Combating environmental pollution demands a focus on sustainability, in particular from rapidly advancing technologies that are poised to be ubiquitous in modern societies. Among these, soft robotics promises to replace conventional rigid machines for applications requiring adaptability and dexterity. For key components of soft robots, such as soft actuators, it is thus important to explore sustainable options like bioderived and biodegradable materials. We introduce systematically determined compatible materials systems for the creation of fully biodegradable, high-performance electrohydraulic soft actuators, based on various biodegradable polymer films, ester-based liquid dielectric, and NaCl-infused gelatin hydrogel. We demonstrate that these biodegradable actuators reliably operate up to high electric fields of 200 V/μm, show performance comparable to nonbiodegradable counterparts, and survive more than 100,000 actuation cycles. Furthermore, we build a robotic gripper based on biodegradable soft actuators that is readily compatible with commercial robot arms, encouraging wider use of biodegradable materials systems in soft robotics.

https://www.science.org/doi/pdf/10.1126/sciadv.adf5551?download=true

Biodegradable electrohydraulic actuators for sustainable soft robots

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers’ semantic reasoning and action. Here, we call this process, the recovery of the “language of sonography”. This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques. Additionally, we present the challenges that the scientific community needs to face in the coming years in order to achieve its ultimate goal of developing intelligent robotic sonographer colleagues. These colleagues are expected to be capable of collaborating with human sonographers in dynamic environments to enhance both diagnostic and intraoperative imaging. 

pdf/robotic-ultrasound-imaging-state-of-the-art-and-future-14mobyv4lw.pdf

Robotic ultrasound imaging: State-of-the-art and future perspectives

Human hands are amazingly skilled at recognizing and handling objects of different sizes and shapes. To date, soft robots rarely demonstrate autonomy equivalent to that of humans for fine perception and dexterous operation. Here, an intelligent soft robotic system with autonomous operation and multimodal perception ability is developed by integrating capacitive sensors with triboelectric sensor. With distributed multiple sensors, our robot system can not only sense and memorize multimodal information but also enable an adaptive grasping method for robotic positioning and grasp control, during which the multimodal sensory information can be captured sensitively and fused at feature level for crossmodally recognizing objects, leading to a highly enhanced recognition capability. The proposed system, combining the performance and physical intelligence of biological systems (i.e., self-adaptive behavior and multimodal perception), will greatly advance the integration of soft actuators and robotics in many fields.

Multimodal Sensors Enabled Autonomous Soft Robotic System with Self-Adaptive Manipulation.

Ion gradient induced self-powered flexible pressure sensor

Electrostatic actuators with constant force at low power loss using matched dielectrics

Soft robotic grippers achieve increased versatility and reduced complexity through intelligence embodied in their flexible and conformal structures. The most widely used soft grippers are pneumatically driven; they are simple and effective but require bulky air compressors that limit their application space and external sensors or computationally expensive vision systems for pick verification. In this study, a multi‐material architecture for self‐sensing electrohydraulic bending actuators is presented that enables a new class of highly versatile and reconfigurable soft grippers that are electrically driven and feature capacitive pick verification and object size detection. These electrohydraulic grippers are fast (step input results in finger closure in 50 ms), draw low power (6.5 mW per finger to hold grasp), and can pick a wide variety of objects with simple binary electrical control. Integrated high‐voltage driving electronics are presented that greatly increase the application space of the grippers and make them readily compatible with commercially available robotic arms.

A Soft, Fast and Versatile Electrohydraulic Gripper with Capacitive Object Size Detection

The current crisis surrounding the COVID-19 pandemic demonstrates the amount of responsibility and the workload on our healthcare system and, above all, on the medical staff around the world. In this work, we propose a promising approach to overcome this problem using robot-assisted telediagnostics, which allows medical experts to examine patients from distance. The designed telediagnostic system consists of two robotic arms. Each robot is located at the doctor and patient sites. Such a system enables the doctor to have a direct conversation via telepresence and to examine patients through robot-assisted inspection (guided tactile and audiovisual contact). The proposed bilateral teleoperation system is redundant in terms of teleoperation control algorithms and visual feedback. Specifically, we implemented two main control modes: joint-based and displacement-based teleoperation. The joint-based mode was implemented due to its high transparency and ease of mapping between Leader and Follower whereas the displacement-based is highly flexible in terms of relative pose mapping and null-space control. Tracking tests between Leader and Follower were conducted on our system using both wired and wireless connections. Moreover, our system was tested by seven medical doctors in two experiments. User studies demonstrated the system's usability and it was successfully validated by the medical experts.

/pdf/tactile-robotic-telemedicine-for-safe-remote-diagnostics-in-157386t7.pdf

Tactile Robotic Telemedicine for Safe Remote Diagnostics in Times of Corona: System Design, Feasibility and Usability Study

Introduction The SARS-CoV-2 pandemic has affected global public healthcare for several years. Numerous medical professionals have been infected since the outbreak in 2019, resulting in a shortage of healthcare providers. Since traditional personal protective wear was insufficient to eliminate the virus transmission reliably, new strategies to avoid cross-infection were imperative while enabling high-quality medical care. In the project ProteCT, we investigated the potential of robotic-assisted examination in providing medical examination via a telemedical approach. Material and Methods We constructed a fully functional examination cabin equipped with cameras, microphones, screens and robotic arms to evaluate usability and perception. Therefore, we conducted a preliminary study with 10 healthy volunteers and 10 physicians to gain first insights and optimize the setup. In a second step, we performed telemedical examinations of actual patients from the local emergency department to compare the robotic approach with the classical method of measuring vital signs, auscultation, palpation and percussion. Results The preliminary study identified basic requirements, such as the need for force-feedback and telemedical training for physicians. In the main study, acceptance was high and most patients indicated they would use a telemedical system again. Our setup enabled the physician to make the same diagnoses as by classic examination in the emergency department in most cases. Discussion The potential acceptance of a telemedical system such as ProteCT is high. Robotic telemedical approaches could complement future healthcare beyond the Corona pandemic to reach rural areas or even war zones. Moreover, the daily clinical use of robotic telemedicine could improve patients’ safety, the quality of perioperative management and the workflow in any medical facility. Conclusion The development of telemedical and telerobotic systems is a multidisciplinary and complex challenge. However, acceptance of the proposed system was high among patients and physicians, indicating the potential use of similar systems for future healthcare.

Toward telemedical diagnostics—clinical evaluation of a robotic examination system for emergency patients

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A Soft, Fast and Versatile Electrohydraulic Gripper with Capacitive Object Size Detection

Tactile Robotic Telemedicine for Safe Remote Diagnostics in Times of Corona: System Design, Feasibility and Usability Study

Toward telemedical diagnostics—clinical evaluation of a robotic examination system for emergency patients