Publications

We propose the use of bio-inspired robotics equipped with soft sensor technologies to gain a better understanding of the mechanics and control of animal movement. Soft robotic systems can be used to generate new hypotheses and uncover fundamental principles underlying animal locomotion and sensory capabilities, which could subsequently be validated using living organisms. Physical models increasingly include lateral body movements, notably back and tail bending, which are necessary for horizontal plane undulation in model systems ranging from fish to amphibians and reptiles. We present a comparative study of the use of physical modeling in conjunction with soft robotics and integrated soft and hyperelastic sensors to monitor local pressures, enabling local feedback control, and discuss issues related to understanding the mechanics and control of undulatory locomotion. A parallel approach combining live animal data with biorobotic physical modeling promises to be beneficial for gaining a better understanding of systems in motion.

Arboreal mammals navigate a highly three dimensional and discontinuous habitat. Among arboreal mammals, squirrels demonstrate impressive agility. In a recent 'viral' YouTube video, unsuspecting squirrels were mechanically catapulted off of a track, inducing an initially uncontrolled rotation of the body. Interestingly, they skillfully stabilized themselves using tail motion, which ultimately allowed the squirrels to land successfully. Here we analyze the mechanism by which the squirrels recover from large body angular rates. We analyzed from the video that squirrels first use their tail to help stabilizing their head to visually fix a landing site. Then the tail starts to rotate to help stabilizing the body, preparing themselves for landing. To analyze further the mechanism of this tail use during mid-air, we built a multibody squirrel model and showed the righting strategy based on body inertia moment changes and active angular momentum transfer between axes. To validate the hypothesized strategy, we made a squirrel-like robot and demonstrated a fall-stabilizing experiment. Our results demonstrate squirrel's long tail, despite comprising just 3% of body mass, can inertially stabilize a rapidly rotating body. This research contributes to better understanding the importance of long tails for righting mechanisms in animals living in complex environments such as trees.

Locomotion in unstructured and irregular environments is an enduring challenge in robotics. This is particularly true at the small scale, where relative obstacle size increases, often to the point that a robot is required to climb and transition both over obstacles and between locomotion modes. In this paper, we explore the efficacy of different design features, using 'morphological intelligence', for mobile robots operating in rugged terrain, focusing on the use of active and passive tails and changes in mass distribution, as well as elastic suspensions of mass. We develop an initial prototype whegged robot with a compliant neck and test its obstacle traversal performance in rapid locomotion with varying its mass distribution. Then we examine a second iteration of the prototype with a flexible tail to explore the effect of the tail and mass distribution in ascending a slope and traversing obstacles. Based on observations from these tests, we develop a new platform with increased performance and a fin ray wheel-leg design and present experiments on traversing large obstacles, which are larger than the robot's body, of this platform with tails of varying compliance. This biorobotic platform can assist with generating and testing hypotheses in robotics-inspired biomechanics of animal locomotion.

Soft robotics can be used not only as a means of achieving novel, more lifelike forms of locomotion but also as a tool to understand complex biomechanics through the use of robotic model animals. This paper presents the control of the undulation mechanics of an entirely soft robotic subcarangiform fish, using antagonistic fast-PneuNet actuators and hyperelastic eutectic Gallium-Indium (eGaIn) embedded in silicone channels for strain sensing. To design a controller, a simple, data-driven lumped parameter approach is developed, which allows accurate but lightweight simulation, tuned using experimental data and a genetic algorithm. The model accurately predicts the robot's behavior over a range of driving frequencies and a range of pressure amplitudes, including the effect of antagonistic co-contraction of the soft actuators. An amplitude controller is prototyped using the model and deployed to the robot to reach the setpoint of a tail-beat amplitude using fully soft and real-time strain sensing.

Rapid maneuvers are critical for animal survival in predator-prey interactions and these behaviors are more likely to apply selective pressure on performance, stability and mechanical limits compared to the extensively studied steady-state motion. Maneuvers such as jumping (eg. lemurs, mantises and jumping spiders) or aerial righting (eg. lizards or bats) often introduce instability which need to be actively compensated for. The cheetah (Acinonyx jubatus) is not only the fastest terrestrial animal but also one of the most maneuverable. These rapid maneuvers are often accompanied by dramatic swinging of its lengthy tail. However, these tail motions are under-explored. Here, we present an overview of stabilization behaviors for animals maneuvering using wings, limbs, and tails. We show kinematic simulations comparing various stabilization strategies and propose a maneuver template. We also present whole-body kinematic data obtained from captive-bred cheetahs in South Africa during 94 enrichment exercises. We analyzed over 60 tail flicks measured rotations of over 800 deg/s which further imply its use as a stabilizing element.

