A new Measure for Optimization of Field Sensor Network with Application to LiDAR

This thesis proposes a solution to the problem of modeling and optimizing the field sensor network in terms of the coverage performance. The term field sensor is referred to a class of sensors which can detect the regions in 2D/3D spaces through non-contact measurements. The most widely used field sensors include cameras, LiDAR, ultrasonic sensor, and RADAR, etc. The key challenge in the applications of field sensor networks, such as area coverage, is to develop an effective performance measure, which has to involve both sensor and environment parameters. The nature of space distribution in the case of the field sensor incurs a great deal of difficulties for such development and, hence, poses it as a very interesting research problem. Therefore, to tackle this problem, several attempts have been made in the literature. However, they have failed to address a comprehensive and applicable approach to distinctive types of field sensors (in 3D), as only coverage of a particular sensor is usually addressed at the time. In addition, no coverage model has been proposed yet for some types of field sensors such as LiDAR sensors. In this dissertation, a coverage model is obtained for the field sensors based on the transformation of sensor and task parameters into the sensor geometric model. By providing a mathematical description of the sensor’s sensing region, a performance measure is introduced which characterizes the closeness between a single sensor and target configurations. In this regard, the first contribution is developing an Infinity norm based measure which describes the target distance to the closure of the sensing region expressed by an area-based approach. The second contribution can be geometrically interpreted as mapping the sensor’s sensing region to an n-ball using a homeomorphism map and developing a performance measure. The third contribution is introducing the measurement principle and establishing the coverage model for the class of solid-state (flash) LiDAR sensors. The fourth contribution is point density analysis and developing the coverage model for the class of mechanical (prism rotating mechanism) LiDAR sensors. Finally, the effectiveness of the proposed coverage model is illustrated by simulations, experiments, and comparisons is carried out throughout the dissertation. This coverage model is a powerful tool as it applies to the variety of field sensors

Autonomous Navigation of Mobile Robot Using Modular Architecture for Unstructured Environment

This article proposes a solution for autonomous navigation of mobile robot based on distributed control architecture. In this architecture, each stage of the algorithm is divided into separate software modules capable of interfacing to each other to obtain an effective global solution. The work starts with selection of suitable sensors depending on their requirement for the purpose and for the present work a stereo vision module and a laser range finder are used. These sensors are integrated with the robot controller via Ethernet/USB and the sensory feedbacks are used to control and navigate the robot. Using the architecture, an algorithm has been developed and implemented to intelligently avoid dynamic obstacles and optimally re-planning the path to reach the target location. The algorithm has been successfully tested with a Summit_XL mobile robot. The thesis describing the present research work is divided into eight chapters. The subject of the topic its contextual relevance and the related matters including the objectives of the work are presented in Chapter 1. The reviews on several diverse streams of literature on different issues of the topic such as autonomous navigation using various combinations of sensors networks, SLAM, obstacle detection and avoidance etc. are presented in Chapter 2. In Chapter 3, selected methodologies are explained. Chapter 4 presents the detail description of the sensors, automobile platform and software tools used to implement the developed methodology. In Chapter 5, detail view of the experimental setup is provided. Procedures and parametric evaluations are given in chapter 6. Successful indoor tests results are described in chapter 7. Finally, Chapter 8 presents the conclusion and future scope of the research work

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

The next detectors for gravitational wave astronomy

This paper focuses on the next detectors for gravitational wave astronomy which will be required after the current ground based detectors have completed their initial observations, and probably achieved the first direct detection of gravitational waves. The next detectors will need to have greater sensitivity, while also enabling the world array of detectors to have improved angular resolution to allow localisation of signal sources. Sect. 1 of this paper begins by reviewing proposals for the next ground based detectors, and presents an analysis of the sensitivity of an 8 km armlength detector, which is proposed as a safe and cost-effective means to attain a 4-fold improvement in sensitivity. The scientific benefits of creating a pair of such detectors in China and Australia is emphasised. Sect. 2 of this paper discusses the high performance suspension systems for test masses that will be an essential component for future detectors, while sect. 3 discusses solutions to the problem of Newtonian noise which arise from fluctuations in gravity gradient forces acting on test masses. Such gravitational perturbations cannot be shielded, and set limits to low frequency sensitivity unless measured and suppressed. Sects. 4 and 5 address critical operational technologies that will be ongoing issues in future detectors. Sect. 4 addresses the design of thermal compensation systems needed in all high optical power interferometers operating at room temperature. Parametric instability control is addressed in sect. 5. Only recently proven to occur in Advanced LIGO, parametric instability phenomenon brings both risks and opportunities for future detectors. The path to future enhancements of detectors will come from quantum measurement technologies. Sect. 6 focuses on the use of optomechanical devices for obtaining enhanced sensitivity, while sect. 7 reviews a range of quantum measurement options

Towards a bionic bat: A biomimetic investigation of active sensing, Doppler-shift estimation, and ear morphology design for mobile robots.

