The emergence of technologies such as cloud computing and artificial intelligence (AI) is expected to drive innovation in the medical robotics segment thereby reducing the need for the surgeon to be physically present.
Robotics technologies are expected to help in improving the quality of life for elderly patients through non-invasive surgical procedures.
Listed below are the technology trends impacting the Robotics in Medical (2021) theme, as identified by GlobalData.
AI
AI technologies, most notably machine learning, are integral to the development of intelligent industrial robots, which can anticipate and adapt to certain situations based on the interpretation of data derived from an array of sensors. Further advances are needed in certain AI technologies, including computer vision, conversational platforms, and context aware computing, to take industrial automation and industrial robotics to the next level.
Neuromorphic processors will become an important part of the next generation of robots. They are trained using basic libraries of relevant data and then taught to think for themselves by processing sensory inputs. These processors will eventually use their acquired skills to perform assigned duties using associations and probabilities.
Edge computing
Robotic operations can be performed from the cloud, however, security and latency issues may require robots to process real-time data about their operational environments and respond immediately. Edge computing has the potential to improve the performance of robots due to lower latency. It also improves security as the edge is safer than the cloud. Edge computing will make cyberattacks more difficult when combined with robotics’ self-contained “sense-decide act” firmware loops.
Cybersecurity
One of the major challenges to the widespread implementation of robots is the threat of cyberattacks. Robots, especially those that are internet-connected, are highly vulnerable to hacking. Leaving them unprotected may allow unauthorised access to key applications and systems, which in turn may lead to loss, theft, destruction, or inappropriate use of sensitive information.
The latest industrial cybersecurity management solutions address the risks associated with industrial automation equipment, applications, and plants. These solutions enable enterprises to comply with industry-specific cybersecurity regulations, such as the North American Electric Reliability Corporation Critical Infrastructure Protection (NERC CIP). Organisations can combine IT and operational technology (OT) security efforts and maximise the potential of all corporate cybersecurity resources by including these cybersecurity management solutions in their security strategy.
Industrial Internet
The Industrial Internet implies a greater degree of interconnection between systems and assumes that the monitoring and control data will flow beyond the boundaries of the factory to be consumed and managed by cloud-based services. Existing factories, machines, and processes represent the primary opportunity for the Industrial Internet.
The biggest short-term gains will come from retrofitting advanced communications and management functionality to today’s industrial infrastructure. Giving industrial machinery manufacturers the ability to access real-time performance data should allow them to offer new services and support new business models such as pre-emptive maintenance or robotics as a service (RaaS).
Cloud robotics
Advances in AI have enabled the development of robots, allowing them to become highly complex products rather than the stand-alone, fixed-function machines they used to be, which has increased the number of roles that robots can perform. Central to this development has been cloud computing, which allows sensing, computation, and memory to be managed more rapidly, securely, and at scale.
The use of cloud within robotics has the potential to change the way that the technology is consumed. The RaaS market includes products that integrate cloud-based management and analytics services with physical robots. The leading robot manufacturers have implemented cloud connectivity, enabling robots to be monitored, managed, and maintained remotely.
Robotics centres of excellence (CoEs)
A robotics CoE is responsible for developing and implementing robotic solutions that are efficient, productive, and responsive to the needs of industries. The CoE gathers, assesses, and manages the information that eases the deployment of robotic solutions. A robotics CoE needs the right mix of people, including a sponsor, a lead, a project manager, business analysts, architects, developers, and controllers, in addition to a strong governance model.
A CoE is established to maintain existing organisational dynamics and sustain current and future initiatives to implement robotics. Precision is vital in industries such as healthcare as patients’ lives are at stake. Several medical facilities in the US have established robotic surgery CoEs to ensure that patient safety and care quality standards are met.
Open process automation (OPA)
Traditionally, robotic components such as controllers were only compatible with products made by the same company. Various organisations are striving to break free from these limitations and establish an open system that would make robotic components universally compatible, which has led to the development of OPA.
The advent of OPA will make process controls more interoperable. It allows technology vendors to work collaboratively with various organisations to produce standard, secure, and open architecture that can ease robotic integration, giving rise to vendor-neutral solutions.
Lightweight design robotics and doing less with more
The robots of the 2020s will be smaller and lighter, which will make them more flexible, easier to deploy, and more cost-efficient. The trend towards lightweight design applies to both the bodies and the brains of robots. Several companies are investing in optimised operation systems, software, and programming.
Academia is also developing solutions for some of the most complex problems, such as trajectory simplification, which aims to make robots better at navigating their environment. Research into trajectory simplification balances the need for robots to make correct decisions even when information is scarce.
Customisable robots
Robots have become prevalent across different industries, but designing, and modelling a robot is tedious, cumbersome, and expensive. Moreover, accommodating a minor change or modification at a later stage can further prolong this process. In response, manufacturers are attempting to create robot prototypes that can be customised.
Soft and self-healing robots
Soft robots are made of soft materials or polymers instead of conventional metal. These materials give robots organic characteristics, replicating the way muscles work. Research is ongoing on enabling them to self-repair, which would make them more flexible and adaptable. Self-healing robots are still in their infancy, but research is likely to improve the technology. Currently, that research is mainly going into improving materials and devising ways for different materials to be compatible to avoid any chemical reaction. There are multiple potential use cases in healthcare, manufacturing, and defence and security for such robots.
This is an edited extract from the Robotics in Medical Devices, 2021 Update – Thematic Research report produced by GlobalData Thematic Research.
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