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

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

Expanding wavefront frontier detection: An approach for efficiently detecting frontier cells

Frontier detection is a key step in many robot exploration algorithms. The more quickly frontiers can be detected, the more efficiently and rapidly exploration can be completed. This paper proposes a new frontier detection algorithm called Expanding Wavefront Frontier Detection (EWFD), which uses the frontier cells from the previous timestep as a starting point for detecting the frontiers in the current timestep. As an alternative to simply comparing against the naive frontier detection approach of evaluating all cells in a map, a new benchmark algorithm for frontier detection is also presented, called Naive Active Area frontier detection, which operates in bounded constant time. EWFD and NaiveAA are evaluated in simulations and the results compared against existing state-of-the-art frontier detection algorithms, such as Wavefront Frontier Detection and Incremental-Wavefront Frontier Detection

Efficient neighbourhood-based information gain approach for exploration of complex 3D environments

This paper presents an approach for exploring a complex 3D environment with a sensor mounted on the end effector of a robot manipulator. In contrast to many current approaches which plan as far ahead as possible using as much environment information as is available, our approach considers only a small set of poses (vector of joint angles) neighbouring the robot's current pose in configuration space. Our approach is compared to an existing exploration strategy for a similar robot. Our results demonstrate a significant decrease in the number of information gain estimation calculations that need to be performed, while still gathering an equivalent or increased amount of information about the environment. © 2013 IEEE

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

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

Climbing Robot for Steel Bridge Inspection: Design Challenges

Inspection of bridges often requires high risk operations such as working at heights, in confined spaces, in hazardous environments; or sites inaccessible by humans. There is significant motivation for robotic solutions which can carry out these inspection tasks. When inspection robots are deployed in real world inspection scenarios, it is inevitable that unforeseen challenges will be encountered. Since 2011, the New South Wales Roads & Maritime Services and the Centre of Excellence for Autonomous Systems at the University of Technology, Sydney, have been working together to develop an innovative climbing robot to inspect high risk locations on the Sydney Harbour Bridge. Many engineering challenges have been faced throughout the development of several prototype climbing robots, and through field trials in the archways of the Sydney Harbour Bridge. This paper will highlight some of the key challenges faced in designing a climbing robot for inspection, and then present an inchworm inspired robot which addresses many of these challenges