Adaptive and intelligent navigation of autonomous planetary rovers - A survey

The application of robotics and autonomous systems in space has increased dramatically. The ongoing Mars rover mission involving the Curiosity rover, along with the success of its predecessors, is a key milestone that showcases the existing capabilities of robotic technology. Nevertheless, there has still been a heavy reliance on human tele-operators to drive these systems. Reducing the reliance on human experts for navigational tasks on Mars remains a major challenge due to the harsh and complex nature of the Martian terrains. The development of a truly autonomous rover system with the capability to be effectively navigated in such environments requires intelligent and adaptive methods fitting for a system with limited resources. This paper surveys a representative selection of work applicable to autonomous planetary rover navigation, discussing some ongoing challenges and promising future research directions from the perspectives of the authors

System of Terrain Analysis, Energy Estimation and Path Planning for Planetary Exploration by Robot Teams

NASA’s long term plans involve a return to manned moon missions, and eventually sending humans to mars. The focus of this project is the use of autonomous mobile robotics to enhance these endeavors. This research details the creation of a system of terrain classification, energy of traversal estimation and low cost path planning for teams of inexpensive and potentially expendable robots. The first stage of this project was the creation of a model which estimates the energy requirements of the traversal of varying terrain types for a six wheel rocker-bogie rover. The wheel/soil interaction model uses Shibly’s modified Bekker equations and incorporates a new simplified rocker-bogie model for estimating wheel loads. In all but a single trial the relative energy requirements for each soil type were correctly predicted by the model. A path planner for complete coverage intended to minimize energy consumption was designed and tested. It accepts as input terrain maps detailing the energy consumption required to move to each adjacent location. Exploration is performed via a cost function which determines the robot’s next move. This system was successfully tested for multiple robots by means of a shared exploration map. At peak efficiency, the energy consumed by our path planner was only 56% that used by the best case back and forth coverage pattern. After performing a sensitivity analysis of Shibly’s equations to determine which soil parameters most affected energy consumption, a neural network terrain classifier was designed and tested. The terrain classifier defines all traversable terrain as one of three soil types and then assigns an assumed set of soil parameters. The classifier performed well over all, but had some difficulty distinguishing large rocks from sand. This work presents a system which successfully classifies terrain imagery into one of three soil types, assesses the energy requirements of terrain traversal for these soil types and plans efficient paths of complete coverage for the imaged area. While there are further efforts that can be made in all areas, the work achieves its stated goals

Percepción basada en visión estereoscópica, planificación de trayectorias y estrategias de navegación para exploración robótica autónoma

