the spacecraft from Earth into Lunar orbit and supporting scientific measurements. Due to the challenging lunar orbit insertion and high tip off rate out of launch vehicle's dispenser, the initial design concept using solar sail propulsion accompanied with small commercial-on-the-shelf (COTS) reaction wheels was abandoned mid-course and replaced by a green propulsion system along with larger reaction wheels, both newly developed for LF. However, using thrusters for the small CubeSat created an additional challenge of controlling the spacecraft attitude. The story of the GNC system development, qualifications, technical challenges encountered, and lessons learned are discussed in this paper.

Hardware in the loop simulation for homing missiles

In this paper, we present a new method of testing the guidance, navigation and control (GNC) system of missiles with homing guidance based on image processing homing head. Testing of the GNC system of the homing missile is usually carried out on a five axis or three axis motion simulator in the hardware in the loop (HWIL) environment. HWIL testing on a five axis motion simulator is applicable to all guidance systems regardless of the type of detector used in the homing head, but equipping the laboratory is at least two times more expensive compared to the new method of testing presented here. The goal of this paper is to present a relatively cheap, simple and effective way of testing the guidance systems in cases when the type of detector used in the homing head is either television (TV) or Infra-Red (IR) camera, more precisely when image processing homing heads are used.

Guidance, Navigation and Control of Unmanned Airships under Time-Varying Wind for Extended Surveillance

This paper deals with the control of lighter-than-air vehicles, more specifically the design of an integrated guidance, navigation and control (GNC) scheme that is capable of navigating an airship through a series of constant-altitude, planar waypoints. Two guidance schemes are introduced, a track-specific guidance law and a proportional navigation guidance law, that provide the required signals to the corresponding controllers based on the airship position relative to a target waypoint. A novel implementation of the extended Kalman filter, namely the scheduled extended Kalman filter, estimates the required states and wind speed to enhance the performance of the track-specific guidance law in the presence of time-varying wind. The performance of the GNC system is tested using a high fidelity nonlinear dynamic simulation for a variety of flying conditions. Representative results illustrate the performance of the integrated system for chosen flight conditions.

Architecture design for reliable and reconfigurable FPGA-based GNC computer for deep space exploration

SRAM (static random access memory)-based FPGA (field programmable gate array), owing to its large capacity, high performance, and dynamical reconfiguration, has become an attractive platform for SoPC (system on programmable chip) development. However, as the configuration memory and logic memory of the SRAM-based FPGA are highly susceptible to SEUs (single-event upsets) in deep space, it is a challenge to design and implement a highly reliable FPGA-based system for spacecraft, and no practical architecture has been proposed. In this paper, a new architecture for a reliable and reconfigurable FPGAbased computer in a highly critical GNC (guidance navigation and control) system is proposed. To mitigate the effect of an SEU on the system, multi-layer reconfiguration and multi-layer TMR (triple module redundancy) techniques are proposed, with a reliable reconfigurable real-time operating system (SpaceOS) managing the system level fault tolerance of the computer in the architecture. The proposed architecture for the reconfigurable FPGA-based computer has been implemented with COTS (commercial off the shelf) FPGA and has firstly been applied to the GNC system of a circumlunar return and reentry flight vehicle. The in-orbit results show that the proposed architecture is capable of meeting the requirements of high reliability and high availability, and can provide the expressive varying functionality and runtime flexibility for an FPGA-based GNC computer in deep space.

