The Rise of Massage and Medical Gymnastics in London and Paris before the First World War.

Massage and medical gymnastics experienced a rapid institutionalization across Europe and North America between 1850 and 1914. This article explores how this process took place in London and Paris. Physiotherapy developed many of the hallmarks of an independent discipline during this period, including an identified corpus of manipulations and exercises, some autonomous training courses and degrees for future practitioners, and even the creation of departments within several hospitals. The article analyzes all of the processes surrounding this rise, paying special attention to the influence of the ambassadors of Swedish gymnastics (which led to the re-invention of massage across Europe), to the installation of physiotherapy in hospitals in London and in Paris, and to the practical and institutional innovations driven by nurses in England and by doctors in France

Saturn S-IB Stage assembly and test report, S-IB-1

Manufacture, assembly, and static tests of Saturn S-IB-1 stag

Experimental Evaluation of Nearest Neighbor Exploration Approach in Field Environments

© 2017 IEEE. Inspecting surface conditions in 3-D environments such as steel bridges is a complex, time-consuming, and often hazardous undertaking that is an essential part of tasks such as bridge maintenance. Developing an autonomous exploration strategy for a mobile climbing robot would allow for such tasks to be completed more quickly and more safely than is possible with human inspectors. The exploration strategy tested in this paper, called the nearest neighbors exploration approach (NNEA), aims to reduce the overall exploration time by reducing the number of sensor position evaluations that need to be performed. NNEA achieves this by first considering at each time step only a small set of poses near to the current robot as candidates for the next best view. This approach is compared with another exploration strategy for similar robots performing the same task. The improvements between the new and previous strategy are demonstrated through trials on a test rig, and also in field trials on a ferromagnetic bridge structure. Note to Practitioners-This paper was motivated by the problem of inspecting confined spaces for rust and flaking paint with a manipulator robot arm. Existing approaches involve creating a large set of candidate robot poses to take a scan from. Evaluating all these candidate poses is very time consuming if full coverage is guaranteed. This paper suggests a principled method for restricting the size of this set in a way that does not reduce inspection coverage but decreases overall time taken for inspection

A sliding window approach to exploration for 3D map building using a biologically inspired bridge inspection robot

© 2015 IEEE. This paper presents a Sliding Window approach to viewpoint selection when exploring an environment using a RGB-D sensor mounted to the end-effector of an inchworm climbing robot for inspecting areas inside steel bridge archways which cannot be easily accessed by workers. The proposed exploration approach uses a kinematic chain robot model and information theory-based next best view calculations to predict poses which are safe and are able to reduce the information remaining in an environment. At each exploration step, a viewpoint is selected by analysing the Pareto efficiency of the predicted information gain and the required movement for a set of candidate poses. In contrast to previous approaches, a sliding window is used to determine candidate poses so as to avoid the costly operation of assessing the set of candidates in its entirety. Experimental results in simulation and on a prototype climbing robot platform show the approach requires fewer gain calculations and less robot movement, and therefore is more efficient than other approaches when exploring a complex 3D steel bridge structure

Key feature-based approach for efficient exploration of structured environments

© 2015 IEEE. This paper presents an exploration approach for robots to determine sensing actions that facilitate the building of surface maps of structured partially-known environments. This approach uses prior knowledge about key environmental features to rapidly generate an estimate of the rest of the environment. Specifically, in order to quickly detect key features, partial surface patches are used in combination with pose optimisation to select a pose from a set of nearest neighbourhood candidates, from which to make an observation of the surroundings. This paper enables the robot to greedily search through a sequence of nearest neighbour poses in configuration space, then converge upon poses from which key features can best be observed. The approach is experimentally evaluated and found to result in significantly fewer exploration steps compared to alternative approaches