Cleft lip and palate (CLP) is a prevalent congenital disorder that impacts children globally. Despite recent advances in understanding CLP aetiology and improvements in surgical interventions and therapies, CLP still results in significant physical, psychological, and societal obstacles for affected children. This study presents a review of the predominant issues that affect children with CLP in the domains of speech, social interaction, hearing, and feeding, revealing speech-related challenges as the most significant factors for children with CLP. A systematic review analysing articles published in Scopus and Web of Science pertaining to robotics and machine learning in the context of CLP is presented following PRISMA guidelines, suggesting the potential for artificial intelligence AI and robots as an aid in speech and language therapy. While existing robot speech production assistants have shown promise in supporting CLP children, research in this area still needs to be completed. In response to these challenges, findings from the systematic literature review were utilised to develop a model for a dedicated speech therapy assistant robot to be used during therapy sessions. Future investigations will seek to ascertain the feasibility of incorporating this model into speech and language therapy sessions for children affected by CLP in partnering clinics in the UK.
The use of robots in the health system is inevitable and covers many fields and scopes. Therefore, their organization and categorization are very important. However, the current classification of robots in the healthcare sector lacks coherence and consistency, leading to a fragmented understanding of their roles and capabilities. To address these issues, this review paper proposes a new classification based on healthcare processes and the intrinsic properties of robotic devices, such as minimally robotic manipulators, autonomous mobile robots, cobots, and artificial intelligence (AI)-based software. Existing classifications often conflate established robots, experimental prototypes, and hypothetical concepts, creating a disorganized view of healthcare system robotics. Laboratory robots, notably absent from many classifications, further highlight the inconsistencies. Despite the promising advancements, the lack of a systematic classification obscures the trends in this dynamic field. A comprehensive classification system for healthcare robots would help developers navigate complex regulations, identify relevant standards, and streamline the commercialization of robotic products. This would enable quicker development and market entry while ensuring compliance with safety and quality standards.
This review proposes an analysis of the scientific challenges of Soft Miniaturized Robots, providing a map of the recent works in this emerging field. The advent of precision 3D microprinting technologies enabling to build microstructures and micro-actuators based on soft polymers has opened a way to the development of soft miniaturized robotics in several fields: (i) some swimming soft microrobots actuated with an external field enable to explore high small channel for in vitro or in vivo applications; (ii) miniaturized soft robot based on artificial muscles find applications in in vivo exploration or in dexterous micromanipulation. Placing at the crossroads of small-scale robotics and soft robotics, miniaturized soft robots have their own scientific paradigm, which we describe in this article. It requires to develop methods and technologies to design, actuate and fabricate this new type of miniature robots. The intrinsic nonlinear behavior of these robots requires advanced methods to model and control them.
Purpose of review In this review, we briefly summarize the numerical methods commonly used for the nonlinear dynamic analysis of soft robotic systems. The underlying mechanical principles as well as the geometrical treatment tailored for soft robots are introduced with particular emphasis on one-dimensional models. Additionally, the review encompasses three-dimensional frameworks, available simulation packages, and various types of interaction models, shedding light on the design, actuation, motion control, and internal and external forces of soft robots. Recent findings Reduced-order models can offer high efficiency in characterizing nonlinear deformations, allowing convenient tailoring based on specific structural and material configurations. For pursuing high simulation accuracy and detailed mechanics, the finite element method proves to be a valuable tool through numerous off-the-shelf platforms. Furthermore, machine learning has emerged as a promising tool to effectively address the challenges within the mechanics community. Summary A wide range of kinematic and dynamic numerical models is available for simulating the behaviors of soft robots, offering exceptional adaptability to different geometries and structures based on existing modeling theories and numerical solution algorithms. However, the trade-off between computational complexity and simulation accuracy remains a challenge in achieving fast, accurate, and robust control of soft robots in complex environments.
Purpose of Review: Distributed ledger technologies (DLTs), particularly blockchain, are paving the way to securing and managing distributed and large-scale systems of autonomous agents. We look into how these technologies are moving out of the lab and into the real world within the robotics field. Recent Findings: Despite the scalability and real-world applicability concerns, new solutions have emerged that show resilience to intermittent connectivity, as well as scalable solutions for managed or permissioned networks. Summary: We present a review on the various use cases that different DLTs can support in multi-robot systems. We argue that the majority of the work to date on open and permissionless blockchains is only applicable to a subset of robotics use cases, with novel DLT architectures and permissioned blockchains driving adoption across industrial and more mature application scenarios.