Active debris removal GNC challenges over design and required ground validation

Because of the exponential growth of space debris, the access to space in the medium-term future is considered as being seriously compromised, particularly within LEO polar Sun-synchronous orbits and within geostationary orbits. The active debris removal (ADR) application poses new and challenging requirements on: first, the new required Guidance, Navigation and Control (GNC) technologies and, second, how to validate these new technologies before being applied in real missions. There is no doubt about the strong safety and collision risk aspects affecting the real operational ADR missions. But it shall be considered that even ADR demonstration missions will be affected by significant risk of collision during the demonstration, and that the ADR GNC systems/technologies to be used shall be well mature before using/demonstrating them in space. Specific and dedicated on-ground validation approaches, techniques and facilities are mandatory. The different ADR techniques can be roughly catalogued in three main groups (rigid capture, non-rigid capture and contactless). All of them have a strong impact on the GNC system of the active vehicle during the capture/proximity phase and, particularly, during the active vehicle/debris combo control phase after capture and during the de-orbiting phase. The main operational phases on an ADR scenario are: (1) ground controlled phase (ADR vehicle and debris are far), (2) fine orbit synchronization phase (ADR vehicle to reach debris ±V-bar), (3) short range phase (along track distance reduction till 10–100 s of metres), (4) terminal approach/capture phase and (5) de-orbiting. While phases 1–3 are somehow conventional and already addressed in detail during past/on-going studies related to rendezvous and/or formation flying, phases 4–5 are very specific and not mature in terms of GNC needed technologies and HW equipment. GMV is currently performing different internal activities and ESA studies/developments related to ADR mission, GNC and capture technologies. This paper focuses on some specific aspects and technologies related to ADR terminal phases involved technologies and ground validation approaches: (1) Terminal ADR approach phase using visual-based navigation (VBN). Potential Image Processing techniques and preliminary performances will be described, together with the challenge of generating on-ground realistic images as input for the HW/SW VBN system. Some results of image generation (including comparison with real flight image missions) and processing using GMV’s Optical Laboratory (image generation by rendering spacecraft 3D models and projecting on a screen in front of the HW camera) and using GMV’s platform-art ® laboratory to reproduce space-realistic physical scenarios (to be captured by a HW camera) using 1:1 physical spacecraft mock-ups in an absolutely dark environment with a Sun-like single illumination source. (2) Ground validation of GNC systems based on HW-in-the-Loop (HIL) test facilities, including realistic space-representative avionics (at processor, interfaces and real-time operating system), realistic and air-to-air stimulated breadboard perception sensors (IMU, optical cameras, laser 3D sensors) through the use of dynamic robotic devices hosting the active vehicle and debris mock-ups and reproducing accurately the spatial relative dynamic corresponding to an ADR scenario. This type of ground validation can effectively achieve validation in relevant environment, till TRL (Technology Readiness Level) 5/6 on ground and minimizing the uncertainty/risk of such technologies/systems with respect to its operational use. Description and video demonstration of some ADR applicable test case/s using GMV’s platform-art ® dynamic test facility will be included. Particular attention will be paid on the needed type of structural/functional active ADR vehicle and debris mock-ups, force/torque measurement and feedback capability over debris contact or momentum exchange actions, ground gravity compensation.

Guidance, navigation and control technologies of Chang’E-3 lunar rover

The jade rabbit lunar rover of ChangE-3 probe was the first explorer of China roaming on the surface of extratellurian celestials, which had the totally different guidance, navigation and control (GNC) technologies from the earth orbital spacecrafts. Several key technologies had been broken in GNC system of ChangE-3 lunar rover, such as autonomous position and attitude determination, multi-wheel motion control on lunar surface, binocular stereo visio based autonomous environment perception, traversibility quantitative analysis based path planning, structure-light vision based obstacle avoidance for emergence case, and experimentation on earth. Since December 14, 2013 the ChangE-3 probe landed successfully on the moon, the GNC system of jade rabbit lunar rover had been working well all the time, and accomplished the set mission. The GNC technologies employed in ChangE-3 Lunar Rover laid foundation for future space exploration. The mission requirement, system component, key technologies, work modes and so forth of GNC system were discussed systematically in this paper.

A novel approach for trajectory tracking of UAVs

Purpose The purpose of this paper is to present a novel approach for trajectory tracking of UAVS. Research on unmanned aircraft is constantly improving the autonomous flight capabilities of these vehicles to provide performance needed to use them in even more complex tasks. The UAV path planner (PP) plans the best path to perform the mission. This is a waypoint sequence that is uploaded on the flight management system providing reference to the aircraft guidance, navigation and control system (GNCS). The UAV GNCS converts the waypoint sequence in guidance references for the flight control system (FCS) that, in turn, generates the command sequence needed to track the optimum path.