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Ingeniería del Software e Inteligencia artificial, leída el 13-05-2015En esta tesis se trata el desarrollo de una estrategia de navegación autónoma basada en visión artificial para exploración robótica autónoma de superficies planetarias. Se han desarrollado una serie de subsistemas, módulos y software específicos para la investigación desarrollada en este trabajo, ya que la mayoría de las herramientas existentes para este dominio son propiedad de agencias espaciales nacionales, no accesibles a la comunidad científica. Se ha diseñado una arquitectura software modular multi-capa con varios niveles jerárquicos para albergar el conjunto de algoritmos que implementan la estrategia de navegación autónoma y garantizar la portabilidad del software, su reutilización e independencia del hardware. Se incluye también el diseño de un entorno de trabajo destinado a dar soporte al desarrollo de las estrategias de navegación. Éste se basa parcialmente en herramientas de código abierto al alcance de cualquier investigador o institución, con las necesarias adaptaciones y extensiones, e incluye capacidades de simulación 3D, modelos de vehículos robóticos, sensores, y entornos operacionales, emulando superficies planetarias como Marte, para el análisis y validación a nivel funcional de las estrategias de navegación desarrolladas. Este entorno también ofrece capacidades de depuración y monitorización.La presente tesis se compone de dos partes principales. En la primera se aborda el diseño y desarrollo de las capacidades de autonomía de alto nivel de un rover, centrándose en la navegación autónoma, con el soporte de las capacidades de simulación y monitorización del entorno de trabajo previo. Se han llevado a cabo un conjunto de experimentos de campo, con un robot y hardware real, detallándose resultados, tiempo de procesamiento de algoritmos, así como el comportamiento y rendimiento del sistema en general. Como resultado, se ha identificado al sistema de percepción como un componente crucial dentro de la estrategia de navegación y, por tanto, el foco principal de potenciales optimizaciones y mejoras del sistema. Como consecuencia, en la segunda parte de este trabajo, se afronta el problema de la correspondencia en imágenes estéreo y reconstrucción 3D de entornos naturales no estructurados. Se han analizado una serie de algoritmos de correspondencia, procesos de imagen y filtros. Generalmente se asume que las intensidades de puntos correspondientes en imágenes del mismo par estéreo es la misma. Sin embargo, se ha comprobado que esta suposición es a menudo falsa, a pesar de que ambas se adquieren con un sistema de visión compuesto de dos cámaras idénticas. En consecuencia, se propone un sistema experto para la corrección automática de intensidades en pares de imágenes estéreo y reconstrucción 3D del entorno basado en procesos de imagen no aplicados hasta ahora en el campo de la visión estéreo. Éstos son el filtrado homomórfico y la correspondencia de histogramas, que han sido diseñados para corregir intensidades coordinadamente, ajustando una imagen en función de la otra. Los resultados se han podido optimizar adicionalmente gracias al diseño de un proceso de agrupación basado en el principio de continuidad espacial para eliminar falsos positivos y correspondencias erróneas. Se han estudiado los efectos de la aplicación de dichos filtros, en etapas previas y posteriores al proceso de correspondencia, con eficiencia verificada favorablemente. Su aplicación ha permitido la obtención de un mayor número de correspondencias válidas en comparación con los resultados obtenidos sin la aplicación de los mismos, consiguiendo mejoras significativas en los mapas de disparidad y, por lo tanto, en los procesos globales de percepción y reconstrucción 3D.Depto. de Ingeniería de Software e Inteligencia Artificial (ISIA)Fac. de InformáticaTRUEunpu

Fast Approximate Clearance Evaluation for Rovers with Articulated Suspension Systems

We present a light-weight body-terrain clearance evaluation algorithm for the automated path planning of NASA's Mars 2020 rover. Extraterrestrial path planning is challenging due to the combination of terrain roughness and severe limitation in computational resources. Path planning on cluttered and/or uneven terrains requires repeated safety checks on all the candidate paths at a small interval. Predicting the future rover state requires simulating the vehicle settling on the terrain, which involves an inverse-kinematics problem with iterative nonlinear optimization under geometric constraints. However, such expensive computation is intractable for slow spacecraft computers, such as RAD750, which is used by the Curiosity Mars rover and upcoming Mars 2020 rover. We propose the Approximate Clearance Evaluation (ACE) algorithm, which obtains conservative bounds on vehicle clearance, attitude, and suspension angles without iterative computation. It obtains those bounds by estimating the lowest and highest heights that each wheel may reach given the underlying terrain, and calculating the worst-case vehicle configuration associated with those extreme wheel heights. The bounds are guaranteed to be conservative, hence ensuring vehicle safety during autonomous navigation. ACE is planned to be used as part of the new onboard path planner of the Mars 2020 rover. This paper describes the algorithm in detail and validates our claim of conservatism and fast computation through experiments

Comparative Study of Different Methods in Vibration-Based Terrain Classification for Wheeled Robots with Shock Absorbers

open access articleAutonomous robots that operate in the field can enhance their security and efficiency by accurate terrain classification, which can be realized by means of robot-terrain interaction-generated vibration signals. In this paper, we explore the vibration-based terrain classification (VTC), in particular for a wheeled robot with shock absorbers. Because the vibration sensors are usually mounted on the main body of the robot, the vibration signals are dampened significantly, which results in the vibration signals collected on different terrains being more difficult to discriminate. Hence, the existing VTC methods applied to a robot with shock absorbers may degrade. The contributions are two-fold: (1) Several experiments are conducted to exhibit the performance of the existing feature-engineering and feature-learning classification methods; and (2) According to the long short-term memory (LSTM) network, we propose a one-dimensional convolutional LSTM (1DCL)-based VTC method to learn both spatial and temporal characteristics of the dampened vibration signals. The experiment results demonstrate that: (1) The feature-engineering methods, which are efficient in VTC of the robot without shock absorbers, are not so accurate in our project; meanwhile, the feature-learning methods are better choices; and (2) The 1DCL-based VTC method outperforms the conventional methods with an accuracy of 80.18%, which exceeds the second method (LSTM) by 8.23%

