Robotic Exploration of an Unknown Nuclear Environment Using Radiation Informed Autonomous Navigation
AuthorsGroves, Keir; orcid: 0000-0002-0763-7069; email: email@example.com
Hernandez, Emili; orcid: 0000-0002-6143-6161; email: firstname.lastname@example.org
West, Andrew; orcid: 0000-0003-4553-8640; email: email@example.com
Wright, Thomas; email: firstname.lastname@example.org
Lennox, Barry; orcid: 0000-0003-0905-8324; email: email@example.com
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AbstractThis paper describes a novel autonomous ground vehicle that is designed for exploring unknown environments which contain sources of ionising radiation, such as might be found in a nuclear disaster site or a legacy nuclear facility. While exploring the environment, it is important that the robot avoids radiation hot spots to minimise breakdowns. Broken down robots present a real problem: they not only cause the mission to fail but they can block access routes for future missions. Until now, such robots have had no autonomous gamma radiation avoidance capabilities. New software algorithms are presented that allow radiation measurements to be converted into a format in which they can be integrated into the robot’s navigation system so that it can actively avoid receiving a high radiation dose during a mission. An unmanned ground vehicle was fitted with a gamma radiation detector and an autonomous navigation package that included the new radiation avoidance software. The full system was evaluated experimentally in a complex semi-structured environment that contained two radiation sources. In the experiment, the robot successfully identified both sources and avoided areas that were found to have high levels of radiation while navigating between user defined waypoints. This advancement in the state-of-the-art has the potential to deliver real benefit to the nuclear industry, in terms of both increased chance of mission success and reduction of the reliance on human operatives to perform tasks in dangerous radiation environments.
CitationRobotics, volume 10, issue 2, page e78
DescriptionFrom MDPI via Jisc Publications Router
History: accepted 2021-05-15, pub-electronic 2021-05-24
Publication status: Published
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Bayesian Reference Analysis for the Generalized Normal Linear Regression ModelTomazella, Vera Lucia Damasceno; orcid: 0000-0002-6780-2089; email: firstname.lastname@example.org; Jesus, Sandra Rêgo; email: email@example.com; Gazon, Amanda Buosi; orcid: 0000-0001-8140-5496; email: firstname.lastname@example.org; Louzada, Francisco; orcid: 0000-0001-7815-9554; email: email@example.com; Nadarajah, Saralees; email: firstname.lastname@example.org; Nascimento, Diego Carvalho; orcid: 0000-0002-3406-4518; email: email@example.com; Rodrigues, Francisco Aparecido; email: firstname.lastname@example.org; Ramos, Pedro Luiz; orcid: 0000-0002-5387-2457; email: email@example.com (MDPI, 2021-05-12)This article proposes the use of the Bayesian reference analysis to estimate the parameters of the generalized normal linear regression model. It is shown that the reference prior led to a proper posterior distribution, while the Jeffreys prior returned an improper one. The inferential purposes were obtained via Markov Chain Monte Carlo (MCMC). Furthermore, diagnostic techniques based on the Kullback–Leibler divergence were used. The proposed method was illustrated using artificial data and real data on the height and diameter of Eucalyptus clones from Brazil.
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Bedtime Oral Hygiene Behaviours, Dietary Habits and Children’s Dental HealthKitsaras, George; orcid: 0000-0002-1631-1730; email: email@example.com; Goodwin, Michaela; orcid: 0000-0002-0375-3118; email: firstname.lastname@example.org; Kelly, Michael P.; orcid: 0000-0002-2029-5841; email: email@example.com; Pretty, Iain A.; email: firstname.lastname@example.org (MDPI, 2021-05-19)Background: Oral hygiene behaviours as well as dietary habits before bed can affect children’s dental health resulting in higher prevalence of dental disease. Dental disease can affect children’s health, development and even school performance. If left untreated, dental disease can progress and it can lead to extractions under general anaesthetic causing further distress for children and families. Consistent and appropriate oral hygiene behaviours and dietary habits can prevent dental diseases from occurring in the first place. Objective: This cross-sectional study examines the relationship between oral hygiene behaviours, dietary habits around bedtime and children’s dental health. Methods: A total of 185 parents with children between the ages of 3 and 7 years from deprived areas participated in the study. Data on bedtime routine activities were collected using an automated text-survey system. Children’s dental health status was established through examination of dental charts and dmft (decayed, missed, filled teeth) scores. Results: In total, 52.4% of parents reported that their children’s teeth were brushed every night. The majority of children (58.9%) had dmft scores over zero. In total, 51 (46.7% of children with dmft score over 0 and 27.5% of all children) children had active decay. The mean dmft score for those experiencing decay was 2.96 (SD = 2.22) with an overall mean dmft score of 1.75 (SD = 2.24). There were significant correlations between frequency of tooth brushing, frequency of snacks/drinks before bed and dmft scores (r = −0.584, p 0.001 and r = 0.547, p = 0.001 respectively). Finally, higher brushing frequency was associated with a lower likelihood of a dmft score greater than 0 (Exp(B) = 0.9). Conclusions: Despite families implementing oral hygiene behaviours as part of their bedtime routines those behaviours varied in their consistency. Results of this study highlight the need for additional studies that consider bedtime routine-related activities and especially the combined effects of oral hygiene practices and dietary habits due to their potentially important relationship with children’s dental health.