Rough-terrain mobile robot planning and control with application to planetary exploration

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001.Includes bibliographical references (leaves 119-130).Future planetary exploration missions will require mobile robots to perform difficult tasks in highly challenging terrain, with limited human supervision. Current motion planning and control algorithms are not well suited to rough-terrain mobility, since they generally do not consider the physical characteristics of the rover and its environment. Failure to understand these characteristics could lead to rover entrapment and mission failure. In this thesis, methods are presented for improved rough-terrain mobile robot mobility, which exploit fundamental physical models of the rover and terrain. Wheel-terrain interaction has been shown to be critical to rough terrain mobility. A wheel-terrain interaction model is presented, and a method for on-line estimation of important model parameters is proposed. The local terrain profile also strongly influences robot mobility. A method for on-line estimation of wheel-terrain contact angles is presented. Simulation and experimental results show that wheel-terrain model parameters and contact angles can be estimated on-line with good accuracy. Two rough-terrain planning algorithms are introduced. First, a motion planning algorithm is presented that is computationally efficient and considers uncertainty in rover sensing and localization. Next, an algorithm for geometrically reconfiguring the rover kinematic structure to optimize tipover stability margin is presented. Both methods utilize models developed earlier in the thesis.(cont.) Simulation and experimental results on the Jet Propulsion Laboratory Sample Return Rover show that the algorithms allow highly stable, semi-autonomous mobility in rough terrain. Finally, a rough-terrain control algorithm is presented that exploits the actuator redundancy found in multi-wheeled mobile robots to improve ground traction and reduce power consumption. The algorithm uses models developed earlier in the thesis. Simulation and experimental results show that the algorithm leads to improved wheel thrust and thus increased mobility in rough terrain.by Karl David Iagnemma.Ph.D

Planetary Rover Inertial Navigation Applications: Pseudo Measurements and Wheel Terrain Interactions

Accurate localization is a critical component of any robotic system. During planetary missions, these systems are often limited by energy sources and slow spacecraft computers. Using proprioceptive localization (e.g., using an inertial measurement unit and wheel encoders) without external aiding is insufficient for accurate localization. This is mainly due to the integrated and unbounded errors of the inertial navigation solutions and the drifted position information from wheel encoders caused by wheel slippage. For this reason, planetary rovers often utilize exteroceptive (e.g., vision-based) sensors. On the one hand, localization with proprioceptive sensors is straightforward, computationally efficient, and continuous. On the other hand, using exteroceptive sensors for localization slows rover driving speed, reduces rover traversal rate, and these sensors are sensitive to the terrain features. Given the advantages and disadvantages of both methods, this thesis focuses on two objectives. First, improving the proprioceptive localization performance without significant changes to the rover operations. Second, enabling adaptive traversability rate based on the wheel-terrain interactions while keeping the localization reliable. To achieve the first objective, we utilized the zero-velocity, zero-angular rate updates, and non-holonomicity of a rover to improve rover localization performance even with the limited available sensor usage in a computationally efficient way. Pseudo-measurements generated from proprioceptive sensors when the rover is stationary conditions and the non-holonomic constraints while traversing can be utilized to improve the localization performance without any significant changes to the rover operations. Through this work, it is observed that a substantial improvement in localization performance, without the aid of additional exteroceptive sensor information. To achieve the second objective, the relationship between the estimation of localization uncertainty and wheel-terrain interactions through slip-ratio was investigated. This relationship was exposed with a Gaussian process with time series implementation by using the slippage estimation while the rover is moving. Then, it is predicted when to change from moving to stationary conditions by mapping the predicted slippage into localization uncertainty prediction. Instead of a periodic stopping framework, the method introduced in this work is a slip-aware localization method that enables the rover to stop more frequently in high-slip terrains whereas stops rover less frequently for low-slip terrains while keeping the proprioceptive localization reliable

System Design, Motion Modelling and Planning for a Recon figurable Wheeled Mobile Robot

Over the past ve decades the use of mobile robotic rovers to perform in-situ scienti c investigations on the surfaces of the Moon and Mars has been tremendously in uential in shaping our understanding of these extraterrestrial environments. As robotic missions have evolved there has been a greater desire to explore more unstructured terrain. This has exposed mobility limitations with conventional rover designs such as getting stuck in soft soil or simply not being able to access rugged terrain. Increased mobility and terrain traversability are key requirements when considering designs for next generation planetary rovers. Coupled with these requirements is the need to autonomously navigate unstructured terrain by taking full advantage of increased mobility. To address these issues, a high degree-of-freedom recon gurable platform that is capable of energy intensive legged locomotion in obstacle-rich terrain as well as wheeled locomotion in benign terrain is proposed. The complexities of the planning task that considers the high degree-of-freedom state space of this platform are considerable. A variant of asymptotically optimal sampling-based planners that exploits the presence of dominant sub-spaces within a recon gurable mobile robot's kinematic structure is proposed to increase path quality and ensure platform safety. The contributions of this thesis include: the design and implementation of a highly mobile planetary analogue rover; motion modelling of the platform to enable novel locomotion modes, along with experimental validation of each of these capabilities; the sampling-based HBFMT* planner that hierarchically considers sub-spaces to better guide search of the complete state space; and experimental validation of the planner with the physical platform that demonstrates how the planner exploits the robot's capabilities to uidly transition between various physical geometric con gurations and wheeled/legged locomotion modes

Enabling All-Access Mobility for Planetary Exploration Vehicles via Transformative Reconfiguration

