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In this paper, we investigate a scenario of one-human-multiple-robot navigation in three dimensions, and examine the impacts of the VR (Virtual Reality) technology on human properties from a control-theoretic perspective. We start by reviewing a passivity-based distributed control architecture that takes complementary interactions such that motion synchronization is autonomously completed by a distributed robot controller while the operator is dedicated to robot navigation. Due to the limited human capability of 3-D recognition and limited dimensionality on the real-time manipulability, 3-D navigation is completely different from that of the one- or two-dimensional case and we need to carefully design both feedback and command interfaces between the operator and robots. Specifically, we employ two different pairs of the interfaces, traditional joystick controller with 2-D display monitor and HMD (Head Mounted Display) with VR controller. We then build human models from the operation data with these interfaces on a human-in-the-loop simulator. Through the human modeling, we present two novel findings: (i) VR interfaces improve the accuracy of the human model with about 25∼45% of fitting ratio, which must drastically eases the design of human-robot collaboration systems, (ii) VR interfaces enhance human passivity, which is a key to ensuring closed-loop stability for the human-in-the-loop system.

This article considers solving an overdetermined system of linear equations in peer-to-peer multiagent networks. The network is assumed to be synchronous and strongly connected. Each agent has a set of local data points, and their goal is to compute a linear model that fits the collective data points. In principle, the agents can apply the decentralized gradient-descent method (DGD). However, when the data matrix is ill-conditioned, DGD requires many iterations to converge and is unstable against system noise. We propose a decentralized preconditioning technique to mitigate the deleterious effects of the data points’ conditioning on the convergence rate of DGD. The proposed algorithm converges linearly, with an improved convergence rate than DGD. Considering the practical scenario where the computations performed by the agents are corrupted, we study the robustness guarantee of the proposed algorithm. In addition, we apply the proposed algorithm for solving decentralized state estimation problems. The empirical results show our proposed state predictor’s favorable convergence rate and robustness against system noise compared to prominent decentralized algorithms.

Passivity-based control (PBC) and the related energy-shaping control have a rich history in robotics going back to the 1980s. The kinematics and dynamics of robot manipulators and Lagrangian systems in general are highly complex, and the realization that they satisfy a passivity property was crucial to the development of rigorous robust and adaptive control laws, beginning in the mid-1980s and continuing to this day (see “Summary”). See “Passivity-Based Control” for the origin of the term “passivity-based control.”

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This paper investigates coordination between a human operator and robotic swarm. The objective is to guarantee human-enabled motion synchronization to desired position/velocity references. The presence of a human in the system could improve performance in completing complex missions and adaptation to changes in environment or mission goal. Although in some works the human is modeled or assumed as a passive system, this does not always hold and a systematic solution to deal with non-passive humans is still needed. To this end, this paper assumes the human operator’s process as a passivity-short system. Based on the positive feedback interconnection of passivity-short systems, we present a novel distributed control architecture interconnecting the human operator and the robotic swarm. The control goals are then proved to be achieved even in the presence of passivity shortage in the human operator. We finally demonstrate the proposed architecture through simulation studies and also implementation on an experimental testbed.

Nocturia is an under‐reported and undertreated condition in primary care. In this article the authors provide GPs with practical recommendations and tools for the assessment, diagnosis and management of nocturia, using real clinical cases as examples. The recommendations are based on clinical evidence as well as the authors' personal experiences.

Distributed average consensus refers to computing average of inputs held by multiple agents communicating with each other over peer-to-peer network. Cooperation amongst agents is imperative for any distributed average consensus protocol as each agent has to share its input with other agents, which are usually the adjacent(neighboring) agents. That being said, privacy issues could discourage some agents from participating in such protocols. This paper proposes a novel distributed privacy mechanism that preserves privacy of the collection of honest agents’ inputs as long as the colluding semi-honest agents do not form a vertex cut. The proposed privacy mechanism does not alter the average of agents’ inputs, hence it does not provide privacy against what is already lost by knowing the average of the inputs. It poses minimal additional computation and communication costs, requires no alteration of the distributed consensus protocol and promises a highly scalable practical solution for privacy in distributed average consensus. The privacy achieved is quantified using Kullback-Leibler divergence (KL-divergence) and limitations are discussed analytically for two cases; case i) inputs are continuous random variables, and case ii) inputs are discrete random variables.

