Green sea turtles (Chelonia mydas) can swim up to 50 km per day while only consuming seagrass or microalgae. How the animal accomplishes this vast journey on such low energy intake points to the effectiveness of their swimming technique and is a testament to the power of evolution. Understanding the green sea turtle's ability to accomplish these journeys requires insight into their propulsive strategies. Conducting animal testing to uncover their propulsive strategies brings significant challenges: firstly, the ethical issues of conducting experiments on an endangered animal, and secondly, the animal may not even swim with its regular routine during the experiments. In this work, we develop a new soft-robotic sea turtle that reproduces the real animal's form and function to provide biomechanical insights without the need for invasive experimentation. We found that the green sea turtle may only produce propulsion for approximately 30% of the limb beat cycle, with the remaining 70% exploiting a power-preserving low-drag glide. Due to the animal's large mass and relatively low drag coefficient, losses in swim speed are minimal during the gliding stage. These findings may lead to the creation of a new generation of robotic systems for ocean exploration that use an optimised derivative of the sea turtle propulsive strategy.

Biomechanically, sea turtles could be perceived as birds of the ocean as they glide and flap their forelimbs to produce the necessary forces required for locomotion, making sea turtles an interesting animal to study. However, being an endangered species makes studying the sea turtle's biomechanics a complex problem to solve, both technically and ethically, without causing disturbance. This work develops a novel, non-invasive procedure to develop full three-dimensional kinematics for wild sea turtles by filming the animals in Australia's Great Barrier Reef using underwater drones without disturbing them. We found that the wild animals had very different swimming patterns than previous studies on juveniles in captivity. Our findings show that the flipper goes through a closed-loop trajectory with extended sweeping of the flipper tip towards the centre of the carapace to create a clapping motion. We have named this the “sweep stroke” and in contrast to previously described four-stage models, it creates a five-stage cycle swimming locomotion model. The model presented here could lead to a better comprehension of the sea turtle propulsion methods and their fluid–structure interaction.

Sea turtles gracefully navigate their marine environments by flapping their pectoral flippers in an elegant routine to produce the required hydrodynamic forces required for locomotion. The propulsion of sea turtles has been shown to occur for approximately 30% of the limb beat, with the remaining 70% employing a drag-reducing glide. However, it is unknown how the sea turtle manipulates the flow during the propulsive stage. Answering this research question is a complicated process, especially when conducting laboratory tests on endangered animals, and the animal may not even swim with its regular routine while in a captive state. In this work, we take advantage of our robotic sea turtle, internally known as Cornelia, to offer the first insights into the flow features during the sea turtle’s propulsion cycle consisting of the downstroke and the sweep stroke. Comparing the flow features to the animal’s swim speed, flipper angle of attack, power consumption, thrust and lift production, we hypothesise how each of the flow features influences the animal’s propulsive efforts and cost of transport (COT). Our findings show that the sea turtle can produce extremely low COT values that point to the effectiveness of the sea turtle propulsive technique. Based on our findings, we extract valuable data that can potentially lead to turtle-inspired elements for high-efficiency underwater drones for long-term underwater missions.

Sea turtles are recognised as one of the ocean’s most remarkable migratory species, accomplishing journeys that cover thousands of kilometres. This fact is even more extraordinary when considering sea turtles consume mostly low-energy foods. The biology of sea turtles dominates the literature; however, the swimming strategies they employ to achieve their migratory success from a biomechanical and hydrodynamic viewpoint is relatively unexplored. In past research, the sea turtle’s upstroke has been debated among researchers as to whether it is passive or for thrust production. In this work, we recreate a model based on the green sea turtle (Chelonia mydas) and develop an ad hoc testing rig to uncover the secrets behind the sea turtle’s upstroke. Our findings suggest sea turtles utilise a passive upstroke that can substantially lower the animal’s drag coefficient to levels that cause insignificant losses in swim speed despite not developing any thrust force. This can conceivably save the animal a notable amount of energy as the upstroke is responsible for a large percentage of the overall limb beat cycle. These findings could potentially pave a path towards developing high-efficiency bioinspired underwater drone technologies.

Sea turtles are a keystone species for the ocean’s ecosystem, with all species currently being listed as endangered. Such a threat is mainly due to human factors such as fishing net entanglement. This entanglement often comes at the expense of turtles losing a pectoral flipper. The reduction in a sea turtle’s survival odds upon losing a flipper is a significant concern. This issue extends beyond individual animals, as the potential extinction of sea turtles could have detrimental effects on ocean health and subsequently disrupt our lifestyles. In this work, with the help of robotics, we tested the suitability of a prosthetic flipper for sea turtles that have lost a flipper. Testing with our sea-turtle-inspired robot helped to demonstrate the prosthetic flipper’s performance without clinical trials in live animals. The robot showed that the prosthetic could closely mimic the sea turtle’s downstroke and upstroke, allowing the animal to regain control in roll, pitch, and yaw, despite the absence of anatomical joints and related muscles. Additionally, swim speed tests provided an average swim speed of 0.487 m/s while dragging 6 m of cable to give a calculated maximum swim speed of 0.618 m/s, coming close to the average swim speed of wild sea turtles of 0.6 m/s. Our aspiration is that the findings from this study will pave the way for an open-source implant design, empowering veterinary professionals globally to aid injured turtles. Furthermore, this research promises to inspire additional animal-based robotic designs, advancing technologies geared towards assisting other animals in distress.