Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age

Simultaneous Localization and Mapping (SLAM)consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it. The SLAM community has made astonishing progress over the last 30 years, enabling large-scale real-world applications, and witnessing a steady transition of this technology to industry. We survey the current state of SLAM. We start by presenting what is now the de-facto standard formulation for SLAM. We then review related work, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers. This paper simultaneously serves as a position paper and tutorial to those who are users of SLAM. By looking at the published research with a critical eye, we delineate open challenges and new research issues, that still deserve careful scientific investigation. The paper also contains the authors' take on two questions that often animate discussions during robotics conferences: Do robots need SLAM? and Is SLAM solved

PHROG: A Multimodal Feature for Place Recognition

International audienceLong-term place recognition in outdoor environments remains a challenge due to high appearance changes in the environment. The problem becomes even more difficult when the matching between two scenes has to be made with information coming from different visual sources, particularly with different spectral ranges. For instance, an infrared camera is helpful for night vision in combination with a visible camera. In this paper, we emphasize our work on testing usual feature point extractors under both constraints: repeatability across spectral ranges and long-term appearance. We develop a new feature extraction method dedicated to improve the repeatability across spectral ranges. We conduct an evaluation of feature robustness on long-term datasets coming from different imaging sources (optics, sensors size and spectral ranges) with a Bag-of-Words approach. The tests we perform demonstrate that our method brings a significant improvement on the image retrieval issue in a visual place recognition context, particularly when there is a need to associate images from various spectral ranges such as infrared and visible: we have evaluated our approach using visible, Near InfraRed (NIR), Short Wavelength InfraRed (SWIR) and Long Wavelength InfraRed (LWIR)

Two Measures for Enhancing Data Association Performance in SLAM

Data association is one of the key problems in the SLAM community. Several data association failures may cause the SLAM results to be divergent. Data association performance in SLAM is affected by both data association methods and sensor information. Two measures of handling sensor information are introduced herein to enhance data association performance in SLAM. For the first measure, truncating strategy of limited features, instead of all matched features, is used for observation update. These features are selected according to an information variable. This truncating strategy is used to lower the effect of false matched features. For the other measure, a special rejecting mechanism is designed to reject suspected observations. When the predicted robot pose is obviously different from the updated robot pose, all observed sensor information at this moment is discarded. The rejecting mechanism aims at eliminating accidental sensor information. Experimental results indicate that the introduced measures perform well in improving the stability of data association in SLAM. These measures are of extraordinary value for real SLAM applications

Implementación de un algoritmo de mapeo 2D mediante sensor Rplidar

En el siguiente trabajo se hará la primera parte de un algoritmo de mapeo 2D por medio de la adquisición de profundidades de un sensor laser de la marca RoboPeak, el RPLidar para el movimiento de una plataforma móvil que funcionará como transportador del sensor. Este algoritmo se desarrollará por medio de la técnica de SLAM (Simultaneous Localization and Mapping). El fin de este algoritmo es el crear mapas de lugares sin explorar mediante la liberación de una plataforma móvil que se irá desplazando a medida que va tomando escaneos del área, para que, al finalizar su trayectoria, haya obtenido datos suficientes para crear un mapa del lugar. Este trabajo se enfocará en la conexión entre los diferentes elementos de hardware (tarjeta de adquisición de datos Odroid, plataforma móvil de la empresa IRobot, el IRobot Create 2 y el sensor laser de la empresa RoboPeak, el RPLidar) y el envío de datos entre estos, además de la obtención de los datos de entrada y salida para el algoritmo de mapeo, por medio de la obtención de los datos arrojados por el sensor laser RPLidar (calidad, ángulo y distancia), los datos arrojados por los encoder de la plataforma móvil y el movimiento de la plataforma. Se logró capturar los datos que se deseaban los cuales servirán para un trabajo futuro enfocado en el desarrollo del algoritmo de mapeo 2D.Ingeniero Mecatrónicopregrad

Advances in Robot Navigation

Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments. Different solutions providing adaptive navigation are taken from nature inspiration, and diverse applications are described in the context of an important field of study: social robotics