Recycling automotive, electronic and other end-oflife waste liberates large quantities of metals which can be returned to the supply chain. Sorting the non-ferrous metals however, is not straightforward. Common methods range from laborious hand-sorting to expensive and environmentally deleterious wet processes. The goal is to move towards dry processes, such as induction sensors and vision systems, which can identify and sort non-ferrous scrap efficiently and economically.In this paper, we present a new classification method using magnetic induction spectroscopy (MIS) to sort three high-value metals that make up the majority of the non-ferrous fractioncopper, aluminium and brass. Two approaches are investigated: The first uses MIS with a set of geometric features returned by a vision system, where metal fragments are matched to known test pieces from a training set. The second approach uses MIS only. A surprisingly effective classifier can be constructed by combining the MIS frequency components in a manner determined by how eddy currents circulate in the metal fragment. An average precision and recall (purity and recovery rate) of around 92% was shown. This has significant industrial relevance, as the MIS-only classifier is simple, scalable, and straightforward to implement on existing commercial sorting lines.

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Biological tissues have a complex-impedance, or bio-impedance, profile which changes with respect to frequency. This is caused by dispersion mechanisms which govern how the electromagnetic field interacts with the tissue at the cellular and molecular level. Measuring the bio-impedance spectra of a biological sample can potentially provide insight into the sample's properties and its cellular structure. This has obvious applications in the medical, pharmaceutical and food-based industrial domains. However, measuring the bio-impedance spectra non-destructively and in a way which is practical at an industrial-scale presents substantial challenges. The low-conductivity of the sample requires a highly sensitive instrument, while the demands of industrialscale operation require a fast high-throughput sensor of rugged design. In this paper, we describe a multi-frequency magnetic induction spectroscopy (MIS) system suitable for industrial-scale, non-contact, spectroscopic bioimpedance measurement over a bandwidth of 156 kHz-2.5 MHz. The system sensitivity and performance are investigated using calibration and known reference samples. It is is shown to yield rapid and consistently sensitive results with good long-term stability. The system is then used to obtain conductivity spectra of a number biological test samples, including yeast suspensions of varying concentration and a range of agricultural produce, such as apples, pears, nectarines, kiwis, potatoes, oranges and tomatoes.

The magnetic dipole polarizability tensor of a metallic object gives unique information about the size, shape and electromagnetic properties of the object. In this paper, we present a novel method of coin characterization based on the spectroscopic response of the absolute tensor. The experimental measurements are validated using a combination of tests with a small set of bespoke coin surrogates and simulated data. The method is applied to an uncirculated set of US coins. Measured and simulated spectroscopic tensor responses of the coins show significant differences between different coin denominations. The presented results are encouraging as they strongly demonstrate the ability to characterize coins using an absolute tensor approach.

SUMMARYSurgical robotics is a growing discipline, continuously expanding with an influx of new ideas and research. However, it is important that the development of new devices take account of past mistakes and successes. A structured approach is necessary, as with proliferation of such research, there is a danger that these lessons will be obscured, resulting in the repetition of mistakes and wasted effort and energy. There are several research paths for surgical robotics, each with different risks and opportunities and different methodologies to reach a profitable outcome. The main emphasis of this paper is on a methodology for 'applied research' in surgical robotics. The methodology sets out a hierarchy of criteria consisting of three tiers, with the most important being the bottom tier and the least being the top tier. It is argued that a robotic system must adhere to these criteria in order to achieve acceptability. Recent commercial systems are reviewed against these criteria, and are found to conform up to at least the bottom and intermediate tiers, the most important first two tiers, and thus gain some acceptability. However, the lack of conformity to the criteria in the top tier, and the inability to conclusively prove increased clinical benefit, is shown to be hampering their potential in gaining wide establishment.