Effective large-scale exploration of planetary surfaces requires robotic vehicles capable of mobility across chaotic terrain. Characterized by a combination of ridges, cracks and valleys, the demands of this environment can cause spacecraft to experience significant reductions in operating footprint, performance, or even result in total system loss. Significantly increasing the scientific return of an interplanetary mission is facilitated by architectures capable of real-time configuration changes that go beyond that of active suspensions while concurrently meeting system, mass, power, and cost constraints. This Phase 1 report systematically explores how in-service architecture changes can expand system capabilities and mission opportunities. A foundation for concept generation is supplied by four Martian mission profiles spanning chasms, ice fields, craters and rocky terrain. A fifth mission profile centered on Near Earth Object exploration is also introduced. Concept generation is directed using four transformation principles - a taxonomy developed by the engineering design community to explain the cause of an architecture change and existing brainstorming techniques. This allowed early conceptual sketches of architecture changes to be organized by the principle driving the greatest increase in mission performance capability

Design Issues for Hexapod Walking Robots

Hexapod walking robots have attracted considerable attention for several decades. Many studies have been carried out in research centers, universities and industries. However, only in the recent past have efficient walking machines been conceived, designed and built with performances that can be suitable for practical applications. This paper gives an overview of the state of the art on hexapod walking robots by referring both to the early design solutions and the most recent achievements. Careful attention is given to the main design issues and constraints that influence the technical feasibility and operation performance. A design procedure is outlined in order to systematically design a hexapod walking robot. In particular, the proposed design procedure takes into account the main features, such as mechanical structure and leg configuration, actuating and driving systems, payload, motion conditions, and walking gait. A case study is described in order to show the effectiveness and feasibility of the proposed design procedure

Adaptive Localization and Mapping for Planetary Rovers

Future rovers will be equipped with substantial onboard autonomy as space agencies and industry proceed with missions studies and technology development in preparation for the next planetary exploration missions. Simultaneous Localization and Mapping (SLAM) is a fundamental part of autonomous capabilities and has close connections to robot perception, planning and control. SLAM positively affects rover operations and mission success. The SLAM community has made great progress in the last decade by enabling real world solutions in terrestrial applications and is nowadays addressing important challenges in robust performance, scalability, high-level understanding, resources awareness and domain adaptation. In this thesis, an adaptive SLAM system is proposed in order to improve rover navigation performance and demand. This research presents a novel localization and mapping solution following a bottom-up approach. It starts with an Attitude and Heading Reference System (AHRS), continues with a 3D odometry dead reckoning solution and builds up to a full graph optimization scheme which uses visual odometry and takes into account rover traction performance, bringing scalability to modern SLAM solutions. A design procedure is presented in order to incorporate inertial sensors into the AHRS. The procedure follows three steps: error characterization, model derivation and filter design. A complete kinematics model of the rover locomotion subsystem is developed in order to improve the wheel odometry solution. Consequently, the parametric model predicts delta poses by solving a system of equations with weighed least squares. In addition, an odometry error model is learned using Gaussian processes (GPs) in order to predict non-systematic errors induced by poor traction of the rover with the terrain. The odometry error model complements the parametric solution by adding an estimation of the error. The gained information serves to adapt the localization and mapping solution to the current navigation demands (domain adaptation). The adaptivity strategy is designed to adjust the visual odometry computational load (active perception) and to influence the optimization back-end by including highly informative keyframes in the graph (adaptive information gain). Following this strategy, the solution is adapted to the navigation demands, providing an adaptive SLAM system driven by the navigation performance and conditions of the interaction with the terrain. The proposed methodology is experimentally verified on a representative planetary rover under realistic field test scenarios. This thesis introduces a modern SLAM system which adapts the estimated pose and map to the predicted error. The system maintains accuracy with fewer nodes, taking the best of both wheel and visual methods in a consistent graph-based smoothing approach

Planetary rovers and data fusion

This research will investigate the problem of position estimation for planetary rovers. Diverse algorithmic filters are available for collecting input data and transforming that data to useful information for the purpose of position estimation process. The terrain has sandy soil which might cause slipping of the robot, and small stones and pebbles which can affect trajectory. The Kalman Filter, a state estimation algorithm was used for fusing the sensor data to improve the position measurement of the rover. For the rover application the locomotion and errors accumulated by the rover is compensated by the Kalman Filter. The movement of a rover in a rough terrain is challenging especially with limited sensors to tackle the problem. Thus, an initiative was taken to test drive the rover during the field trial and expose the mobile platform to hard ground and soft ground(sand). It was found that the LSV system produced speckle image and values which proved invaluable for further research and for the implementation of data fusion. During the field trial,It was also discovered that in a at hard surface the problem of the steering rover is minimal. However, when the rover was under the influence of soft sand the rover tended to drift away and struggled to navigate. This research introduced the laser speckle velocimetry as an alternative for odometric measurement. LSV data was gathered during the field trial to further simulate under MATLAB, which is a computational/mathematical programming software used for the simulation of the rover trajectory. The wheel encoders came with associated errors during the position measurement process. This was observed during the earlier field trials too. It was also discovered that the Laser Speckle Velocimetry measurement was able to measure accurately the position measurement but at the same time sensitivity of the optics produced noise which needed to be addressed as error problem. Though the rough terrain is found in Mars, this paper is applicable to a terrestrial robot on Earth. There are regions in Earth which have rough terrains and regions which are hard to measure with encoders. This is especially true concerning icy places like Antarctica, Greenland and others. The proposed implementation for the development of the locomotion system is to model a system for the position estimation through the use of simulation and collecting data using the LSV. Two simulations are performed, one is the differential drive of a two wheel robot and the second involves the fusion of the differential drive robot data and the LSV data collected from the rover testbed. The results have been positive. The expected contributions from the research work includes a design of a LSV system to aid the locomotion measurement system. Simulation results show the effect of different sensors and velocity of the robot. The kalman filter improves the position estimation process

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