Conceptual spatial representations for indoor mobile robots

We present an approach for creating conceptual representations of human-made indoor environments using mobile robots. The concepts refer to spatial and functional properties of typical indoor environments. Following findings in cognitive psychology, our model is composed of layers representing maps at different levels of abstraction. The complete system is integrated in a mobile robot endowed with laser and vision sensors for place and object recognition. The system also incorporates a linguistic framework that actively supports the map acquisition process, and which is used for situated dialogue. Finally, we discuss the capabilities of the integrated system

Sensor fusion for flexible human-portable building-scale mapping

This paper describes a system enabling rapid multi-floor indoor map building using a body-worn sensor system fusing information from RGB-D cameras, LIDAR, inertial, and barometric sensors. Our work is motivated by rapid response missions by emergency personnel, in which the capability for one or more people to rapidly map a complex indoor environment is essential for public safety. Human-portable mapping raises a number of challenges not encountered in typical robotic mapping applications including complex 6-DOF motion and the traversal of challenging trajectories including stairs or elevators. Our system achieves robust performance in these situations by exploiting state-of-the-art techniques for robust pose graph optimization and loop closure detection. It achieves real-time performance in indoor environments of moderate scale. Experimental results are demonstrated for human-portable mapping of several floors of a university building, demonstrating the system's ability to handle motion up and down stairs and to organize initially disconnected sets of submaps in a complex environment.Lincoln LaboratoryUnited States. Air Force (Contract FA8721-05-C-0002)United States. Office of Naval Research (Grant N00014-10-1-0936)United States. Office of Naval Research (Grant N00014-11-1-0688)United States. Office of Naval Research (Grant N00014-12-10020

Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools

Two Dimensional Positioning and Heading Solution for Flying Vehicles Using a Line-Scanning Laser Radar (LADAR)

Emerging technology in small autonomous flying vehicles requires the systems to have a precise navigation solution in order to perform tasks. In many critical environments, such as indoors, GPS is unavailable necessitating the development of supplemental aiding sensors to determine precise position. This research investigates the use of a line scanning laser radar (LADAR) as a standalone two dimensional position and heading navigation solution and sets up the device for augmentation into existing navigation systems. A fast histogram correlation method is developed to operate in real-time on board the vehicle providing position and heading updates at a rate of 10 Hz. LADAR navigation methods are adapted to 3 dimensions with a simulation built to analyze performance loss due attitude changes during flight. These simulations are then compared to experimental results collected using SICK LD-OEM 1000 mounted a cart traversing. The histogram correlation algorithm applied in this work was shown to successfully navigate a realistic environment where a quadrotor in short flights of less than 5 min in larger rooms. Application in hallways show great promise providing a stable heading along with tracking movement perpendicular to the hallway

Marine Vessel Inspection as a Novel Field for Service Robotics: A Contribution to Systems, Control Methods and Semantic Perception Algorithms.

This cumulative thesis introduces a novel field for service robotics: the inspection of marine vessels using mobile inspection robots. In this thesis, three scientific contributions are provided and experimentally verified in the field of marine inspection, but are not limited to this type of application. The inspection scenario is merely a golden thread to combine the cumulative scientific results presented in this thesis. The first contribution is an adaptive, proprioceptive control approach for hybrid leg-wheel robots, such as the robot ASGUARD described in this thesis. The robot is able to deal with rough terrain and stairs, due to the control concept introduced in this thesis. The proposed system is a suitable platform to move inside the cargo holds of bulk carriers and to deliver visual data from inside the hold. Additionally, the proposed system also has stair climbing abilities, allowing the system to move between different decks. The robot adapts its gait pattern dynamically based on proprioceptive data received from the joint motors and based on the pitch and tilt angle of the robot's body during locomotion. The second major contribution of the thesis is an independent ship inspection system, consisting of a magnetic wall climbing robot for bulkhead inspection, a particle filter based localization method, and a spatial content management system (SCMS) for spatial inspection data representation and organization. The system described in this work was evaluated in several laboratory experiments and field trials on two different marine vessels in close collaboration with ship surveyors. The third scientific contribution of the thesis is a novel approach to structural classification using semantic perception approaches. By these methods, a structured environment can be semantically annotated, based on the spatial relationships between spatial entities and spatial features. This method was verified in the domain of indoor perception (logistics and household environment), for soil sample classification, and for the classification of the structural parts of a marine vessel. The proposed method allows the description of the structural parts of a cargo hold in order to localize the inspection robot or any detected damage. The algorithms proposed in this thesis are based on unorganized 3D point clouds, generated by a LIDAR within a ship's cargo hold. Two different semantic perception methods are proposed in this thesis. One approach is based on probabilistic constraint networks; the second approach is based on Fuzzy Description Logic and spatial reasoning using a spatial ontology about the environment

