Using
a brain-inspired approach, scientists from Nanyang Technological
University in Singapore (NTU) 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.
To watch the robot respond to pain and self-heal, click here.
Co-lead author of the study, Associate Professor Arindam Basu from the School of Electrical & Electronic Engineering says, “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, says, “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, says, “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.
