Robots with space to "think" for themselves are much more useful
10-09-2024

Robots with space to "think" for themselves are much more useful

Engineers have developed a pioneering technique that enables robots to follow complex instructions without the need for electricity. This could significantly expand the cognitive capabilities of robots by freeing up more space in their “brains” for advanced thinking. 

This breakthrough, led by researchers from King’s College London (KCL), involves transmitting commands to robots through variations in fluid pressure instead of relying on electrical signals – a world-first approach that could revolutionize how robots are built and operate.

This novel method could pave the way for a new generation of robots whose bodies can function independently from their central control systems. 

Freeing up space in robots

The space in the robotic system, traditionally dedicated to basic operations, could instead be used for more sophisticated artificial intelligence (AI) software, allowing these machines to manage more complex tasks in diverse environments. 

Such an advancement could lead to robots that are not only more efficient but also more socially aware and adaptable in real-world situations.

Antonio Forte is a senior lecturer in engineering at KCL and the senior author of the study.

“Delegating tasks to different parts of the body frees up computational space for robots to ‘think,’ allowing future generations of robots to be more aware of their social context or even more dexterous,” said Forte.

“This opens the door for a new kind of robotics in places like social care and manufacturing.”

Robots with fluid-powered technology 

The research, recently published in Advanced Science, goes beyond simply improving robotic efficiency – it also opens the possibility of using robots in situations where electricity-powered devices cannot function effectively. 

This could include exploration missions in irradiated zones such as Chernobyl, where high radiation levels can destroy electrical circuits, or in highly sensitive environments like MRI rooms, where electronic devices can interfere with medical equipment. 

Furthermore, robots built using this fluid-powered technology could become essential in low-income countries, where reliable access to electricity may be a challenge.

Making robots more efficient 

Forte highlights the importance of this new approach in enhancing the functionality of robots. 

“Put simply, robots are split into two parts: the brain and the body. An AI brain can help run the traffic system of a city, but many robots still struggle to open a door – why is that? Software has advanced rapidly in recent years, but hardware has not kept up,” said Forte. 

“By creating a hardware system independent from the software running it, we can offload a lot of the computational load onto the hardware, in the same way your brain doesn’t need to tell your heart to beat.”

The challenge of complex tasks

Currently, almost all robots rely on electricity and integrated computer chips to perform their tasks. A robotic “brain,” which consists of algorithms and AI software, sends instructions to the robot’s physical body, which carries out the action. 

This interaction between the software and the hardware is managed through encoders, which translate the software’s commands into physical movements. 

However, this approach is particularly problematic for “soft robotics,” a subfield that designs devices made from soft, flexible materials, like robotic muscles. The integration of rigid electronic encoders complicates the system, making it harder for the material to perform complex tasks, such as grasping a doorknob.

A new level of control

To address this challenge, the research team developed a reconfigurable circuit featuring an adjustable valve. This valve acts like a transistor in a standard electrical circuit, but instead of using electrical signals, it uses pressure to send commands directly to the hardware. 

The engineers use fluid pressure to transmit binary-like signals to the robot’s physical structure, allowing the robot to perform complex movements without requiring electricity or constant instructions from a central processing unit. 

This innovation allows for a level of control that surpasses what current fluid-based systems can offer.

Giving the robot space to think

By offloading part of the computational work onto the robot’s physical system, this new circuit design frees up the robot’s “brain” to focus on more complex tasks, making the robot more adaptive and capable in a wide variety of scenarios. 

As a result, robots equipped with this technology could be more effective in real-world situations, including those that require nuanced physical interactions or decision-making abilities.

The next step for the researchers is to scale up their circuit design. They plan to move beyond small experimental setups and integrate this technology into larger robots, such as those used for monitoring power plants or robots with entirely soft engines. 

These new systems could be used in environments that require advanced robotics, like industrial sites or in complex rescue operations.

Broader implications of the research

Mostafa Mousa, a post-graduate researcher at KCL and co-author of the study, emphasized the broader implications of this development.

“Ultimately, without investment in embodied intelligence, robots will plateau. Soon, if we do not offload the computational load that modern day robots take on, algorithmic improvements will have little impact on their performance,” said Mousa.

“Our work is just a first step on this path, but the future holds smarter robots with smarter bodies.”

This breakthrough marks a significant step forward in the field of robotics, with the potential to transform the capabilities of robots across industries. 

By shifting part of the cognitive load from software to hardware, robots could become far more versatile and efficient in their tasks, allowing them to be more adaptive, resilient, and ultimately, more useful in a wider range of applications.

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