Using a brain-inspired approach, scientists from Nanyang Technological University, Singapore (NTU Singapore) have developed a way for robots to have the artificial intelligence (AI) to recognise pain and to self-repair when damaged.
The system has AI-enabled sensor nodes to process and
respond to ‘pain’ arising from pressure exerted by a physical force. The system
also allows the robot to detect and repair its own damage when minorly ‘injured’,
without the need for human intervention.
Currently, robots use a network of sensors to generate
information about their immediate environment. For example, a disaster rescue
robot uses camera and microphone sensors to locate a survivor under debris and
then pulls the person out with guidance from touch sensors on their arms. A
factory robot working on an assembly line uses vision to guide its arm to the
right location and touch sensors to determine if the object is slipping when
picked up.
Today’s sensors typically do not process information
but send it to a single large, powerful, central processing unit where learning
occurs. As a result, existing robots are usually heavily wired which result in
delayed response times. They are also susceptible to damage that will require
maintenance and repair, which can be long and costly.
The new NTU approach embeds AI into the network of
sensor nodes, connected to multiple small, less-powerful, processing units,
that act like ‘mini-brains’ distributed on the robotic skin. This means
learning happens locally and the wiring requirements and response time for the
robot are reduced five to ten times compared to conventional robots, say the
scientists.
Combining the system with a type of self-healing ion
gel material means that the robots, when damaged, can recover their mechanical
functions without human intervention.
The breakthrough research by the NTU scientists was
published in the peer-reviewed scientific journal Nature Communications in
August.
Co-lead author of the study, Associate Professor
Arindam Basu from the School of Electrical & Electronic Engineering said,
“For robots to work together with humans one day, one concern is how to ensure
they will interact safely with us. For that reason, scientists around the world
have been finding ways to bring a sense of awareness to robots, such as being
able to ‘feel’ pain, to react to it, and to withstand harsh operating
conditions. However, the complexity of putting together the multitude of
sensors required and the resultant fragility of such a system is a major
barrier for widespread adoption.”
Assoc Prof Basu, who is a neuromorphic computing
expert added, “Our work has demonstrated the feasibility of a robotic system
that is capable of processing information efficiently with minimal wiring and
circuits. By reducing the number of electronic components required, our system
should become affordable and scalable. This will help accelerate the adoption
of a new generation of robots in the marketplace.”
Robust system enables ‘injured’ robot to
self-repair
To teach the robot how to recognise pain and learn
damaging stimuli, the research team fashioned memtransistors, which are
‘brain-like’ electronic devices capable of memory and information processing,
as artificial pain receptors and synapses.
Through lab experiments, the research team
demonstrated how the robot was able to learn to respond to injury in real time.
They also showed that the robot continued to respond to pressure even after
damage, proving the robustness of the system.
When ‘injured’ with a cut from a sharp object, the
robot quickly loses mechanical function. But the molecules in the self-healing
ion gel begin to interact, causing the robot to ‘stitch’ its ‘wound’ together
and to restore its function while maintaining high responsiveness.
First author of the study, Rohit Abraham John, who is
also a Research Fellow at the School of Materials Science & Engineering at
NTU, said, “The self-healing properties of these novel devices help the robotic
system to repeatedly stitch itself together when ‘injured’ with a cut or
scratch, even at room temperature. This mimics how our biological system works,
much like the way human skin heals on its own after a cut.
“In our tests, our robot can ‘survive’ and respond to
unintentional mechanical damage arising from minor injuries such as scratches
and bumps, while continuing to work effectively. If such a system were used
with robots in real world settings, it could contribute to savings in
maintenance.”
Associate Professor Nripan Mathews, who is co-lead
author and from the School of Materials Science & Engineering at NTU, said,
“Conventional robots carry out tasks in a structured programmable manner, but
ours can perceive their environment, learning and adapting behaviour
accordingly. Most researchers focus on making more and more sensitive sensors,
but do not focus on the challenges of how they can make decisions effectively.
Such research is necessary for the next generation of robots to interact
effectively with humans.
“In this work, our team has taken an approach that is
off-the-beaten path, by applying new learning materials, devices and
fabrication methods for robots to mimic the human neuro-biological functions. While
still at a prototype stage, our findings have laid down important frameworks
for the field, pointing the way forward for researchers to tackle these
challenges.”
Building on their previous body of work on
neuromorphic electronics such as using light-activated devices to recognise
objects, the NTU research team is now looking to collaborate with industry
partners and government research labs to enhance their system for larger scale
application.
Journal article: https://www.nature.com/articles/s41467-020-17870-6
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