Editorial Feature

Potential Applications of Quantum Computing in Robotics

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Quantum computing has the potential to drastically increase the processing power available to the field of robotics. This drastic increase in processing power will have numerous – and even some unforeseeable – applications, and could bring about a future in which autonomous robots are safely supporting human society in enormous cities, taking over hazardous and unpleasant menial and industrial tasks, and helping to tackle climate change.

Quantum Computing and Quantum Supremacy

Quantum computing exploits the peculiar mechanics of quantum (or smallest possible interacting) particles to create computer architecture that is potentially exponentially faster than the binary logic-based classical computing systems we use today. In quantum computing, qubits are derived through the manipulation of individual particles. A qubit is a unit of information that, unlike a binary unit (bit) used in classical computing architecture, can exist in a superposition of two states at once. This means that quantum computers can perform simultaneous processing tasks, and exploiting other aspects of quantum mechanics makes them even faster.

The theoretical future state in which a quantum computer can perform any task faster, more accurately or more reliably than a conventional classical computer is referred to as “quantum supremacy”. This is not yet a reality, but with government agencies, research departments and the biggest technology companies in the world today (including Google, IBM, and Intel) all dedicating time and significant resources to the field of quantum computing, it may be just around the corner.

Computing Applications in Robotics

All robots must be programmed to function. If their functions are in any way dynamic or more complicated than the static, repetitive tasks required of early robots designed for industrial automation in the mid-twentieth century automotive industry, then their programming must be written and uploaded with the use of computers. In this way, robotics is limited by the processing power of the computers that are available to program them.

Computing applications in robotics include (and are by no means limited to):

  • Input sensing or data acquisition
  • Data processing, for example, face recognition or gas analysis
  • Programming and then correctly performing functions
  • Generating outputs, for example in a human-machine interface (HMI) display
  • Variable user control, for example in remote control devices such as drones
  • Automated control systems, for example, System Control and Data Acquisition (SCADA) systems in industrial automation
  • Rapid prototyping and research and development (R&D)

Quantum Computing Applied in Robotics

Quantum supremacy, by bringing exponentially faster, more reliable and more powerful processing ability to computers, has the potential to rapidly advance all of these applications and more.

In input sensing and data acquisition, quantum computers could be applied to enable robots to identify much smaller, even nanoscale, particles and aberrances. This would enable exponentially greater precision in the fields of metrology and materials science.

Onboard quantum computers in robots would much better identify and process the data they gather. This could include advanced facial and voice recognition for caring robots in the medical field, or more accurate gas analysis to prevent toxic leaks in heavy industries.

Quantum processor chips could be vastly smaller than classical chips with the same computing ability. This could enable microscopic robots to perform multiple, complex tasks.

Automating processes become much more practical when more processing power is applied, as would be the case in quantum computing when applied to robotics. This means that an automatic computer system could control entire fleets of drones, entire industrial processes, or even entire Internet-of-Things connected networks of smart devices. This could result in drastic energy efficiency gains in the future.

Finally, a quantum-computing powered rapid prototyping process could lead – alongside machine learning – to new opportunities developing in robotics which researchers are currently unable to imagine.

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Ben Pilkington

Written by

Ben Pilkington

Ben Pilkington is a freelance writer who is interested in society and technology. He enjoys learning how the latest scientific developments can affect us and imagining what will be possible in the future. Since completing graduate studies at Oxford University in 2016, Ben has reported on developments in computer software, the UK technology industry, digital rights and privacy, industrial automation, IoT, AI, additive manufacturing, sustainability, and clean technology.


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