Research has introduced a computational model that effectively represents the complex muscle structure of an octopus arm.
Mechanical engineering PhD student Arman Tekinalp, graduate student Seung Hyun Kim, Professor Prashant Mehta, and Associate Professor Mattia Gazzola, all part of the Department of Mechanical Science and Engineering at the University of Illinois Urbana-Champaign, have published their findings in the Proceedings of the National Academy of Science (PNAS). This interdisciplinary research also involved Assistant Professor Noel Naughton from the University of Virginia Tech and personnel from the Department of Molecular and Integrative Physiology at Illinois, as well as collaborators from the University of North Carolina Chapel Hill and the University of South Florida. Their paper titled “Topology, dynamics, and control of a muscle-architected soft arm,” which featured on the cover, presents a groundbreaking computational model highlighting the elaborate muscular design of an octopus arm.
This model is instrumental in illustrating how structural mechanics can simplify arm control by seamlessly coordinating complex three-dimensional repeated movements derived from straightforward muscle contractions. The researchers have been working together on this project since 2019, aiming to create “cyberoctopus” capabilities — robotic systems that can mimic the intricate movements of octopus arms.
In many creatures, including humans, a centralized brain functions as the main control center, managing the body’s actions. However, octopuses have a different setup, with a distributed nervous system allowing each of their eight arms to operate autonomously. Additionally, the octopus’s anatomy enables each arm to move in nearly limitless ways, making it quite challenging to compute.
“The primary goal is to understand how to manage a complex system with many movement possibilities and find alternatives to costly computations,” explained Gazzola. “The octopus serves as a fascinating model organism that has been investigated since the 1980s, as researchers seek to uncover the ‘secret’ behind its abilities.”
“I find learning from living creatures intriguing, and I aim to adapt some of these insights into soft robotics,” said Tekinalp regarding his motivation for the research.
In earlier projects, the team developed a theoretical method for controlling a simplified octopus arm model as part of their interdisciplinary efforts. They used MRI and detailed biomedical data to create a realistic model of an arm made up of nearly 200 interlaced muscles.
They also tracked the movements of a real octopus in action within a tank. This octopus was positioned next to a Plexiglas barrier with a hole that allowed only one arm to pass through. A desirable object was placed on the other side, enabling the researchers to capture footage of the octopus reaching for and interacting with the item.
“Observing the octopus was like engaging with a curious child,” Gazzola remembered. “You have to know how to approach and keep it interested.”
From their imaging, the scientists gathered motion data, demonstrating through simulations that their control technique could duplicate the octopus arm’s intricate movements. “We utilized topology and differential geometry to apply key theoretical principles to the arm, allowing us to describe its shape and control it through muscle activation,” Gazzola added.
To capture the arm’s movement dynamics, the researchers crafted straightforward muscle activation templates that could facilitate complex 3D motions. “Instead of grappling with thousands of movement possibilities, we focused on two key topological aspects — writhe and twist — relative to muscle dynamics,” Gazzola stated. “Each of these is influenced by distinct muscle groups, and their combined activation generates a third topological element that represents the arm’s morphological changes in 3D — that is, its motion.”
This advanced computational model marks a significant achievement in both biological studies, providing insights into octopus capabilities, and in the field of engineering. “The model serves as a valuable testing ground for roboticists to evaluate their algorithms,” Mehta noted.
This long-term investigation exemplifies collaborative work from different research groups and numerous students over the years. The team continues to evolve; for instance, Tekinalp, who is set to graduate in December 2024, will transition to a postdoctoral role at the University of Maryland, College Park.
“It was encouraging for both Mattia and me to witness the strong teamwork between students from our two research groups,” Mehta remarked.
Looking ahead, the researchers expect to enhance their simulation techniques to explore ways to coordinate all eight arms in unison (for instance, imitating how an octopus handles multiple objects simultaneously). They also aim to turn their discoveries into robotic prototypes for practical testing.
“Our theoretical understanding remains somewhat intuitive,” Gazzola said when discussing future directions. “We aspire to establish an automated system so that our octopus model can autonomously learn and complete tasks.”