SSTAC/ARTS review of the draft Integrated Technology Plan (ITP). Volume 8: Aerothermodynamics Automation and Robotics (A/R) systems sensors, high-temperature superconductivity

Viewgraphs of briefings presented at the SSTAC/ARTS review of the draft Integrated Technology Plan (ITP) on aerothermodynamics, automation and robotics systems, sensors, and high-temperature superconductivity are included. Topics covered include: aerothermodynamics; aerobraking; aeroassist flight experiment; entry technology for probes and penetrators; automation and robotics; artificial intelligence; NASA telerobotics program; planetary rover program; science sensor technology; direct detector; submillimeter sensors; laser sensors; passive microwave sensing; active microwave sensing; sensor electronics; sensor optics; coolers and cryogenics; and high temperature superconductivity

Access Mars: Assessing Cave Capabilities Establishing Specific Solutions: Final Report

The human race has evolved, grown and expanded through the exploration of Earth. After initial steps on the Moon, our next challenge is to explore the solar system. Mars shows potential for both scientific discovery and future human settlement, and so is a prime candidate for the next leap of human exploration. Such a bold endeavor will be a driver for an unprecedented worldwide cooperative effort and the catalyst for a new era of international, intercultural and interdisciplinary human relations. Scientific and technological progress will also accelerate as mankind is ushered into a new era of space exploration. Currently proposed Mars missions have identified a number of challenges such as high levels of radiation, harsh climate and limited launch windows. Recently discovered lava tubes on Mars present potential solutions to some of these issues, but raise a variety of intriguing new challenges. These encompass not only technological and engineering considerations, but also legal, ethical and societal issues such as planetary protection and crew safety. This report assesses the feasibility of overcoming such challenges through the exploitation of Mars caves. This report reviews existing reference missions and identifies areas of further research essential for adapting mission architectures to utilize caves. Cave suitability is considered with respect to size, type, location and their potential to mitigate hazards. They are also assessed with respect to their potential for scientific work adhering to astrobiology guidelines and the search for extra-terrestrial life. This report compares surface and subsurface habitat options. Engineering challenges arising from the use of caves are addressed along with proposals for alternate architecture solutions. Mission analysis is conducted to determine the transit trajectory and define two possible mission scenarios with surface crews of 6 and 12 crew members. Different types of habitat are described and evaluated. An architecture for precursor missions is provided utilizing surface rovers, cargo delivery rovers and pressurized human transport vehicles. The implications of sub-surface operations on thermal control, communications and power systems are investigated with recommendations given. Crew selection, training methods and life support system solutions are also addressed. Literature suggests a low radiation environment within Martian caves, allowing for extended duration missions. The ACCESS Mars Team concludes that using lava tubes as human habitats is not merely a viable habitat solution for a Mars expedition, but also potentially more beneficial than proposed surface solutions

Navigation Requirements Development and Performance Assessment of a Martian Ascent Vehicle

To support development of Martian Ascent Vehicles, analysis tools are needed to support the development of Guidance, Navigation, and Control requirements. This paper presents a focused approach to Navigation analysis to capture development of requirements on initial state knowledge and inertial sensor capabilities. A simulation and analysis framework was used to assess the capability of a range of sensors to operate inertially along a range of launch trajectories. The baseline Martian Ascent Vehicle was used as the input for optimizing a set of trajectories from each launch site. These trajectories were used to perform Monte Carlo analysis dispersing error sensor terms and their effects on integrated vehicle performance. Additionally, this paper provides insight into the use of optical navigation techniques to assess state determination and the potential to use observations of local extraplanetary bodies to estimate state. This paper provides an initial level of performance assessment of navigation components to support continued requirements development of a Martian Ascent Vehicle with applications to both crew and sample return missions