How blockchain technology could power robotic systems for industry 4.0

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Athlone IT’s Dr Saeed Hamood Alsamhi is investigating the feasibility of applying blockchain technology to robotic systems, which could be used in areas ranging from intelligent manufacturing to disaster monitoring.

Dr Saeed Hamood Alsamhi went around the world on a research journey that took him into the areas of blockchain and robotics. He began studying engineering at Ibb University in Yemen, before earning his master’s and doctoral degrees from the Indian Institute of Technology. He later went to China for a postdoc position at Tsinghua University and became an assistant professor at the Shenzhen Institute of Advanced Technology.

Alsamhi is currently a Marie Sklodowska-Curie Actions Fellow at Confirm, Science Foundation Ireland’s research center for intelligent manufacturing, based at Athlone IT. His research interests include blockchain technology, multi-robot collaboration, digital twins, space technologies, internet of things and green communication.

‘Multi-robot systems have broad application scenarios, especially in hazardous, unknown or hazardous environments’- DR SAEED HAMOOD ALSAMHI

What prompted you to become a researcher?

Growing up, I enjoyed asking how advanced technologies will improve our quality of life and change our world to be smarter and greener. My research interest began during my masters degree at the Indian Institute of Technology in Varanasi, India. It was my first time writing an article and when I attended an international conference, many attendees asked questions and appreciated my proposed idea. This has allowed me to do more research in advanced technologies and applications.

I continued my research with my PhD in Space Technology. Before finishing my PhD, I received a message from Prof Ou Ma at the Tsinghua University School of Aerospace Engineering in Beijing, China. He invited me to work with him as a postdoc in the area of ​​research on optimal and intelligent wireless networks and its applications to improve robotics technologies. I checked the Tsinghua University degree and found it was the 17th in the world. This news made my day beautiful.

Can you tell us about the research you are currently working on?

My research at the moment focuses on multi-robot collaboration to reach consensus while executing activities in industry, or outside of industry, with the help of blockchain technology. The project aims to develop a decentralized ledger platform with corresponding algorithms to enable heterogeneous robot collaborations with network partition tolerance and Byzantine robots or untrusted robots.

The project will investigate the constraints and characteristics of realistic robotic collaboration applications to develop consensus algorithms for robotics-oriented blockchain systems. The chosen robotic applications will be implemented on top of the blockchain system, for example the best-of-n problem, which is an abstraction of the problem of achieving discrete consensus.

Why do you think your research is important?

All the research work is important, but I think the work I am doing is important because we are trying to study realistic heterogeneous robot collaboration applications with high security levels in a decentralized way using blockchain technology.

This could help manage heterogeneous multi-robots in smart factories in Ireland and the EU, accomplishing complex tasks effectively and efficiently, and improving productivity in a way that a single robot cannot. Additionally, multi-robot collaboration is needed for disaster management to respond and effectively mitigate potential adverse effects.

Additionally, robots can be used to monitor and combat Covid-19 and future pandemics. Autonomous robotic collaboration can provide services, goods and medicines anywhere: during Covid-19, robots delivered items to quarantine areas and carried out activities in hospitals without human intervention.

I have already published two articles in magazines about it: Blockchain for decentralized multi-drone to fight Covid-19 and future pandemics: Framework and proposed solutions and multi-robot collaboration enhanced by Blockchain to fight Covid-19 and future pandemics.

What commercial applications do you envisage for your research?

The development of decentralized robotic collaboration could accelerate the adoption of multi-robot systems in industries. There are several commercial applications in the intelligent manufacturing of multi-robot collaboration, such as the handling and transportation of objects, natural resource monitoring, and delivery operations.

Commercial applications include disaster monitoring and management, emergency response and rescue, repair and fault diagnosis for outdoor sector operations. Furthermore, in the health sector, multi-robot collaboration can be used to avoid human interaction and to fight and monitor pandemics, such as Covid-19.

Multi-robot systems have broad application scenarios, especially in hazardous, unknown or hazardous environments, such as humanitarian demining, search and rescue, exploration or underwater surveillance.

What are some of the biggest challenges you face as a researcher in your field?

My current research is at a very early stage. The goal is to verify the feasibility of applying blockchain technology in robotic systems. The results so far are positive, but there are many challenges.

Most solutions require each robot to process transactions and store the world state [a database that holds current values of a set of ledger states] similarly, just like normal blockchain systems do. But these solutions are difficult to manage with heterogeneous capacities and network partitions.

What are some of the research areas you would like to see addressed in the years to come?

With the advancement of communication technology such as Beyond 5G and 6G integrated with blockchain and federated learning, multi-robot collaboration in Industry 4.0 could solve real world challenges, improve process flexibility with productivity, improve decision making and action performance and response in real time.

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