VFH+ based shared control for remotely operated mobile robots

This paper addresses the problem of safe and efficient navigation in remotely controlled robots operating in hazardous and unstructured environments; or conducting other remote robotic tasks. A shared control method is presented which blends the commands from a VFH+ obstacle avoidance navigation module with the teleoperation commands provided by an operator via a joypad. The presented approach offers several advantages such as flexibility allowing for a straightforward adaptation of the controller's behaviour and easy integration with variable autonomy systems; as well as the ability to cope with dynamic environments. The advantages of the presented controller are demonstrated by an experimental evaluation in a disaster response scenario. More specifically, presented evidence show a clear performance increase in terms of safety and task completion time compared to a pure teleoperation approach, as well as an ability to cope with previously unobserved obstacles.Comment: 8 pages,6 figure

A METHODOLOGY FOR CREATING INTELLIGENT WHEELCHAIR USERS’ PROFILES

Intelligent Wheelchair (IW) is a new concept aiming to allow higher autonomy to people with lower mobility such as disabled or elderly individuals. Some of the more recent IWs have a multimodal interface, enabling multiple command modes such as joystick, voice commands, head movements, or even facial expressions. In these IW it may be very useful to provide the user with the best way of driving it through an adaptive interface. This paper describes the foundations for creating a simple methodology for extracting user profiles, which can be used to adequately select the best IW command mode for each user. The methodology is based on an interactive wizard composed by a flexible set of simple tasks presented to the user, and a method for extracting and analyzing the user’s execution of those tasks. The results achieved showed that it is possible to extract simple user profiles, using the proposed method. Thus, the approach may be further used to extract more complete user profiles, just by extending the set of tasks used, enabling the adaptation of the IW interface to each user’s characteristics.info:eu-repo/semantics/publishedVersio

低重心型平行二輪ビークルにおける質量移動機構を用いた車体傾斜制御設計に関する研究

豊橋技術科学大

Desenvolvimento de um protótipo e de metodologias de controlo de uma cadeira de rodas inteligente

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

Learning human navigational skill for smart wheelchair.

by Hon Nin Chow.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 79-84).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation --- p.1Chapter 1.2 --- Organization of the Thesis --- p.3Chapter 2 --- Literature Survey --- p.6Chapter 2.1 --- Learning-by-Demonstration --- p.6Chapter 2.2 --- Neural Networks --- p.7Chapter 2.3 --- Navigation Learning --- p.8Chapter 2.4 --- Localization --- p.9Chapter 2.5 --- Robotic Wheelchair --- p.10Chapter 3 --- System Implementation --- p.12Chapter 3.1 --- Hardware Platform --- p.12Chapter 3.2 --- Software Platform --- p.14Chapter 3.3 --- Basic Functionality --- p.15Chapter 3.3.1 --- Collision Avoidance --- p.15Chapter 3.3.2 --- Wearable Eye-jaw Control Interface --- p.16Chapter 4 --- Learning Human Navigational Skill --- p.22Chapter 4.1 --- Introduction --- p.22Chapter 4.2 --- Problem Formulation --- p.23Chapter 4.3 --- Approach --- p.23Chapter 4.4 --- Experimental Study --- p.26Chapter 4.4.1 --- Settings --- p.26Chapter 4.4.2 --- Results --- p.30Chapter 4.5 --- Discussions --- p.31Chapter 5 --- Learning from Multi-phase Demonstrations --- p.33Chapter 5.1 --- Introduction --- p.33Chapter 5.2 --- Problem Formulation --- p.34Chapter 5.3 --- Approach --- p.35Chapter 5.4 --- Experimental Study --- p.35Chapter 5.4.1 --- Settings --- p.35Chapter 5.4.2 --- Results --- p.37Chapter 5.5 --- Evaluation of Learning Performance --- p.37Chapter 5.6 --- Discussions --- p.43Chapter 6 --- Localization Learning --- p.44Chapter 6.1 --- Introduction --- p.44Chapter 6.2 --- Problem Formulation --- p.45Chapter 6.3 --- Approach --- p.45Chapter 6.4 --- Experimental Study --- p.46Chapter 6.4.1 --- Settings --- p.46Chapter 6.4.2 --- Result 1: Localization Performance --- p.47Chapter 6.4.3 --- Result 2: Similar Sensor Patterns in Various Configurations . --- p.53Chapter 6.4.4 --- Result 3: Small Variations in Major Dimensions of Environ- mental Feature along the Route --- p.53Chapter 6.5 --- Discussions --- p.59Chapter 6.5.1 --- Accuracy --- p.59Chapter 6.5.2 --- Choices of Sensor-Configuration Mappings --- p.60Chapter 7 --- Conclusion --- p.62Chapter 7.1 --- Contributions --- p.62Chapter 7.2 --- Future Work --- p.65Chapter A --- Cascade Neural Network --- p.67Chapter B --- Trajectories for the Navigation Learning in Chapter 4 --- p.69Chapter C --- Publications Resulted from the Study --- p.7

