Closed-Loop Perching and Spatial Guidance Laws for Bio-Inspired Articulated Wing MAV

This paper presents the underlying theoretical developments and successful experimental demonstrations of perching of an aerial robot. The open-loop lateral-directional dynamics of the robot are inherently unstable because it lacks a vertical tail for agility, similar to birds. A unique feature of this robot is that it uses wing articulation for controlling the flight path angle as well as the heading. New guidance algorithms with guaranteed stability are obtained by rewriting the flight dynamic equations in the spatial domain rather than as functions of time, after which dynamic inversion is employed. It is shown that nonlinear dynamic inversion naturally leads to proportional-integral-derivative (PID) controllers, thereby providing an exact method for tuning the gains. The effectiveness of the proposed bio-inspired robot design and its novel closed-loop perching controller has been successfully demonstrated with perched landings on a human hand

Effectiveness of e-learning in continuing medical education for occupational physicians

Background Within a clinical context e-learning is comparable to traditional approaches of continuing medical education (CME). However, the occupational health context differs and until now the effect of postgraduate e-learning among occupational physicians (OPs) has not been evaluated

A trial of a job-specific workers' health surveillance program for construction workers: study protocol

<p>Abstract</p> <p>Background</p> <p>Dutch construction workers are offered periodic health examinations. This care can be improved by tailoring this workers health surveillance (WHS) to the demands of the job and adjust the preventive actions to the specific health risks of a worker in a particular job. To improve the quality of the WHS for construction workers and stimulate relevant job-specific preventive actions by the occupational physician, we have developed a job-specific WHS. The job-specific WHS consists of modules assessing both physical and psychological requirements. The selected measurement instruments chosen, are based on their appropriateness to measure the workers' capacity and health requirements. They include a questionnaire and biometrical tests, and physical performance tests that measure physical functional capabilities. Furthermore, our job-specific WHS provides occupational physicians with a protocol to increase the worker-behavioural effectiveness of their counselling and to stimulate job-specific preventive actions. The objective of this paper is to describe and clarify our study to evaluate the behavioural effects of this job-specific WHS on workers and occupational physicians.</p> <p>Methods/Design</p> <p>The ongoing study of bricklayers and supervisors is a nonrandomised trial to compare the outcome of an intervention (job-specific WHS) group (n = 206) with that of a control (WHS) group (n = 206). The study includes a three-month follow-up. The primary outcome measure is the proportion of participants who have undertaken one or more of the preventive actions advised by their occupational physician in the three months after attending the WHS. A process evaluation will be carried out to determine context, reach, dose delivered, dose received, fidelity, and satisfaction. The present study is in accordance with the TREND Statement.</p> <p>Discussion</p> <p>This study will allow an evaluation of the behaviour of both the workers and occupational physician regarding the preventive actions undertaken by them within the scope of a job-specific WHS.</p> <p>Trial registration</p> <p><a href="http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3012">NTR3012</a></p

A participatory physical and psychosocial intervention for balancing the demands and resources among industrial workers (PIPPI): study protocol of a cluster-randomized controlled trial

Background: Need for recovery and work ability are strongly associated with high employee turnover, well-being and sickness absence. However, scientific knowledge on effective interventions to improve work ability and decrease need for recovery is scarce. Thus, the present study aims to describe the background, design and protocol of a cluster randomized controlled trial evaluating the effectiveness of an intervention to reduce need for recovery and improve work ability among industrial workers. Methods/Design: A two-year cluster randomized controlled design will be utilized, in which controls will also receive the intervention in year two. More than 400 workers from three companies in Denmark will be aimed to be cluster randomized into intervention and control groups with at least 200 workers (at least 9 work teams) in each group. An organizational resources audit and subsequent action planning workshop will be carried out to map the existing resources and act upon initiatives not functioning as intended. Workshops will be conducted to train leaders and health and safety representatives in supporting and facilitating the intervention activities. Group and individual level participatory visual mapping sessions will be carried out allowing team members to discuss current physical and psychosocial work demands and resources, and develop action plans to minimize strain and if possible, optimize the resources. At all levels, the intervention will be integrated into the existing organization of work schedules. An extensive process and effect evaluation on need for recovery and work ability will be carried out via questionnaires, observations, interviews and organizational data assessed at several time points throughout the intervention period. Discussion: This study primarily aims to develop, implement and evaluate an intervention based on the abovementioned features which may improve the work environment, available resources and health of industrial workers, and hence their need for recovery and work ability

Sick leave and work disability in patients with early arthritis

We studied the occurrence of sick leave and work disability, the presence of workplace adaptations and the usage of professional guidance related to working problems in patients with early arthritis. Inclusion criteria were arthritis symptoms of less than 2 years duration and a paid job at the time of diagnosis. Assessments were done in connection with an early arthritis clinic (EAC) at entry into the cohort and 12 months thereafter by means of a questionnaire comprising questions on sick leave (absenteeism from work reported to the employer), work disability (receiving a full or partial work disability pension), unemployment, work adaptations and professional guidance related to working problems. Fifty-seven of the 69 participants (83%) had an arthritis symptom duration of <6 months. The number of patients with sick leave due to arthritis in the past 12 months decreased from 28 (41%) at study entry to 18 (26%) after 12 months of follow-up. The number of patients receiving a work disability pension increased from 5 (7%) at study entry to 13 (19%) after 12 months of follow-up (10 partial and 3 full). Sick leave in the 12 months before study entry appeared to be the most important predictor of the institution or increase in a work disability pension (odds ratio, 16.1; 95%CI, 1.8–142.8). Between study entry and follow-up, the number of patients with workplace adaptations increased from 20 (29%) to 28 (42%), whereas the number of patients receiving vocational guidance decreased from 48 (70%) to 36 (52%). In patients with early arthritis and a paid job, arthritis-related sick leave was common and occurred in part before patients entered the EAC and a diagnosis was made. About 20% of the patients became permanently work disabled, with partial work disability being more common than full work disability. Considerable proportions of patients received workplace adaptations and professional guidance with working problems

Human Demonstrations for Fast and Safe Exploration in Reinforcement Learning

<p>Reinforcement learning is a promising framework for controlling complex vehicles with a high level of autonomy, since it does not need a dynamic model of the vehicle, and it is able to adapt to changing conditions. When learning from scratch, the performance of a reinforcement learning controller may initially be poor and -for real life applications- unsafe. In this paper the effects of using human demonstrations on the performance of reinforcement learning is investigated, using a combination of offline and online least squares policy iteration. It is found that using the human as an efficient explorer improves learning time and performance for a benchmark reinforcement learning problem. The benefit of the human demonstration is larger for problems where the human can make use of its understanding of the problem to efficiently explore the state space. Applied to a simplified quadrotor slung load drop off problem, the use of human demonstrations reduces the number of crashes during learning. As such, this paper contributes to safer and faster learning for model-free, adaptive control problems.</p