In the field of mobile robotics, the study of multi-robot systems (MRSs) has grown significantly in size and importance in recent years. Having made great progress in the development of the basic problems concerning single-robot control, many researchers shifted their focus to the study of multi-robot coordination. This paper presents a systematic survey and analysis of the existing literature on coordination, especially in multiple mobile robot systems (MMRSs). A series of related problems have been reviewed, which include a communication mechanism, a planning strategy and a decision-making structure. A brief conclusion and further research perspectives are given at the end of the paper.

We examined how individual and institutional factors in health care settings affected discrimination toward persons with HIV/AIDS. A representative sample of 1101 Chinese service providers was recruited in 2005, including doctors, nurses, and laboratory technicians. Multiple regression models were used to describe associations among identified variables, the relationships with HIV-related personal prejudicial attitudes, and perceived institutional support and discrimination at work. Multivariate analyses revealed that respondents' general view of persons living with HIV/AIDS and their perceived levels of support from their institutions regarding protection procedures were both important predictors for discrimination intent. Perceived institutional support varied according to age, gender, ethnicity, and training background. A better understanding of HIV-related discrimination in health care settings requires consideration of both individual and institutional factors.

Human detection and tracking are essential aspects to be considered in service robotics, as the robot often shares its workspace and interacts closely with humans. This paper presents an online learning framework for human classification in 3D LiDAR scans, taking advantage of robust multi-target tracking to avoid the need for data annotation by a human expert. The system learns iteratively by retraining a classifier online with the samples collected by the robot over time. A novel aspect of our approach is that errors in training data can be corrected using the information provided by the 3D LiDAR-based tracking. In order to do this, an efficient 3D cluster detector of potential human targets has been implemented. We evaluate the framework using a new 3D LiDAR dataset of people moving in a large indoor public space, which is made available to the research community. The experiments analyse the real-time performance of the cluster detector and show that our online learned human classifier matches and in some cases outperforms its offline version.

This study assessed the effect of a brief intervention aimed at reducing HIV-related stigma among service providers in China. From December 2005 to June 2006, 138 service providers from four county hospitals in the Yunnan province of China were randomly assigned into either an intervention or a control condition. HIV stigma reduction concepts were conveyed through participatory small group activities, including role-plays, games, group discussions, and testimony by an HIV advocate. Participants were assessed at baseline before the intervention, and at 3- and 6-month follow-ups. Data were analyzed using a logistic regression mixed-effects model. Service providers in the brief intervention condition were significantly more likely to report better protection of patients' confidentiality and right to HIV testing, lower levels of negative feelings toward people living with HIV/AIDS, and more accurate understanding and practice of universal precautions. This brief intervention pilot showed potential in reducing HIV stigma and discrimination among service providers in China. Further intervention trials are needed to test the efficacy and long-term outcomes of this intervention.

This paper presents a novel 3DOF pedestrian trajectory prediction approach for autonomous mobile service robots. While most previously reported methods are based on learning of 2D positions in monocular camera images, our approach uses range-finder sensors to learn and predict 3DOF pose trajectories (i.e. 2D position plus 1D rotation within the world coordinate system). Our approach, T-Pose-LSTM (Temporal 3DOF-Pose Long-Short-Term Memory), is trained using long-term data from real-world robot deployments and aims to learn context-dependent (environment-and timespecific) human activities. Our approach incorporates long-term temporal information (i.e. date and time) with short-term pose observations as input. A sequence-to-sequence LSTM encoderdecoder is trained, which encodes observations into LSTM and then decodes as predictions. For deployment, it can perform on-the-fly prediction in real-time. Instead of using manually annotated data, we rely on a robust human detection, tracking and SLAM system, providing us with examples in a global coordinate system. We validate the approach using more than 15K pedestrian trajectories recorded in a care home environment over a period of three months. The experiment shows that the proposed T-Pose-LSTM model advances the state-of-the-art 2D-based method for human trajectory prediction in long-term mobile robot deployments.

No abstract

No abstract

Objectives The objective of the intervention was to reduce service providers’ stigmatizing attitudes and behaviors toward people living with HIV. Methods The randomized controlled trial was conducted in 40 county-level hospitals in 2 provinces of China between October 2008 and February 2010. Forty-four service providers were randomly selected from each hospital, yielding a total of 1760 study participants. We randomized the hospitals to either an intervention condition or a control condition. In the intervention hospitals, about 15% of the popular opinion leaders were identified and trained to disseminate stigma reduction messages. Results We observed significant improvements for the intervention group in reducing prejudicial attitudes (P < .001), reducing avoidance intent towards people living with HIV (P < .001), and increasing institutional support in the hospitals (P = .003) at 6 months after controlling for service providers’ background factors and clinic-level characteristics. The intervention effects were sustained and strengthened at 12 months. Conclusions The intervention reduced stigmatizing attitudes and behaviors among service providers. It has the potential to be integrated into the health care systems in China and other countries.