A Comprehensive Review on Autonomous Navigation

The field of autonomous mobile robots has undergone dramatic advancements over the past decades. Despite achieving important milestones, several challenges are yet to be addressed. Aggregating the achievements of the robotic community as survey papers is vital to keep the track of current state-of-the-art and the challenges that must be tackled in the future. This paper tries to provide a comprehensive review of autonomous mobile robots covering topics such as sensor types, mobile robot platforms, simulation tools, path planning and following, sensor fusion methods, obstacle avoidance, and SLAM. The urge to present a survey paper is twofold. First, autonomous navigation field evolves fast so writing survey papers regularly is crucial to keep the research community well-aware of the current status of this field. Second, deep learning methods have revolutionized many fields including autonomous navigation. Therefore, it is necessary to give an appropriate treatment of the role of deep learning in autonomous navigation as well which is covered in this paper. Future works and research gaps will also be discussed

Towards topological mapping with vision-based simultaneous localization and map building

Although the theory of Simultaneous Localization and Map Building (SLAM) is well developed, there are many challenges to overcome when incorporating vision sensors into SLAM systems. Visual sensors have different properties when compared to range finding sensors and therefore require different considerations. Existing vision-based SLAM algorithms extract point landmarks, which are required for SLAM algorithms such as the Kalman filter. Under this restriction, the types of image features that can be used are limited and the full advantages of vision not realized. This thesis examines the theoretical formulation of the SLAM problem and the characteristics of visual information in the SLAM domain. It also examines different representations of uncertainty, features and environments. It identifies the necessity to develop a suitable framework for vision-based SLAM systems and proposes a framework called VisionSLAM, which utilizes an appearance-based landmark representation and topological map structure to model metric relations between landmarks. A set of Haar feature filters are used to extract image structure statistics, which are robust against illumination changes, have good uniqueness property and can be computed in real time. The algorithm is able to resolve and correct false data associations and is robust against random correlation resulting from perceptual aliasing. The algorithm has been tested extensively in a natural outdoor environment

Análisis de la tecnología de posicionamiento indoor aplicada a robots autónomos móviles

La creación del presente proyecto surge de la necesidad del Departamento de Sistemas y Automática de la Universidad Carlos III de disponer de un documento que recoja las diferentes tecnologías dedicadas al posicionamiento de robot autónomos móviles en interiores. El propósito del documento es exponer de forma accesible pero rigurosa los aspectos clave de los sistemas de posicionamiento en interiores, sus usos actuales en múltiples entornos y las posibles evoluciones futuras de las diferentes tecnologías. Los principales contenidos cubiertos son: - Principales tecnologías de posicionamiento: características, ventajas e inconvenientes. - Estrategias y algoritmos usados en los sistemas de posicionamiento. - Estado de los sistemas de posicionamiento en interiores en la actualidad, tanto comerciales como en fase de desarrollo. De forma complementaria, se estudian conceptos relativos a la locomoción robótica, ya que pueden ser determinantes a la hora de analizar las estrategias de los robots autónomos móviles, y se presentan las principales tecnologías de sensores organizadas según su campo de aplicación. Finalmente, se analizan los resultados y se elaboran conclusiones en función de los requerimientos iniciales del proyecto, valorando su adecuidad para las aplicaciones propuestas.The making of this project emerges from the need of the Department of Systems and Automation at the University Carlos III to gather information in a survey about the different technologies related to the indoor positioning of self-sufficient mobile robots. The purpose of the project is to present the key aspects of the selected indoor positioning systems, their current usage in multiple surroundings and the possible future development of these different technologies in an accessible, yet rigorous way. The main content covered by the survey is: - Relevant positioning technologies: characteristics, benefits and disadvantages. - Strategies and algorithms applied by the positioning systems. - Present status of existing indoor positioning systems, considering both systems that are currently commercialized and systems in stage of development. To enrich the survey, it has been complemented by a study of concepts related to robotic locomotion, seeing that they can be decisive at the moment of analyzing the strategy of the autonomous mobile robots. Relevant sensor technologies are also presented, organized by the application area. Finally, the results are analyzed and the conclusions are made according to the requirements established in the initial phases of the project, considering the adequacy for the suggested applications.Ingeniería Técnica en Electrónic

Recent Advances in Multi Robot Systems

To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems

Mobile robot vavigation using a vision based approach

PhD ThesisThis study addresses the issue of vision based mobile robot navigation in a partially cluttered indoor environment using a mapless navigation strategy. The work focuses on two key problems, namely vision based obstacle avoidance and vision based reactive navigation strategy. The estimation of optical flow plays a key role in vision based obstacle avoidance problems, however the current view is that this technique is too sensitive to noise and distortion under real conditions. Accordingly, practical applications in real time robotics remain scarce. This dissertation presents a novel methodology for vision based obstacle avoidance, using a hybrid architecture. This integrates an appearance-based obstacle detection method into an optical flow architecture based upon a behavioural control strategy that includes a new arbitration module. This enhances the overall performance of conventional optical flow based navigation systems, enabling a robot to successfully move around without experiencing collisions. Behaviour based approaches have become the dominant methodologies for designing control strategies for robot navigation. Two different behaviour based navigation architectures have been proposed for the second problem, using monocular vision as the primary sensor and equipped with a 2-D range finder. Both utilize an accelerated version of the Scale Invariant Feature Transform (SIFT) algorithm. The first architecture employs a qualitative-based control algorithm to steer the robot towards a goal whilst avoiding obstacles, whereas the second employs an intelligent control framework. This allows the components of soft computing to be integrated into the proposed SIFT-based navigation architecture, conserving the same set of behaviours and system structure of the previously defined architecture. The intelligent framework incorporates a novel distance estimation technique using the scale parameters obtained from the SIFT algorithm. The technique employs scale parameters and a corresponding zooming factor as inputs to train a neural network which results in the determination of physical distance. Furthermore a fuzzy controller is designed and integrated into this framework so as to estimate linear velocity, and a neural network based solution is adopted to estimate the steering direction of the robot. As a result, this intelligent iv approach allows the robot to successfully complete its task in a smooth and robust manner without experiencing collision. MS Robotics Studio software was used to simulate the systems, and a modified Pioneer 3-DX mobile robot was used for real-time implementation. Several realistic scenarios were developed and comprehensive experiments conducted to evaluate the performance of the proposed navigation systems. KEY WORDS: Mobile robot navigation using vision, Mapless navigation, Mobile robot architecture, Distance estimation, Vision for obstacle avoidance, Scale Invariant Feature Transforms, Intelligent framework

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described