The Biomedical Engineering Laboratory of the School of Electrical and Computer Engineering of the NTUA participates in ENDORSE, a European funded, Horizon 2020-MSCA-RISE Project.
The overall objective of ENDORSE is to develop and validate a safe, efficient and integrated indoor robotic fleet for logistic applications in healthcare and commercial spaces.
Commercial indoor spaces such as hospitals, hotels and offices offer great potential for commercial exploitation of logistic robotics. Also, offer advantages for their deployment, since they are required by law to meet stringent building codes, and therefore the navigation space exhibits some structure. In addition, they offer reliable communications infrastructure, since this is required for normal business operation. Thus, commercial spaces are rightfully considered the next great field of logistic robotics deployment. Despite these advantages, today, few solutions exist, and these solutions do not trigger widespread acceptance by the market. This is because existing systems require costly infrastructure installation (arrays of peripheral sensors, mapping, etc.); they do not easily integrate to corporate IT solutions and as a result, they do not fully automate procedures and traceability; they are limited to a single type of service, i.e. transfer of goods.
Through transfer of knowledge, multidisciplinary research and cross-fertilization between academia and industry, ENDORSE will address the aforementioned technical hurdles. Four innovation pillars will be pursued:
(i) infrastructure-less multi-robot navigation, i.e. minimum (if any) installation of sensors and communications buses inside the building for the localization of robots, targets and docking stations;
(ii) advanced HRI for resolving deadlocks and achieving efficient sharing of space resources in crowded spaces;
(iii) deployment of the ENDORSE software as a cloud-based service facilitating its integration with corporate software solutions such as ERP, CRM, etc.;
(iv) reconfigurable and modular hardware architectures so that diverse modules can be easily swapped. The latter will be demonstrated and validated by the integration of an e-diagnostic support module (equipped with non-invasive sensors/devices) and the Electronic Health Records (EHR) interfacing, which will serve as an e-diagnostic mobile station.
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