Institute of Perception, Action and BehaviourSo-called CF-FM bats are highly mobile creatures who emit long calls in which much of the energy is concentrated in a single frequency. These bats face sensor interpretation problems very similar to those of mobile robots provided with ultrasonic sensors, while navigating in cluttered environments. This dissertation presents biologically inspired engineering on the use of narrowband Sonar in mobile robotics. It replicates, using robotics as a modelling medium, how CF-FM bats process and use the constant frequency part of their emitted call for several tasks, aiming to improve the design and use of narrowband ultrasonic sensors for mobile robot navigation. The experimental platform for the work is RoBat, the biomimetic sonarhead designed by Peremans and Hallam, mounted on a commercial mobile platform as part of the work reported in this dissertation. System integration, including signal processing capabilities inspired by the bat’s auditory system and closed loop control of both sonarhead and mobile base movements, was designed and implemented. The result is a versatile tool for studying the relationship between environmental features, their acoustic correlates and the cues computable from them, in the context of both static, and dynamic real-time closed loop, behaviour. Two models of the signal processing performed by the bat’s cochlea were implemented, based on sets of bandpass filters followed by full-wave rectification and low-pass filtering. One filterbank uses Butterworth filters whose centre frequencies vary linearly across the set. The alternative filterbank uses gammatone filters, with centre frequencies varying non-linearly across the set. Two methods of estimating Doppler-shift from the return echoes after cochlear signal processing were implemented. The first was a simple energy-weighted average of filter centre frequencies. The second was a novel neural network-based technique. Each method was tested with each of the cochlear models, and evaluated in the context of several dynamic tasks in which RoBat was moved at different velocities towards stationary echo sources such as walls and posts. Overall, the performance of the linear filterbank was more consistent than the gammatone. The same applies to the ANN, with consistently better noise performance than the weighted average. The effect of multiple reflectors contained in a single echo was also analysed in terms of error in Doppler-shift estimation assuming a single wider reflector. Inspired by the Doppler-shift compensation and obstacle avoidance behaviours found in CF-FM bats, a Doppler-based controller suitable for collision detection and convoy navigation in robots was devised and implemented in RoBat. The performance of the controller is satisfactory despite low Doppler-shift resolution caused by lower velocity of the robot when compared to real bats. Barshan’s and Kuc’s 2D object localisation method was implemented and adapted to the geometry of RoBat’s sonarhead. Different TOF estimation methods were tested, the parabola fitting being the most accurate. Arc scanning, the ear movement technique to recover elevation cues proposed by Walker, and tested in simulation by her, Peremans and Hallam, was here implemented on RoBat, and integrated with Barshan’s and Kuc’s method in a preliminary narrowband 3D tracker. Finally, joint work with Kim, K¨ampchen and Hallam on designing optimal reflector surfaces inspired by the CF-FM bat’s large pinnae is presented. Genetic algorithms are used for improving the current echolocating capabilities of the sonarhead for both arc scanning and IID behaviours. Multiple reflectors around the transducer using a simple ray light-like model of sound propagation are evolved. Results show phase cancellation problems and the need of a more complete model of wave propagation. Inspired by a physical model of sound diffraction and reflections in the human concha a new model is devised and used to evolve pinnae surfaces made of finite elements. Some interesting paraboloid shapes are obtained, improving performance significantly with respect to the bare transducer

Methods and Devices for Mobile Robot Navigation and Mapping in Unstructured Environments

