Robust tracking of multiple soccer robots using random finite sets

Having a good estimation of the robot-players positions is becoming imperative to accomplish high level tasks in any RoboCup League. Classical approaches use a vector representation of the robot positions and Bayesian filters to propagate them over time. However, these approaches have data association problems in real game situations. In order to tackle this issue, this paper presents a new method for building robot maps using Random Finite Sets (RFS). The method is applied to the problem of estimating the position of the teammates and opponents in the SPL league. Considering the computational capabilities of Nao robots, the GM-PHD implementation of RFS is used. In this implementation, the estimations of the robot positions and the robot observations are represented using Mixture of Gaussians, but instead of associating a robot or an observation to a given Gaussian, the weight of each Gaussian maintains an estimation of the number of robots that it represents. The proposed method is validated in several real game situations and compared with a classical EKF based approach. The proposed GM-PHD method shows a much better performance, being able to deal with most of the data association problems, even being able to manage complex situations such as robot kidnappings

Situational Awareness and Road Prediction for Trajectory Control Applications

The Handbook of Intelligent Vehicles provides a complete coverage of the fundamentals, new technologies, and sub-areas essential to the development of intelligent vehicles; it also includes advances made to date, challenges, and future trends. Significant strides in the field have been made to date; however, so far there has been no single book or volume which captures these advances in a comprehensive format, addressing all essential components and subspecialties of intelligent vehicles, as this book does. Since the intended users are engineering practitioners, as well as researchers and graduate students, the book chapters do not only cover fundamentals, methods, and algorithms but also include how software/hardware are implemented, and demonstrate the advances along with their present challenges. Research at both component and systems levels are required to advance the functionality of intelligent vehicles. This volume covers both of these aspects in addition to the fundamentals listed above

Investigating the organisational factors associated with variation in clinical productivity in community pharmacies: a mixed-methods study

Background: Community pharmacies play a key role in health-care systems, dispensing prescriptions and providing medicine-related services. Service provision varies across community pharmacy organisations and may depend on organisational characteristics, such as ownership, staffing and skill mix. Objectives: To inform the commissioning of community pharmacy services by (1) exploring variation in clinical productivity (levels of service delivery and service quality) in pharmacies, (2) identifying the organisational factors associated with this variation and (3) developing a toolkit for commissioners. Design: Mixed-methods study: community pharmacy survey, administrative data analysis, patient survey, stakeholder interviews and toolkit development. Setting: Nine socioeconomically diverse geographical areas of England. Participants: Stage 1: community pharmacies in nine study areas. Stage 2: in 39 pharmacies, two consecutive samples of approximately 30 patients each following receipt of (1) dispensing and (2) medicines use review (MUR) services. Pharmacy and commissioning representatives from across all types of pharmacy and study sites. Main outcome measures: Stage 1: dispensing, MUR, new medicines service volume and safety climate. Stage 2: patient satisfaction, Satisfaction with Information about Medicines Scale (SIMS) and Medication Adherence Report Scale (MARS). Data sources: Stage 1: (i) community pharmacy activity data; (ii) socioeconomic and health needs data; and (iii) community pharmacy questionnaire (ownership type, organisational culture, staffing and skill mix, working patterns, management structure, safety climate, pharmacy–general practice integration), all linked by pharmacy postcode and organisational ‘F’ code. Stage 2: (i) patient questionnaire (background, patient satisfaction, SIMS, MARS); (ii) semistructured stakeholder interviews (variation in quantity and quality of service provision, opportunities and barriers to clinical productivity, mechanisms by which different organisational characteristics may help or hinder clinical productivity). Quantitative data were analysed by fitting a series of fixed-effects linear, logistic and multilevel logistic regression models in Stata® (version 13; StataCorp LP, College Station, TX, USA). Qualitative data were analysed thematically using a framework approach in NVivo10 (QSR International, Warrington, UK). Results: In stage 1, 285 out of 817 pharmacy questionnaires were returned [valid response rate 34.6% (277/800)]. In stage 2, 1008 out of 2124 patient questionnaires were returned [valid response rate 46.5% (971/2087)]. Thirty pharmacy and 10 commissioning representatives were interviewed face to face or by telephone. Following integration of stage 1 and 2 findings, clinical productivity was associated with pharmacy ownership type, organisational culture, staffing and skill mix, and pharmacy–general practice relationships. Extra-organisational associations included local area deprivation, age profile and health needs, pharmacy location, public perceptions and expectations, supply chain problems, commissioning structures/processes, levels of remuneration and legal/regulatory constraints. Existing arrangements for monitoring clinical productivity focused primarily on quantity. Limitations: Non-random selection of study sites and non-participation by four major pharmacy chains limited generalisability. Investigation of the full scope of pharmacy service provision was prevented by a lack of available activity data for locally commissioned services. Quantitative exploration of service quality was limited by available validated measures. Conclusions: These findings have important implications for community pharmacies and service commissioners, highlighting the importance of ownership type, organisational culture, staffing and skill mix for maximising the delivery of high-quality pharmacy services and informing the development of a commissioners’ toolkit. Future work: Future studies should (1) develop tools to measure community pharmacy service quality; (2) describe and evaluate different models of skill mix; and (3) explore how services are commissioned locally from community pharmacies and the extent to which local needs are met. Funding: The National Institute for Health Research Health Services and Delivery Research programme