Autonomous Navigation for Mars Exploration

The autonomous navigation technology uses the multiple sensors to percept and estimate the spatial locations of the aerospace prober or the Mars rover and to guide their motions in the orbit or the Mars surface. In this chapter, the autonomous navigation methods for the Mars exploration are reviewed. First, the current development status of the autonomous navigation technology is summarized. The popular autonomous navigation methods, such as the inertial navigation, the celestial navigation, the visual navigation, and the integrated navigation, are introduced. Second, the application of the autonomous navigation technology for the Mars exploration is presented. The corresponding issues in the Entry Descent and Landing (EDL) phase and the Mars surface roving phase are mainly discussed. Third, some challenges and development trends of the autonomous navigation technology are also addressed

Robust vision based slope estimation and rocks detection for autonomous space landers

As future robotic surface exploration missions to other planets, moons and asteroids become more ambitious in their science goals, there is a rapidly growing need to significantly enhance the capabilities of entry, descent and landing technology such that landings can be carried out with pin-point accuracy at previously inaccessible sites of high scientific value. As a consequence of the extreme uncertainty in touch-down locations of current missions and the absence of any effective hazard detection and avoidance capabilities, mission designers must exercise extreme caution when selecting candidate landing sites. The entire landing uncertainty footprint must be placed completely within a region of relatively flat and hazard free terrain in order to minimise the risk of mission ending damage to the spacecraft at touchdown. Consequently, vast numbers of scientifically rich landing sites must be rejected in favour of safer alternatives that may not offer the same level of scientific opportunity. The majority of truly scientifically interesting locations on planetary surfaces are rarely found in such hazard free and easily accessible locations, and so goals have been set for a number of advanced capabilities of future entry, descent and landing technology. Key amongst these is the ability to reliably detect and safely avoid all mission critical surface hazards in the area surrounding a pre-selected landing location. This thesis investigates techniques for the use of a single camera system as the primary sensor in the preliminary development of a hazard detection system that is capable of supporting pin-point landing operations for next generation robotic planetary landing craft. The requirements for such a system have been stated as the ability to detect slopes greater than 5 degrees and surface objects greater than 30cm in diameter. The primary contribution in this thesis, aimed at achieving these goals, is the development of a feature-based,self-initialising, fully adaptive structure from motion (SFM) algorithm based on a robust square-root unscented Kalman filtering framework and the fusion of the resulting SFM scene structure estimates with a sophisticated shape from shading (SFS) algorithm that has the potential to produce very dense and highly accurate digital elevation models (DEMs) that possess sufficient resolution to achieve the sensing accuracy required by next generation landers. Such a system is capable of adapting to potential changes in the external noise environment that may result from intermittent and varying rocket motor thrust and/or sudden turbulence during descent, which may translate to variations in the vibrations experienced by the platform and introduce varying levels of motion blur that will affect the accuracy of image feature tracking algorithms. Accurate scene structure estimates have been obtained using this system from both real and synthetic descent imagery, allowing for the production of accurate DEMs. While some further work would be required in order to produce DEMs that possess the resolution and accuracy needed to determine slopes and the presence of small objects such as rocks at the levels of accuracy required, this thesis presents a very strong foundation upon which to build and goes a long way towards developing a highly robust and accurate solution

Use of Navigation Beacons to Support Lunar Vehicle Operations

To support a wide variety of lunar missions in a condensed regime, solutions are needed outside of the use of Earth-based orbit determination. This research presents an alternate approach to in-situ navigation through the use of beacons, similar to that used on Earth as well as under technology development efforts. An overview of the current state of navigation aids included as well as discussion of the Lunar Node 1 payload being built at NASA/Marshall Space Flight Center. Expected navigation results of this beacon payload for planned operation from the lunar surface are provided. Applications of navigation beacons to multiple stages of the proposed human lunar landing architecture are given, with initial analysis showing performance gains from the use of this technology. This work provides a starting point for continued analysis and design, laying out the foundation of how navigation beacons can be incorporated into the architecture to enable continued analysis, design, and future expanded capability

