An annotated bibligraphy of multisensor integration

technical reportIn this paper we give an annotated bibliography of the multisensor integration literature

Workshop on multisensor integration in manufacturing automation

Journal ArticleMany people helped make the Workshop a success, but special thanks must be given to Howard Moraff for his support, and to Vicky Jackson for her efforts in making things run smoothly. Finally, thanks to Jake Aggarwal for helping to start the ball rolling

Система управления на основе нечеткой логики для мобильного робототехнического комплекса в частично наблюдаемой среде

Пропонується система управління на основі нечіткої логіки, яка дозволяє мобільному робототехнічному коплексу досягати поставлених цілей в середовищі, яке спостерігається частково. В системі управліня базові поведінки запропоновано розширити поведінками “рух вздовж стіни справа” та “рух вздовж стіни зліва”, які використовуються при оминанні перешкод. Для кожної з поведінок та для контролю швидкості розроблені набори нечітких правил та реалізовано метод уникнення конфліктів при координації поведінок. Блок керування швидкістю реалізовує більш точне і швидке досягнення цілей шляхом зменшення швидкості при наближенні до перешкоди або цілі та збільшення швидкості в іншому випадку.The control system based on fuzzy logic that enables achieving goals by mobile robotic system in an uncertain environment with obstacles is proposed. We suggest to apply some additional behaviors such as “movement along the right wall” and “movement along the left wall” for implementation of mobile robot motion control. Fuzzy rules for each of behaviors units and speed control unit are realized. A method for coordination conflicts among behaviors is developed. The velocity control unit, which provides more accurate and rapid goal achievement by decreasing speed when obstacles or goal is near robotic system and increasing speed otherwise.Представляется система управления на основе нечеткой логики для достижения целей мобильным робототехническим комплексом в частично наблюдаемой среде. Базовые поведения в системе управления расширены дополнительными поведениями “движение вдоль стены справа” и “движение вдоль стены слева”, которые будуть использоватся для обхода препятствий. Для каждого из поведений и для контроля скорости разработаны наборы нечетких правил. Также разработан метод избежания конфликтов при координации поведений. Блок управления скоростью реализовывает более точное и быстрое достижение целей с помощью уменшения скорости при приближении к препятствию или цели и увеличения скорости в противном случае

Design and Development of Sensor Integrated Robotic Hand

Most of the automated systems using robots as agents do use few sensors according to the need. However, there are situations where the tasks carried out by the end-effector, or for that matter by the robot hand needs multiple sensors. The hand, to make the best use of these sensors, and behave autonomously, requires a set of appropriate types of sensors which could be integrated in proper manners. The present research work aims at developing a sensor integrated robot hand that can collect information related to the assigned tasks, assimilate there correctly and then do task action as appropriate. The process of development involves selection of sensors of right types and of right specification, locating then at proper places in the hand, checking their functionality individually and calibrating them for the envisaged process. Since the sensors need to be integrated so that they perform in the desired manner collectively, an integration platform is created using NI PXIe-1082. A set of algorithm is developed for achieving the integrated model. The entire process is first modelled and simulated off line for possible modification in order to ensure that all the sensors do contribute towards the autonomy of the hand for desired activity. This work also involves design of a two-fingered gripper. The design is made in such a way that it is capable of carrying out the desired tasks and can accommodate all the sensors within its fold. The developed sensor integrated hand has been put to work and its performance test has been carried out. This hand can be very useful for part assembly work in industries for any shape of part with a limit on the size of the part in mind. The broad aim is to design, model simulate and develop an advanced robotic hand. Sensors for pick up contacts pressure, force, torque, position, surface profile shape using suitable sensing elements in a robot hand are to be introduced. The hand is a complex structure with large number of degrees of freedom and has multiple sensing capabilities apart from the associated sensing assistance from other organs. The present work is envisaged to add multiple sensors to a two-fingered robotic hand having motion capabilities and constraints similar to the human hand. There has been a good amount of research and development in this field during the last two decades a lot remains to be explored and achieved. The objective of the proposed work is to design, simulate and develop a sensor integrated robotic hand. Its potential applications can be proposed for industrial environments and in healthcare field. The industrial applications include electronic assembly tasks, lighter inspection tasks, etc. Application in healthcare could be in the areas of rehabilitation and assistive techniques. The work also aims to establish the requirement of the robotic hand for the target application areas, to identify the suitable kinds and model of sensors that can be integrated on hand control system. Functioning of motors in the robotic hand and integration of appropriate sensors for the desired motion is explained for the control of the various elements of the hand. Additional sensors, capable of collecting external information and information about the object for manipulation is explored. Processes are designed using various software and hardware tools such as mathematical computation MATLAB, OpenCV library and LabVIEW 2013 DAQ system as applicable, validated theoretically and finally implemented to develop an intelligent robotic hand. The multiple smart sensors are installed on a standard six degree-of-freedom industrial robot KAWASAKI RS06L articulated manipulator, with the two-finger pneumatic SHUNK robotic hand or designed prototype and robot control programs are integrated in such a manner that allows easy application of grasping in an industrial pick-and-place operation where the characteristics of the object can vary or are unknown. The effectiveness of the actual recommended structure is usually proven simply by experiments using calibration involving sensors and manipulator. The dissertation concludes with a summary of the contribution and the scope of further work

Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

Opportunistic Multi-sensor Fusion for Robust Navigation in Smart Environments

Proceedings of: Workshop on User-Centric Technologies and Applications (CONTEXTS 2011), Salamanca, April 6-8, 2011This paper presents the design of a navigation system for multiple autonomous robotic platforms. It performs multisensor fusion using a Monte Carlo Bayesian filter, and has been designed to maximize information acquisition. Apart from sensors equipped in the mobile platform, the system can dynamically integrate observations from friendly external sensing entities, increasing robustness and making it suitable for both indoor and outdoor operation. A multi-agent layer manages the information acquisition process, making it transparent for the core filtering solution. As a proof of concept, some preliminary results are presented over a real platform using the part of the system specialized in outdoor navigationThis work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/ TIC-1485) and DPS2008-07029-C02-02.publicad

GRASP News Volume 9, Number 1

A report of the General Robotics and Active Sensory Perception (GRASP) Laboratory

Model of Competencies for Decomposition of Human Behavior: Application to Control System of Robots

Humans and machines have shared the same physical space for many years. To share the same space, we want the robots to behave like human beings. This will facilitate their social integration, their interaction with humans and create an intelligent behavior. To achieve this goal, we need to understand how human behavior is generated, analyze tasks running our nerves and how they relate to them. Then and only then can we implement these mechanisms in robotic beings. In this study, we propose a model of competencies based on human neuroregulator system for analysis and decomposition of behavior into functional modules. Using this model allow separate and locate the tasks to be implemented in a robot that displays human-like behavior. As an example, we show the application of model to the autonomous movement behavior on unfamiliar environments and its implementation in various simulated and real robots with different physical configurations and physical devices of different nature. The main result of this study has been to build a model of competencies that is being used to build robotic systems capable of displaying behaviors similar to humans and consider the specific characteristics of robots