Nuclear decommissioning is a global challenge with high costs associated with it due to the hazardous environments created by radioactive materials. Most nuclear decommissioning sites contain significant amounts of pipework, the majority of which is uncharacterised with regards radioactive contamination. If there is any uncertainty as to the contamination status of a pipe, it must be treated as contaminated waste, which can lead to very high disposal costs. To overcome this challenge, an in-pipe autonomous robot for characterisation is being developed. One of the most significant mechatronic challenges with the development of such a robot is the detection of elbows in the unknown pipe networks to allow the robotic system to autonomously navigate around them. This paper presents a novel method of predicting the direction and radius of the corner using whisker-like sensors. Experiments have shown that the proposed system has a mean error of 4.69 • in the direction estimation.

The inspection of legacy nuclear facilities to aid in decommissioning is a world wide issue. One of the challenges is the characterisation of pipe networks within them. This paper presents an autonomous control system for the navigation of these unknown pipe networks, specifically focusing on elbows. The controller utilises three low-cost feeler sensors to navigate the FURO ii@ robot around 150 mm short elbows. The controller is shown to allow the robot to safely navigate around an elbow on all 39 attempts comparing that with the brute force method which only completed five of the nine attempts and damaging the robot. This shows the advantages of the proposed controller. A new metric (Impulse) is also proposed to compare the extra force applied to the robot over the time it is slipping in the elbow due to the errors in the drive unit speeds. Using this metric, the controller is shown to decrease the Impulse applied to the robot by 213.97 Ns when compared to the brute force method.

We propose a new class of models providing a powerful unification and extension of existing statistical methodology for analysis of data obtained in mixture experiments. These models, which integrate models proposed by Scheffé and Becker, extend considerably the range of mixture component effects that may be described. They become complex when the studied phenomenon requires it, but remain simple whenever possible. This article has supplementary material online.

The inspection of legacy mine workings is a difficult, time consuming, costly task, as traditional methods require multiple boreholes to be drilled to allow sensors to be placed in the voids. Discrete sampling of the void from static locations also means that full coverage of the area cannot be achieved and occluded areas and side tunnels may not be fully mapped. The aim of the Prometheus project is to develop an autonomous robotic solution that is able to inspect the mine workings from a single borehole. This paper presents the challenges of operating autonomous aerial vehicles in such an environment, as well as physically entering the void with an autonomous robot. The paper address how some of these challenges can be overcome with bespoke design and intelligent controllers. It details the design of a reconfigurable UAV that is able to be deployed through a 150 mm borehole and unfold to a tip-to-tip diameter of 780 mm, allowing it to carry a payload suitable for a full autonomous mission.

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