OBJECTIVE: To develop a one week widening access summer school for 16 year old pupils from non-traditional backgrounds who are considering applying to medical school, and to identify its short term impact and key success factors. Design Action research with partnership schools in deprived inner city areas in five overlapping phases: schools liaison, recruitment of pupils and assessment of needs, programme design, programme delivery, and evaluation. The design phase incorporated findings from one to one interviews with every pupil, and workshops and focus groups for pupils, parents, teachers, medical student assistants, NHS staff, and other stakeholders. An in-depth process evaluation of the summer school was undertaken from the perspective of multiple stakeholders using questionnaires, interviews, focus groups, and observation. Participants 40 pupils aged 16 years from socioeconomically deprived and under-represented ethnic minority groups. RESULTS: The summer school was popular with pupils, parents, teachers, and staff. It substantially raised pupils' confidence and motivation to apply to medical school. Critical success factors were identified as an atmosphere of "respect"; a focus on hands-on work in small groups; the input of medical students as role models; and vision and leadership from senior staff. A particularly popular and effective aspect of the course was a grand round held on the last day, in which pupils gave group presentations of real cases. CONCLUSION: An action research format allowed us to draw the different stakeholders into a collaborative endeavour characterised by enthusiasm, interpersonal support, and mutual respect. The input from pupils to the programme design ensured high engagement and low dropout rates. Hands-on activities in small groups and social drama of preparing and giving a grand round presentation were particularly important.

OBJECTIVE: To determine if the prevalence of 2 prothrombotic genetic factors, factor V Leiden and prothrombin gene mutation, is increased in patients with antiphospholipid (aPL) antibodies with a history of venous/arterial thrombosis compared to patients with aPL antibodies with no history of thrombosis. METHODS: One hundred fifty-seven patients with aPL antibodies were studied. The occurrence of venous and arterial thrombotic events since the time of antibody detection was determined retrospectively, using appropriate clinical and diagnostic criteria. Clinical risk factors for thrombosis were documented and included hypertension, hyperlipidemia, cigarette smoking, diabetes, positive family history, use of oral contraceptive, pregnancy, trauma, hospitalization, varicose veins, and malignancy. Genomic DNA was extracted from blood cells for determination of factor V Leiden mutation G1691 --> A and prothrombin mutation G20210 --> A by polymerase chain reaction and restriction fragment length polymorphism analysis. RESULTS: Of 157 patients, 69 had a history of thrombosis (venous 37, arterial 32); 147 (94%) patients had anticardiolipin (aCL) antibodies; 69 (45%) had lupus anticoagulant (LAC). The prevalence of factor V Leiden in patients with thrombosis was 13% compared to 4.6% in patients without thrombosis (OR 3.11, CI 0.92-10.6). In patients with aCL antibodies, 15% of patients with arterial thrombosis had factor V mutation compared to 3.5% of patients without thrombosis (OR 4.9, CI 1.2-19.3). The prothrombin gene mutation was identified in 5 patients, none of whom had thrombosis. Stepwise logistic regression analysis indicated that LAC (p = 0.005), male sex (p = 0.04), and hypertension (p = 0.03) were the strongest risk factors for developing thrombosis and that no additional risk was conferred by factor V Leiden (p = 0.13) and prothrombin gene mutation. CONCLUSION: Although the prevalence of factor V Leiden is modestly increased in patients with autoimmune aPL antibodies and thrombosis, these results suggest that its detection does not significantly increase the risk of a thrombotic event, once other clinical risk factors have been considered. Prothrombin gene mutation is not associated with thrombosis in patients with aPL antibodies.