Logic programming for deliberative robotic task planning

Over the last decade, the use of robots in production and daily life has increased. With increasingly complex tasks and interaction in different environments including humans, robots are required a higher level of autonomy for efficient deliberation. Task planning is a key element of deliberation. It combines elementary operations into a structured plan to satisfy a prescribed goal, given specifications on the robot and the environment. In this manuscript, we present a survey on recent advances in the application of logic programming to the problem of task planning. Logic programming offers several advantages compared to other approaches, including greater expressivity and interpretability which may aid in the development of safe and reliable robots. We analyze different planners and their suitability for specific robotic applications, based on expressivity in domain representation, computational efficiency and software implementation. In this way, we support the robotic designer in choosing the best tool for his application.

Surgical data science - from concepts toward clinical translation

Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a new research field that aims to improve the quality of interventional healthcare through the capture, organization, analysis and modeling of data. While an increasing number of data-driven approaches and clinical applications have been studied in the fields of radiological and clinical data science, translational success stories are still lacking in surgery. In this publication, we shed light on the underlying reasons and provide a roadmap for future advances in the field. Based on an international workshop involving leading researchers in the field of SDS, we review current practice, key achievements and initiatives as well as available standards and tools for a number of topics relevant to the field, namely (1) infrastructure for data acquisition, storage and access in the presence of regulatory constraints, (2) data annotation and sharing and (3) data analytics. We further complement this technical perspective with (4) a review of currently available SDS products and the translational progress from academia and (5) a roadmap for faster clinical translation and exploitation of the full potential of SDS, based on an international multi-round Delphi process.

Requirements elicitation for robotic and computer-assisted minimally invasive surgery

The robotic surgical systems and computer-assisted technologies market has seen impressive growth over the last decades, but uptake by end-users is still scarce. The purpose of this article is to provide a comprehensive and informed list of the end-user requirements for the development of new generation robot- and computer-assisted surgical systems and the methodology for eliciting them. The requirements were elicited, in the frame of the EU project SMARTsurg, by conducting interviews on use cases of chosen urology, cardiovascular and orthopaedics procedures, tailored to provide clinical foundations for scientific and technical developments. The structured interviews resulted in detailed requirement specifications which are ranked according to their priorities. Paradigmatic surgical scenarios support the use cases.

Toward a standard ontology of surgical process models

PURPOSE

The development of common ontologies has recently been identified as one of the key challenges in the emerging field of surgical data science (SDS). However, past and existing initiatives in the domain of surgery have mainly been focussing on individual groups and failed to achieve widespread international acceptance by the research community. To address this challenge, the authors of this paper launched a European initiative-OntoSPM Collaborative Action-with the goal of establishing a framework for joint development of ontologies in the field of SDS. This manuscript summarizes the goals and the current status of the international initiative.

METHODS

A workshop was organized in 2016, gathering the main European research groups having experience in developing and using ontologies in this domain. It led to the conclusion that a common ontology for surgical process models (SPM) was absolutely needed, and that the existing OntoSPM ontology could provide a good starting point toward the collaborative design and promotion of common, standard ontologies on SPM.

RESULTS

The workshop led to the OntoSPM Collaborative Action-launched in mid-2016-with the objective to develop, maintain and promote the use of common ontologies of SPM relevant to the whole domain of SDS. The fundamental concept, the architecture, the management and curation of the common ontology have been established, making it ready for wider public use.

CONCLUSION

The OntoSPM Collaborative Action has been in operation for 24 months, with a growing dedicated membership. Its main result is a modular ontology, undergoing constant updates and extensions, based on the experts' suggestions. It remains an open collaborative action, which always welcomes new contributors and applications.

Toward a Knowledge-Driven Context-Aware System for Surgical Assistance

Complex surgeries complications are increasing, thus making an efficient surgical assistance is a real need. In this work, an ontology-based context-aware system was developed for surgical training/assistance during Thoracentesis by using image processing and semantic technologies. We evaluated the Thoracentesis ontology and implemented a paradigmatic test scenario to check the efficacy of the system by recognizing contextual information, e.g. the presence of surgical instruments on the table. The framework was able to retrieve contextual information about current surgical activity along with information on the need or presence of a surgical instrument.