Research and development in robotics with potential to automate handling of biological collections

• DOI: 10.3897/rio.6.e61366
• Publication Date: 2020-11-27T08:00:01Z
• Authors: Helen Hardy; Myriam van Walsum; Laurence Livermore; Stephanie Walton
• Keywords: QA75; 0106 biological sciences; Research Infrastructure; 9. Industry and infrastructure; Science; QH; Q; Digitisation; Robotics; HN; N; Natural History Collections; 01 natural sciences; Health and Safety; Automation; 11. Sustainability; Warehousing; RA; Natural Science Collections

This report investigates the current state of physical (mechanical) robotics, automated warehousing approaches and assistive technologies in relation to storage, handling processing (particularly digitisation) natural history collections. Robotics can sound futuristic, however we provide case studies that show many growing examples automation cultural heritage sectors, including barcodes conveyor belts for digitisation; robots handle multiple vials molecular genetic work; use display or exhibition contexts; library We a non-exhaustive example an end workflow retrieval discuss aspects tools challenges relevant these stages. The Distributed System Scientific Collections (DiSSCo), new Research Infrastructure science collections, should build on this, leading future programme pilots develop understanding independent stages, be connected make progress towards end-to-end solutions. Robots, systems, excel at repetitive tasks, are developing rapidly able more complex object types, lower cost. High volume, high variety objects, considerations such as fragility not unique sector - they apply major retail operations collections do offer some extreme challenges, particular replaceable. Increased consistency storage units is likely critical factor enabling future, well looking possibilities when spaces developed built. Engagement with industry subject matter experts has been patchy again recommend DiSSCo help ensure joined up engagement right incentives place, clear communication requirements shared R&D. When examining return investment automation, collections-holding institutions need consider only time cost compared human labour, but wider factors including: health safety environment repetitve strain injury; security; quality outputs; degree criticality response times (e.g. if digitising demand); effective spaces; freeing staff conduct other tasks. Purely software-based outside scope this report, also increasing enormous potential, transform extraction label specimen data scale from images. managing under require combination hardware software approaches.