2006/2007The work described in this thesis has been carried out in the context of the exploration of an unknown environment by an autonomous mobile robot. It is rather difficult to imagine a robot that is truly autonomous without being capable of acquiring a model of its environment. This model can be built by the robot exploring the environment and registering the data collected with the sensors over time. In the last decades a lot of progress has been made regarding techniques focused on environments which posses a lot of structure. This thesis contributes to the goal of extending existing techniques to unstructured environments by proposing new methods and devices for mapping in real-time. The first part of the thesis addresses some of the problems of ultrasonic sensors which are widely used in mobile robotics for mapping and obstacle detection during exploration. Ultrasonic sensors have two main shortcomings leading to disappointing performance: uncertainty in target location and multiple reflections. The former is caused by wide beam width and the latter gives erroneous distance measurements because of the insertion of spikes not directly connected to the target. With the aim of registering a detailed contour of the environment surrounding the robot, a sensing device was developed by focusing the ultrasonic beam of the most common ultrasonic sensor to extend its range and improve the spatial resolution. Extended range makes this sensor much more suitable for mapping of outdoor environments which are typically larger. Improved spatial resolution enables the usage of recent laser scan matching techniques on the sonar scans of the environment collected with the sensor. Furthermore, an algorithm is proposed to mitigate some undesirable effects and problems of the ultrasonic sensor. The method registers the acquired raw ultrasonic signal in order to obtain a reliable mapping of the environment. A single sonar measurement consists of a number of pulses reflected by an obstacle. From a series of sensor readings at different sonar angles the sequence of pulses reflected by the environment changes according to the distance between the sensor and the environment. This results in an image of sonar reflections that can be built by representing the reading angle on the horizontal axis and the echoes acquired by the sensor on the vertical one. The characteristics of a sonar emission result in a texture embedded in the image. The algorithm performs a 2D texture analysis of the sonar reflections image in such a way that the texture continuity is analyzed at the overall image scale, thus enabling the correction of the texture continuity by restoring weak or missing reflections. The first part of the algorithm extracts geometric semantic attributes from the image in order to enhance and correct the signal. The second part of the algorithm applies heuristic rules to find the leading pulse of the echo and to estimate the obstacle location in points where otherwise it would not be possible due to noise or lack of signal. The method overcomes inherent problems of ultrasonic sensing in case of high irregularities and missing reflections. It is suitable for map building during mobile robot exploration missions. It's main limitation is small coverage area. This area however increases during exploration as more scans are processed from different positions. Localization and mapping problems were addressed in the second part of the thesis. The main issue in robot self-localization is how to match sensed data, acquired with devices such as laser range finders or ultrasonic range sensors, against reference map information. In particular scan matching techniques are used to correct the accumulated positional error using dead reckoning sensors like odometry and inertial sensors and thus cancel out the effects of noise on localization and mapping. Given the reference scan from a known position and the new scan in unknown or approximately known position, the scan matching algorithm should provide a position estimate which is close to the true robot position from which the new scan was acquired. A genetic based optimization algorithm that solves this problem called GLASM is proposed. It uses a novel fitness function which is based on a look up table requiring little memory to speed the search. Instead of searching for corresponding point pairs and then computing the mean of the distances between them, as in other algorithms, the fitness is directly evaluated by matching points which, after the projection on the same coordinate frame, fall in the search window around the previous scan. It has a linear computational complexity, whereas the algorithms based on correspondences have a quadratic cost. The GLASM algorithm has been compared to it's closest rivals. The results of comparison are reported in the thesis and show, to summarize, that GLASM outperforms them both in speed and in matching success ratio. Glasm is suitable for implementation in feature-poor environments and robust to high sensor noise, as is the case with the sonar readings used in this thesis which are much noisier than laser scanners. The algorithm does not place a high computational burden on the processor, which is important for real world applications where the power consumption is a concern, and scales easily on multiprocessor systems. The algorithm does not require an initial position estimate and is suitable for unstructured environments. In mobile robotics it is critical to evaluate the above mentioned methods and devices in real world applications on systems with limited power and computational resources. In the third part of the thesis some new theoretical results are derived concerning open problems in non-preemptive scheduling of periodic tasks on a uniprocessor. This results are then used to propose a design methodology which is used in an application on a mobile robot. The mobile robot is equipped with an embedded system running a new real-time kernel called Yartek with a non-preemptive scheduler of periodic tasks. The application is described and some preliminary mapping results are presented. The real-time operating system has been developed in a collaborative work for an embedded platform based on a Coldfire microcontroller. The operating system allows the creation and running of tasks and offers a dynamic management of a contiguous memory using a first-fit criterion. The tasks can be real-time periodic scheduled with non-preemptive EDF, or non real-time. In order to improve the usability of the system, a RAM-disk is included: it is actually an array defined in the main memory and managed using pointers, therefore its operation is very fast. The goal was to realize small autonomous embedded system for implementing real-time algorithms for non visual robotic sensors, such as infrared, tactile, inertial devices or ultrasonic proximity sensors. The system provides the processing requested by non visual sensors without imposing a computation burden on the main processor of the robot. In particular, the embedded system described in this thesis provides the robot with the environmental map acquired with the ultrasonic sensors. Yartek has low footprint and low overhead. In order to compare Yartek with another operating system a porting of RTAI for Linux has been performed on the Avnet M5282EVB board and testing procedures were implemented. Tests regarding context switch time, jitter time and interrupt latency time are reported to describe the performance of Yartek. The contributions of this thesis include the presentation of new algorithms and devices, their applications and also some theoretical results. They are briefly summarized as: A focused ultrasonic sensing device is developed and used in mapping applications. An algorithm that processes the ultrasonic readings in order to develop a reliable map of the environment is presented. A new genetic algorithm for scan matching called GLASM is proposed. Schedulability conditions for non-preemptive scheduling in a hard real-time operating system are introduced and a design methodology is proposed. A real-time kernel for embedded systems in mobile robotics is presented. A practical robotic application is described and implementation details and trade-offs are explained.XIX Ciclo197