Natural interactions: an application for gestural hands recognition

Dissertação de Mestrado em Desenvolvimento de Software e Sistemas Interativos apresentada à Escola Superior de Tecnologia do Instituto Politécnico de Castelo Branco.Este trabalho apresenta um sistema para o desenvolvimento de novas interfaces homem-máquina com foco no reconhecimento de gestos estáticos de mãos humanas. A proposta é auxiliar o acesso a certos objetos para o ocupante de uma cadeira de rodas inteligente, a fim de facilitar a sua vida diária. A metodologia proposta baseia-se no uso de processos computacionais simples e de hardware de baixo custo. O seu desenvolvimento envolve uma abordagem completa aos problemas de visão computacional, com base nas etapas da captura de imagem de vídeo, segmentação de imagens, extração de características, reconhecimento e classificação de padrões. A importância deste trabalho relaciona-se com a necessidade de construir novos modelos de interação que permitam, de uma forma natural e intuitiva, a simplificação da vida quotidiana de uma pessoa com dificuldades motoras.Abstract: This thesis presents a system for the development of new human-machine interfaces focused on static gestures recognition of human hands. The proposal is to give access to certain objects to the occupant of an intelligent wheelchair in order to facilitate their daily life. The proposed methodology relies on the use of simple computational processes and low-cost hardware. Its development involves a comprehensive approach to the problems of computer vision, based on the steps of the video image capture, image segmentation, feature extraction, pattern recognition and classification. The importance of this work relates to the need to build new models of interaction that allow, in a natural and intuitive way, to simplify the daily life of a disable person

An Incremental Navigation Localization Methodology for Application to Semi-Autonomous Mobile Robotic Platforms to Assist Individuals Having Severe Motor Disabilities.

In the present work, the author explores the issues surrounding the design and development of an intelligent wheelchair platform incorporating the semi-autonomous system paradigm, to meet the needs of individuals with severe motor disabilities. The author presents a discussion of the problems of navigation that must be solved before any system of this type can be instantiated, and enumerates the general design issues that must be addressed by the designers of systems of this type. This discussion includes reviews of various methodologies that have been proposed as solutions to the problems considered. Next, the author introduces a new navigation method, called Incremental Signature Recognition (ISR), for use by semi-autonomous systems in structured environments. This method is based on the recognition, recording, and tracking of environmental discontinuities: sensor reported anomalies in measured environmental parameters. The author then proposes a robust, redundant, dynamic, self-diagnosing sensing methodology for detecting and compensating for hidden failures of single sensors and sensor idiosyncrasies. This technique is optimized for the detection of spatial discontinuity anomalies. Finally, the author gives details of an effort to realize a prototype ISR based system, along with insights into the various implementation choices made

Development of an intelligent wheelchair 3D simulator/visualizer

Tese de mestrado integrado. Engenharia Informática e Computação. Universidade do Porto. Faculdade de Engenharia. 201

Advanced Map Matching Technologies and Techniques for Pedestrian/Wheelchair Navigation

Due to the constantly increasing technical advantages of mobile devices (such as smartphones), pedestrian/wheelchair navigation recently has achieved a high level of interest as one of smartphones’ potential mobile applications. While vehicle navigation systems have already reached a certain level of maturity, pedestrian/wheelchair navigation services are still in their infancy. By comparing vehicle navigation systems, a set of map matching requirements and challenges unique in pedestrian/wheelchair navigation is identified. To provide navigation assistance to pedestrians and wheelchair users, there is a need for the design and development of new map matching techniques. The main goal of this research is to investigate and develop advanced map matching technologies and techniques particular for pedestrian/wheelchair navigation services. As the first step in map matching, an adaptive candidate segment selection algorithm is developed to efficiently find candidate segments. Furthermore, to narrow down the search for the correct segment, advanced mathematical models are applied. GPS-based chain-code map matching, Hidden Markov Model (HMM) map matching, and fuzzy-logic map matching algorithms are developed to estimate real-time location of users in pedestrian/wheelchair navigation systems/services. Nevertheless, GPS signal is not always available in areas with high-rise buildings and even when there is a signal, the accuracy may not be high enough for localization of pedestrians and wheelchair users on sidewalks. To overcome these shortcomings of GPS, multi-sensor integrated map matching algorithms are investigated and developed in this research. These algorithms include a movement pattern recognition algorithm, using accelerometer and compass data, and a vision-based positioning algorithm to fill in signal gaps in GPS positioning. Experiments are conducted to evaluate the developed algorithms using real field test data (GPS coordinates and other sensors data). The experimental results show that the developed algorithms and the integrated sensors, i.e., a monocular visual odometry, a GPS, an accelerometer, and a compass, can provide high-quality and uninterrupted localization services in pedestrian/wheelchair navigation systems/services. The map matching techniques developed in this work can be applied to various pedestrian/wheelchair navigation applications, such as tracking senior citizens and children, or tourist service systems, and can be further utilized in building walking robots and automatic wheelchair navigation systems

A non-holonomic, highly human-in-the-loop compatible, assistive mobile robotic platform guidance navigation and control strategy

The provision of assistive mobile robotics for empowering and providing independence to the infirm, disabled and elderly in society has been the subject of much research. The issue of providing navigation and control assistance to users, enabling them to drive their powered wheelchairs effectively, can be complex and wide-ranging; some users fatigue quickly and can find that they are unable to operate the controls safely, others may have brain injury re-sulting in periodic hand tremors, quadriplegics may use a straw-like switch in their mouth to provide a digital control signal. Advances in autonomous robotics have led to the development of smart wheelchair systems which have attempted to address these issues; however the autonomous approach has, ac-cording to research, not been successful; users reporting that they want to be active drivers and not passengers. Recent methodologies have been to use collaborative or shared control which aims to predict or anticipate the need for the system to take over control when some pre-decided threshold has been met, yet these approaches still take away control from the us-er. This removal of human supervision and control by an autonomous system makes the re-sponsibility for accidents seriously problematic. This thesis introduces a new human-in-the-loop control structure with real-time assistive lev-els. One of these levels offers improved dynamic modelling and three of these levels offer unique and novel real-time solutions for: collision avoidance, localisation and waypoint iden-tification, and assistive trajectory generation. This architecture and these assistive functions always allow the user to remain fully in control of any motion of the powered wheelchair, shown in a series of experiments