We are always looking for new challenges and interesting locations to field test robots / gain experience. In the past we’ve helped researchers gather climate change data in remote locations and even helped explore old buildings and historical sites. Our methods are non-destructive and science driven.
Real Robotics Team at the University of Leeds has responded to the COVID-19 pandemic with autonomous robots for on-demand intelligent precision disinfection. The robots, developed by researchers in the Self-Repairing Cities project at the Universities of Leeds, Birmingham, Southampton and UCL, are equipped with onboard sensing and computation power that enables them to navigate, identify targets, and disinfect them. This effort contributes to help in controlling the virus transmission from frequently touched surfaces in public spaces.
The recent COVID-19 outbreak has dramatically influenced our lives. Germs and viruses have always been surrounding us and will continue to exist and evolve. Disinfecting public spaces is undoubtedly essential to control the spread of the virus. Public Health England has recently published coronavirus survival data on surfaces which reports that the virus can survive up to 72 hours on surfaces depending on the type of surface, humidity, and temperature. It takes an infected person to cough or sneeze in his/her hand and touch a surface in public to create a point of infection that can potentially hunt down the next victim touching that surface. That surface, for instance, can be a door handle of a nearby shop or a public bench.
Current disinfection practices of public places usually aim for maximum coverage of spaces. While these practices can help in attenuating the spread of disease, they often lack consistency and accuracy, which can lead to inadequate surface coverage, leaving behind potential infection spots, or over usage of disinfectant that can lead to unnecessarily public exposure to chemicals.
At Real Robotics, we have identified the current challenges, and we decided to put our multidisciplinary team of researchers, engineers, and robots in action. We needed our system to address mobility, modularity, consistency, and accuracy of the disinfection operations in public spaces. To support this effort, we repurposed part of the Self Repairing Cities project that is supported by the Engineering and Physical Sciences Research Council, part of UK Research and Innovation.
In the past ten weeks, our team has tirelessly worked to design and build a smart robotic disinfection system prototypes for precision spray systems. We initially focused on automation to address mobility, to cover multiple spots quickly, and on consistency, to make sure the operation complies with specific standards. We designed and built two systems to serve our goals; the first is based on a ground wheeled robot (HUSKY), and the second is based on a legged robot (LAIKAGO). Both robots are equipped with integrated custom-built pump-spray systems to handle spraying the disinfectant solution. It was then the time to go beyond automation toward robot intelligence and advanced autonomy to address the modularity and accuracy of the disinfection operation. Each robot is equipped with LiDARs, inertial sensors, and visual and depth sensors that enable the development of navigating autonomously, identifying target areas, and spray them as needed ensuring coverage and avoiding overuse of chemicals.
For us to understand the disinfection requirements, we have identified a range of surfaces used or touched in public (hotspots) and study their geometries to optimise disinfection. It is hard to assume specific contact points or angles of contact between people and the used surfaces, which incentivized us to think of the disinfection process as a three-dimensional coverage problem instead of two-dimensional spraying. For spray precision, the multi-nozzle spray module is mounted on a multi-degrees of freedoms robotic manipulator and visual and depth sensors. We are developing detection and tracking of hotspots based on machine learning and compute manipulator-pump trajectories for effective disinfection.
In the past few weeks, we have tested the viability of our systems in the real world. So far, we have run some robot tests and collected data from two locations, Leeds Bradford International Airport and Leeds City Centre, in collaboration with Leeds Bradford Airport and Leeds City Council. The testing helps us further to understand operational challenges and different scenarios of disinfection.
We believe that robots and intelligent systems will play an essential role in public health, and we are eager to contribute to the national and global health efforts to combat COVID-19.
The team involved in this project (alphabetical order) were:
Andy Blight, Bilal Kaddouh, Camilo Gonzalez Arango, Chengxu Zhou, Christopher Peers, Jake Smith, Jason Liu, Jordan Boyle, Liu Yang, Mohmmad Shaqura, Mohammadali Javaheri Koopaee, Moustafa Motawei, Nick Fry, Peter Mooney, Robert Richardson, Tony Wiese, Wissem Haouas