Dynamic obstacles avoidance algorithms for unmanned ground vehicles

En las últimas décadas, los vehículos terrestres no tripulados (UGVs) están siendo cada vez más empleados como robots de servicios. A diferencia de los robots industriales, situados en posiciones fijas y controladas, estos han de trabajar en entornos dinámicos, compartiendo su espacio con otros vehículos y personas. Los UGVs han de ser capaces de desplazarse sin colisionar con ningún obstáculo, de tal manera que puedan asegurar tanto su integridad como la del entorno. En el estado del arte encontramos algoritmos de navegación autónoma diseñados para UGVs que son capaces de planificar rutas de forma segura con objetos estáticos y trabajando en entornos parcialmente controlados. Sin embargo, cuando estos entornos son dinámicos, se planifican rutas más peligrosas y que a menudo requieren de un mayor consumo de energía y recursos, e incluso pueden llegar a bloquear el UGV en un mínimo local. En esta tesis, la adaptación de algunos algoritmos disponibles en el estado del arte para trabajar en entornos dinámicos han sido planteados. Estos algoritmos incluyen información temporal tales como los basados en arcos de curvatura (PCVM y DCVM) y los basados en ventanas dinámicas (DW4DO y DW4DOT). Además, se ha propuesto un planificador global basado en Lattice State Planner (DLP) que puede resolver situaciones donde los evitadores de obstáculos reactivos no funcionan. Estos algoritmos han sido validados tanto en simulación como en entornos reales, utilizando distintas plataformas robóticas, entre las que se incluye un robot asistente (RoboShop) diseñado y construido en el marco de esta tesis

Laser-Based Detection and Tracking of Moving Obstacles to Improve Perception of Unmanned Ground Vehicles

El objetivo de esta tesis es desarrollar un sistema que mejore la etapa de percepción de vehículos terrestres no tripulados (UGVs) heterogéneos, consiguiendo con ello una navegación robusta en términos de seguridad y ahorro energético en diferentes entornos reales, tanto interiores como exteriores. La percepción debe tratar con obstáculos estáticos y dinámicos empleando sensores heterogéneos, tales como, odometría, sensor de distancia láser (LIDAR), unidad de medida inercial (IMU) y sistema de posicionamiento global (GPS), para obtener la información del entorno con la precisión más alta, permitiendo mejorar las etapas de planificación y evitación de obstáculos. Para conseguir este objetivo, se propone una etapa de mapeado de obstáculos dinámicos (DOMap) que contiene la información de los obstáculos estáticos y dinámicos. La propuesta se basa en una extensión del filtro de ocupación bayesiana (BOF) incluyendo velocidades no discretizadas. La detección de velocidades se obtiene con Flujo Óptico sobre una rejilla de medidas LIDAR discretizadas. Además, se gestionan las oclusiones entre obstáculos y se añade una etapa de seguimiento multi-hipótesis, mejorando la robustez de la propuesta (iDOMap). La propuesta ha sido probada en entornos simulados y reales con diferentes plataformas robóticas, incluyendo plataformas comerciales y la plataforma (PROPINA) desarrollada en esta tesis para mejorar la colaboración entre equipos de humanos y robots dentro del proyecto ABSYNTHE. Finalmente, se han propuesto métodos para calibrar la posición del LIDAR y mejorar la odometría con una IMU