The innovative research project aspires to develop sensors that provide enhanced capabilities to robots, helping improve their motor skills and dexterity, through the use of highly accurate pressure sensors that provide haptic feedback and distributed touch. It is led by the University of the West of Scotland (UWS), Integrated Graphene Ltd, and supported by the Scottish Research Partnership in Engineering (SRPe) and the National Manufacturing Institute for Scotland (NMIS) Industry Doctorate Programme in Advanced Manufacturing.

The innovative research project aspires to develop sensors that provide enhanced capabilities to robots, helping improve their motor skills and dexterity, through the use of highly accurate pressure sensors that provide haptic feedback and distributed touch. It is led by the University of the West of Scotland (UWS), Integrated Graphene Ltd, and supported by the Scottish Research Partnership in Engineering (SRPe) and the National Manufacturing Institute for Scotland (NMIS) Industry Doctorate Programme in Advanced Manufacturing.

Professor Des Gibson, Director of the Institute of Thin Films, Sensors and Imaging at UWS and project principal investigator, said: “Over recent years the advancements in the robotics industry have been remarkable, however, due to a lack of sensory capabilities, robotic systems often fail to execute certain tasks easily. For robots to reach their full potential, accurate pressure sensors, capable of providing greater tactile ability, are required.

“Our collaboration with Integrated Graphene Ltd, has led to the development of advanced pressure sensor technology, which could help transform robotic systems.”

Made from 3D graphene foam, which offers unique properties when put under mechanical stress, the sensors use a piezoresistive approach. This means that when the material is put under pressure it dynamically changes its electric resistance, easily detecting and adapting to the range of pressure required, from light to heavy.

Marco Caffio, co-founder and Chief Scientific Officer at Integrated Graphene said: “Gii, our novel 3D graphene foam, has the capability to mimic the sensitivity and feedback of human touch, which could have a transformative impact on how robotics can be used for a whole range of real-world applications from surgery to precision manufacturing.

“We know the unique property of Gii makes it suitable for use in other applications like disease diagnostics and energy storage, so we’re always very excited to be able to demonstrate its flexibility in projects like this one.”

Dr. Carlos Garcia Nunez, School of Computing Engineering and Physical Sciences at UWS added: “Within robotics and wearable electronics the use of pressure sensors is a vital element, to provide either an information input system, or to give robotic systems human-like motor skills. An advanced material like 3D graphene foam offers excellent potential for use in such applications, due to its outstanding electrical, mechanical, and chemical properties.

“Our work shines a light on the significant potential for this technology to revolutionize the robotics industry with dynamic pressure sensors.”

Claire Ordoyno, Interim Director of SRPe, stated: “The SRPe – NMIS Industrial Doctorate Programme brings together groundbreaking academic research with industry partners to drive forward innovation in engineering. These collaborative PhD projects not only enhance the Scottish engineering research landscape, but produce innovation focussed, industry-ready PhD graduates to feed the talent pipeline.”

The next stage of the project – funded by UWS, Integrated Graphene Ltd, SRPe and NMIS – will look to further increase sensitivity of the sensors, before developing for wider use in robotic systems.

Reference: “Ultra-Thin Graphene Foam Based Flexible Piezoresistive Pressure Sensors for Robotics” by Connor I. Douglas, Carlos Garcia Nuñez, Marco Caffio and Des Gibson, June 2022, Key Engineering Materials. DOI: 10.4028/p-oy94hj

"Our findings show that we can automate one of the most intricate and delicate tasks in surgery: the reconnection of two ends of an intestine. The STAR performed the procedure in four animals and it produced significantly better results than humans performing the same procedure," said senior author Axel Krieger, an assistant professor of mechanical engineering at Johns Hopkins' Whiting School of Engineering.

The robot excelled at intestinal anastomosis, a procedure that requires a high level of repetitive motion and precision. Connecting two ends of an intestine is arguably the most challenging step in gastrointestinal surgery, requiring a surgeon to suture with high accuracy and consistency. Even the slightest hand tremor or misplaced stitch can result in a leak that could have catastrophic complications for the patient

Working with collaborators at the Children's National Hospital in Washington, D.C. and Jin Kang, a Johns Hopkins professor of electrical and computer engineering, Krieger helped create the robot, a vision-guided system designed specifically to suture soft tissue. Their current iteration advances a 2016 model that repaired a pig's intestines accurately, but required a large incision to access the intestine and more guidance from humans.

The team equipped the STAR with new features for enhanced autonomy and improved surgical precision, including specialized suturing tools and state-of-the art imaging systems that provide more accurate visualizations of the surgical field.

Soft-tissue surgery is especially hard for robots because of its unpredictability, forcing them to be able to adapt quickly to handle unexpected obstacles, Krieger said. The STAR has a novel control system that can adjust the surgical plan in real time, just as a human surgeon would.

"What makes the STAR special is that it is the first robotic system to plan, adapt, and execute a surgical plan in soft tissue with minimal human intervention," Krieger said. A structural-light based three-dimensional endoscope and machine learning-based tracking algorithm developed by Kang and his students guides STAR. "We believe an advanced three-dimensional machine vision system is essential in making intelligent surgical robots smarter and safer," Kang said. .

As the medical field moves towards more laparoscopic approaches for surgeries, it will be important to have an automated robotic system designed for such procedures to assist, Krieger said.

"Robotic anastomosis is one way to ensure that surgical tasks that require high precision and repeatability can be performed with more accuracy and precision in every patient independent of surgeon skill," Krieger said. "We hypothesize that this will result in a democratized surgical approach to patient care with more predictable and consistent patient outcomes."