Overview of the NASA Entry, Descent and Landing Systems Analysis Exploration Feed-Forward Study

Technology required to land large payloads (20 to 50 mt) on Mars remains elusive. In an effort to identify the most viable investment path, NASA and others have been studying various concepts. One such study, the Entry, Descent and Landing Systems Analysis (EDLSA) Study [1] identified three potential options: the rigid aeroshell, the inflatable aeroshell and supersonic retropropulsion (SRP). In an effort to drive out additional levels of design detail, a smaller demonstrator, or exploration feed-forward (EFF), robotic mission was devised that utilized two of the three (inflatable aeroshell and SRP) high potential technologies in a configuration to demonstrate landing a two to four metric ton payload on Mars. This paper presents and overview of the maximum landed mass, inflatable aeroshell controllability and sensor suite capability assessments of the selected technologies and recommends specific technology areas for additional work

2020 NASA Technology Taxonomy

This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

Robust deep learning LiDAR-based pose estimation for autonomous space landers

Accurate relative pose estimation of a spacecraft during space landing operation is critical to ensure a safe and successful landing. This paper presents a 3D Light Detection and Ranging (LiDAR) based AI relative navigation architecture solution for autonomous space landing. The proposed architecture is based on a hybrid Deep Recurrent Convolutional Neural Network (DRCNN) combining a Convolutional Neural Network (CNN) with an Recurrent Neural Network (RNN) based on a Long–Short Term Memory (LSTM) network. The acquired 3D LiDAR data is converted into a multi-projected images and feed the DRCNN with depth and other multi-projected imagery. The CNN module of the architecture allows an efficient representation of features, and the RNN module, as an LSTM, provides robust navigation motion estimates. A variety of landing scenarios are considered, simulated and experimented to evaluate the efficiency of the proposed architecture. A LiDAR based imagery data (Range, Slope, and Elevation) is initially created using PANGU (Planet and Asteroid Natural Scene Generation Utility) software and an evaluation of the proposed solution using this data is conducted. Tests using an instrumented Aerial Robot in Gazebo software to simulate landing scenarios on a synthetic but representative lunar terrain (3D digital elevation model) is proposed. Finally, real experiments using a real flying drone equipped with a Velodyne VLP16 3D LiDAR sensor to generate real 3D scene point clouds while landing on a designed down scaled lunar moon landing surface are conducted. All the test results achieved show that the suggested architecture is capable of delivering good 6 Degree of Freedom (DoF) pose precision with a good and reasonable computation

NAVIGATION, GUIDANCE AND CONTROL FOR PLANETARY LANDING

This dissertation aims to develop algorithms of guidance and control for propulsive terminal phase planetary landing, including a piloting strategy. The algorithms developed here are based on the Embedded Model Control (EMC) principles. Currently, the planetary entry descent and landing are important issues, landing on Mars and Moon has been scientifically rewarding; successful landed robotic systems on the surface of Mars have been achieved. Projects as Mars Science Laboratory MSL inter alia have achieved a successful landing. These new approaches are focused in delivering large amounts of mass with a low uncertainty and in performing the entry, descent and landing sequence for human exploration. The dissertation is divided in two parts, the first part is focused on Pinpoint landing algorithms, piloting definition and its integration with guidance; some simulations runs are provided. The second part of this research describes the Borea project. It shows the modelling of quadrotor dynamics and kinematics. Its propulsive system is studied and an alternative methodology for the propeller modelling is presented. The embedded model control for quadrotor vehicles is developed. Test of GNC algorithms for planetary landing were studied and simulated. The dissertation is divided in two parts, the first part is focused on Pinpoint landing algorithms, piloting definition and its integration with guidance, some simulations runs are provided. The second part of this research describes the Borea project. shows modelling of quadrotor dynamics and kinematics. Its propulsive system is studied and an alternative methodology for the propeller modelling is presented. The embedded model control for quadrotor vehicles is developed. Test of GNC algorithms for planetary landing were studied and simulated