Arboreal animals face numerous challenges when negotiating complex three dimensional terrain. Directed aerial descent and gliding flight allows for rapid traversal of arboreal environments, but presents control challenges. Some animals, such as birds or gliding squirrels, have specialized structures to modulate aerodynamic forces while airborne. However, many arboreal animals do not possess these specializations but still control posture and orientation in mid-air. One of the largest inertial segments in lizards is their tail. Inertial reorientation can be used to attain postures appropriate for controlled aerial descent. Here we discuss the role of tail inertia in a range of mid-air reorientation behaviors using experimental data from geckos in combination with general mathematic and physical models. Geckos can self-right in mid-air by tail rotation alone. Equilibrium glide behavior of geckos in a vertical wind tunnel show that they can steer towards a landing surface using rapid, circular tail rotations to control pitch and yaw. Multiple coordinated tail responses are required for the most effective terminal velocity gliding. A mathematical model allows us to explore the relationship between morphology and the capacity for inertial reorientation by conducting sensitivity analyses. Physical models further define the limits of performance and generate new control hypotheses. Such comparative analysis allows predictions about the diversity of performance across a range of lizard morphologies and provides insights into the evolution of aerial behaviors.

The primary approach to measure hyper-redundant animal body structures is the use of high speed cameras in a laboratory environment, which can deprive locomotion of its proper context. Challenging conditions and complex three dimensional (e.g. rainforest or aquatic) environments make the collection of field data difficult, and prevents a complete analysis of an animal’s motion. We have developed liquid metal (eGaIn) based, hyper-elastic silicone strain sensors to measure local tail curvature with minimal impact on environment, mobility and body stiffness and therefore hope to enhance in situ biomechanics data collection without requiring manipulation of conditions. By not relying on imaging systems, long-duration data can be collected at very low latencies with minimal power and processing, and intricate movements can be measured in field experiments. This includes rapid tail surface righting, one of the first movement patterns observed in neonatal development. We propose utilizing soft sensors to measure subtle movements in aquatic animals as well as patterns of autotomized gecko tails. Ultimately, new insights into behavior, neuromuscular control and mechano-sensory receptivity can be gained. When connected to a soft undulating robotic fish with a tail beat frequency of 0.8-1.2 Hz, our sensor response is linear (R2(/sup) = 0.952) with a relative error that is well modeled by Gaussian noise (st. dev. of 0.4%). We additionally produce a data-driven model of the soft fish biorobot, which tracks experimental data to 1% mean error in displacement. We use this model to offer broader insight into the efficacy of eGaIn strain sensing to record biological movement of body caudal appendages in animals.

Arboreal mammals navigate a highly three dimensional and discontinuous terrain. Tail use has been observed in many species and despite specializations, fractures from falls have been observed for example in primates. Among arboreal mammals, squirrels are widely observed to be among the most maneuverable. A recent video on YouTube went viral that showed squirrels (Sciurus carolinensis) voluntarily visiting the YouTuber's garden cross a parcour to earn a food reward. When 'failing' one of the tasks, the squirrels were catapulted off the track inducing an initially uncontrolled rotation of the body. We preliminary analyzed from the video that firstly the squirrels rotate their tails to stabilize the head to visually fix the landing site. Then, the tail starts to rotate to induce a counter moment to slow down and eventually stop the body rotation preparing the squirrel for the landing. To test the hypothesis that squirrels could utilize tails during mid-air reorientation, and gain insight into tail function essential to the mechanics of this remarkable self-righting behavior, and based on basic spatio-temporal information that we extracted from preliminary observations of Sciurus carolinensis, we use an analytical model to predict squirrel kinematics on unexpected ballistic trajectories. Righting maneuvers are optimized in a multibody model which computes tail trajectories. This model is also used to explore the limits of inertial aerial righting. To further substantiate this model and demonstrate the underlying mechanics, we developed an abstracted squirrel robot completed with an actuated tail to replicate self-righting behavior. The squirrel-inspired physical model uses two high speed brushless motors to create a 2-DoF tail capable of rapid impulsive movements to test mid-air righting in a physical model.