Contemporary Robotics

This book book is a collection of 18 chapters written by internationally recognized experts and well-known professionals of the field. Chapters contribute to diverse facets of contemporary robotics and autonomous systems. The volume is organized in four thematic parts according to the main subjects, regarding the recent advances in the contemporary robotics. The first thematic topics of the book are devoted to the theoretical issues. This includes development of algorithms for automatic trajectory generation using redudancy resolution scheme, intelligent algorithms for robotic grasping, modelling approach for reactive mode handling of flexible manufacturing and design of an advanced controller for robot manipulators. The second part of the book deals with different aspects of robot calibration and sensing. This includes a geometric and treshold calibration of a multiple robotic line-vision system, robot-based inline 2D/3D quality monitoring using picture-giving and laser triangulation, and a study on prospective polymer composite materials for flexible tactile sensors. The third part addresses issues of mobile robots and multi-agent systems, including SLAM of mobile robots based on fusion of odometry and visual data, configuration of a localization system by a team of mobile robots, development of generic real-time motion controller for differential mobile robots, control of fuel cells of mobile robots, modelling of omni-directional wheeled-based robots, building of hunter- hybrid tracking environment, as well as design of a cooperative control in distributed population-based multi-agent approach. The fourth part presents recent approaches and results in humanoid and bioinspirative robotics. It deals with design of adaptive control of anthropomorphic biped gait, building of dynamic-based simulation for humanoid robot walking, building controller for perceptual motor control dynamics of humans and biomimetic approach to control mechatronic structure using smart materials

A sensor-based personal navigation system and its application for incorporating humans into a human-robot team

In this thesis methods for the sensor-based localisation of human beings are studied. The thesis presents the theory, test results and a realisation of the methods, which is called PeNa. PeNa is further applied to incorporate a human into a human-robot team that performs a simulated search and rescue task. Human-robot teamwork provides the vision for this thesis. Furthermore, the PeLoTe project and its search and rescue task provided the primary motivation for the research. However, the major part of this work and contribution is on sensor-based personal navigation. The approaches studied for personal navigation systems are based on sensor-based dead reckoning, laser-based dead reckoning, and map-based localisation. Sensor-based dead reckoning is based on heading estimation using a compass and gyro and step length estimation. Two alternative step length estimation methods are presented, ultrasound-based and accelerometer-based. Two laser dead reckoning methods are presented; a pose correlation method and a combined angle histogram matcher with position correlation. Furthermore, there are three variations for map-based localisation based on the well-known Monte Carlo Localisation (MCL): topological MCL, scan-based MCL, and a combined MCL method. As a result of the research it can be stated that it is possible to build a personal navigation system that can localise a human being indoors using only self-contained sensors. The results also show that this can be achieved using various combinations of sensors and methods. Furthermore, the personal navigation system that was developed is used to incorporate a human being into a human-robot team performing a search and rescue task. The initial results show that the location information provides a basis for creating situational awareness for a spatially distributed team

Learning cognitive maps: Finding useful structure in an uncertain world

In this chapter we will describe the central mechanisms that influence how people learn about large-scale space. We will focus particularly on how these mechanisms enable people to effectively cope with both the uncertainty inherent in a constantly changing world and also with the high information content of natural environments. The major lessons are that humans get by with a less is more approach to building structure, and that they are able to quickly adapt to environmental changes thanks to a range of general purpose mechanisms. By looking at abstract principles, instead of concrete implementation details, it is shown that the study of human learning can provide valuable lessons for robotics. Finally, these issues are discussed in the context of an implementation on a mobile robot. © 2007 Springer-Verlag Berlin Heidelberg