Autonomous Trajectory Planning and Guidance Control for Launch Vehicles

This open access book highlights the autonomous and intelligent flight control of future launch vehicles for improving flight autonomy to plan ascent and descent trajectories onboard, and autonomously handle unexpected events or failures during the flight. Since the beginning of the twenty-first century, space launch activities worldwide have grown vigorously. Meanwhile, commercial launches also account for the booming trend. Unfortunately, the risk of space launches still exists and is gradually increasing in line with the rapidly rising launch activities and commercial rockets. In the history of space launches, propulsion and control systems are the two main contributors to launch failures. With the development of information technologies, the increase of the functional density of hardware products, the application of redundant or fault-tolerant solutions, and the improvement of the testability of avionics, the launch losses caused by control systems exhibit a downward trend, and the failures induced by propulsion systems become the focus of attention. Under these failures, the autonomous planning and guidance control may save the missions. This book focuses on the latest progress of relevant projects and academic studies of autonomous guidance, especially on some advanced methods which can be potentially real-time implemented in the future control system of launch vehicles. In Chapter 1, the prospect and technical challenges are summarized by reviewing the development of launch vehicles. Chapters 2 to 4 mainly focus on the flight in the ascent phase, in which the autonomous guidance is mainly reflected in the online planning. Chapters 5 and 6 mainly discuss the powered descent guidance technologies. Finally, since aerodynamic uncertainties exert a significant impact on the performance of the ascent / landing guidance control systems, the estimation of aerodynamic parameters, which are helpful to improve flight autonomy, is discussed in Chapter 7. The book serves as a valuable reference for researchers and engineers working on launch vehicles. It is also a timely source of information for graduate students interested in the subject

Applied Stochastic Optimal Control for Spacecraft Guidance

Optimal control theory has been successfully applied to a wide range of a problems in spacecraft trajectory optimization. Historically, the identification and management of uncertainty in spaceflight applications has been a separate endeavor from optimal trajectory design, with the exception of heuristic margins applied on the deterministic optimal trajectory. Following a stochastic optimal control approach, on the other hand, leads to the direct consideration of uncertainty for the design of closed-loop trajectories with probabilistic constraints. Resulting control laws are designed with respect to all possible trajectory and control input realizations, and the performance is evaluated over measures of the aggregate, or expected, state and control trajectories. This dissertation focuses on specific applications of stochastic optimal control for spacecraft guidance, namely: powered descent guidance (PDG), atmospheric entry guidance, and aerocapture guidance. In addition, extensions are developed, which have further applications for spacecraft guidance, to the general theory of applying convex optimization to jointly steer the mean and covariance of stochastic systems, subject to probabilistic constraints. For minimum-fuel PDG, the problem of setting non-conservative thrust margins is addressed by application of minimum-variance, covariance-constrained stochastic optimal control. The resulting closed-loop PDG process does not, with high probability, either saturate thrust commands or deviate too far from the desired landing site. Next, entry guidance in an atmosphere with spatially-dependent random variations in the atmospheric density is posed as a chance-constrained stochastic optimal control problem; the resulting targeting accuracy is shown to be better than the current state-of-the-art Apollo-derived entry guidance. Finally, in order to address the problem of aerocapture guidance around a planet with an unknown atmosphere, a successive convex programming-based method is developed to solve chance-constrained stochastic optimal control problems for systems acting in the presence of a Gaussian random field. In a numerical example of an aerocapture mission with bank angle control, the developed method is used to solve for a control law that explicitly minimizes the 99th percentile of the required Delta-V, subject to constraints on the probability distribution of the closed-loop bank angle during atmospheric flight.Ph.D