Design and Simulation of an Improved Five Redundancy GNC System Architecture

Aerospace plane, the next generation manned spacecraft has the characteristics of high reliability and high security. Therefore, a five modular redundancy byzantine fault tolerant architecture is propose for the guidance, navigation and control (GNC) system. This architecture can give the system characteristic of double fault resilience, and is also suitable for solving Byzantine general problem. A semi-physical simulation is done, which is based on 1553B data bus and VxWorks operating system. The simulation result has verified the fault tolerant architecture and feasibility of the system implementation.

Integrated System for Autonomous Proximity Operations and Docking

An integrated system composed of guidance, navigation and control (GNC) system for autonomous proximity operations and the docking of two spacecraft was developed. The position maneuvers were determined through the integration of the statedependent Riccati equation formulated from nonlinear relative motion dynamics and relative navigation using rendezvous laser vision (Lidar) and a vision sensor system. In the vision sensor system, a switch between sensors was made along the approach phase in order to provide continuously effective navigation. As an extension of the rendezvous laser vision system, an automated terminal guidance scheme based on the Clohessy-Wiltshire state transition matrix was used to formulate a “V-bar hopping approach” reference trajectory. A proximity operations strategy was then adapted from the approach strategy used with the automated transfer vehicle. The attitude maneuvers, determined from a linear quadratic Gaussian-type control including quaternion based attitude estimation using star trackers or a vision sensor system, provided precise attitude control and robustness under uncertainties in the moments of inertia and external disturbances. These functions were then integrated into an autonomous GNC system that can perform proximity operations and meet all conditions for successful docking. A sixdegree of freedom simulation was used to demonstrate the effectiveness of the integrated system.

Impacting small Near Earth Objects

The design of a low-cost spacecraft to impact on a small, faint Near Earth Object (NEO), poses major challenges. This paper focuses on the terminal phase of such impact mission, analyzing the capability of autonomous Guidance, Navigation and Control (GNC) systems to compensate the deviations in the impact point to achieve a successful collision. The autonomous GNC system employs the information of the optical sensors to estimate the parameters allowing the computation of divert maneuvers to achieve the impact. GMV has developed a simulator, with different levels of sophistication, and a set of different GNC algorithms to help in the design process. This tool is used for different purposes such as: dimensioning the sensors and actuators, verifying mission requirements, computing figures of merit of different SC configurations and evaluating GNC performances. Four GNC algorithms are compared: low-thrust proportional navigation using a fading memory filter, high-thrust predictive guidance using either a Kalman filter or a batch-sequential least-squares filter, and a mid-thrust hybrid predictive-proportional guidance using a fading memory filter. Monte Carlo analysis using global-performances models of the optical sensors for each of these GNC algorithms are presented for two different asteroids (1989 ML and 2002 AT4), showing the mission parameters driving the mission performances. In addition, single-runs with high-fidelity optical sensors models are presented to validate the Monte Carlo simulations.

The Study of the Position Estimation for an Autonomous Land Vehicle

In this paper, we develop and implement a high integrity GNC(Guidance, Navigation, and Control) system, based on the combined use of the Global Positioning System (GPS) and an Inertial Measurement Unit (IMU), for autonomous land vehicle applications. This paper highlights guidance for the predetermined trajectory and navigation with detection of possible faults during the fusion process in order to enhance the integrity of the navigation loop. The implementation of the GNC system to the autonomous land vehicle presented with fault detection methodology considers high frequency faults from the GPS receiver caused by shadowing and multipath error The implementation, based on a low-cost, strapdown INS aided by standard GPS technology, is described. The results of the field test in the urban environment are presented and showed effectiveness of the GNC system.