Squirrels exhibit agile leaping between tree branches, often using non-prehensile gripping with compliant and passively adaptive fingers. We aim to test the utility of such gripping in agile robotic maneuvering. In the present study, we first examine the parametric design of a squirrel-inspired underactuated gripper for passive landing on impact. We fix the geometry of the gripper and vary the joint stiffness and contact conditions. We find that stiffer fingers with soft foam pads enlarge the landing sufficiency region. Specifically, friction appears to enlarge horizontal error tolerance, while joint stiffness and pad damping allow for higher impact speeds. Thus, these features should be considered in the design of future agile robot hands and feet that include high impact landings on rods with pose inaccuracy.

Despite substantial evidence for the crucial role played by an active backbone or spine in animal locomotion, its adoption in legged robots remains limited because the added mechanical complexity and resulting dynamical challenges pose daunting obstacles to characterizing even a partial range of potential performance benefits. This paper takes a next step toward such a characterization by exploring the quasistatic terrestrial self-righting mechanics of a model system with coronal plane spine twisting (CPST). Reduction from a full 3D kinematic model of CPST to a two parameter, two degree of freedom coronal plane representation of body shape affordance predicts a substantial benefit to ground righting by lowering the barrier between stable potential energy basins. The reduced model predicts the most advantageous twist angle for several cross-sectional geometries, reducing the required righting torque by up to an order of magnitude depending on constituent shapes. Experiments with a three actuated degree of freedom physical mechanism corroborate the kinematic model predictions using two different quasistatic reorientation maneuvers for both elliptical and rectangular shaped bodies with a range of eccentricities or aspect ratios. More speculative experiments make intuitive use of the kinematic model in a highly dynamic maneuver to suggest still greater benefits of CPST achievable by coordinating kinetic as well as potential energy, for example as in a future multi-appendage system interacting with a contact-rich 3D environment.

Animals and robots alike face challenges of flipping-over as they move in complex terrain. Small insects like cockroaches can rapidly right themselves when upside down, yet small fast-running legged robots are much less capable of ground-based self-righting. Inspired by the discoid cockroach that opens its wings to push against the ground to self-right, we designed actuated wings for robot self-righting based on recently-developed rounded shells for obstacle traversal [1]. We measured the self-righting performance of a robot using these actuated wings, and systematically studied the effects and trade-offs of wing opening magnitude, speed, symmetry, and wing geometry. Our study provided a proof-of-concept that robots can take advantage of an existing body structure (rounded shell) in novel ways (as actuated wings) to serve new locomotor functions, analogous to biological exaptations [2]. Our results demonstrated that the robot self-rights dynamically, with active wing pushing followed by passive falling, and benefits from increasing kinetic energy by pushing faster and longer. Our experiments also showed that opening both wings asymmetrically increases righting probability at low wing opening magnitudes.

This paper develops a comparative framework for the design of actuated inertial appendages for planar aerial reorientation. We define the inertial reorientation template, the simplest model of this behavior, and leverage its linear dynamics to reveal the design constraints linking a task with the body designs capable of completing it. As practicable inertial appendage designs lead to morphology that is generally more complex, we advance a notion of “anchoring,” whereby a judicious choice of physical design in concert with an appropriate control policy yields a system whose closed-loop dynamics are sufficiently captured by the template to permit all further designs to take place in its far simpler parameter space. This approach is effective and accurate over the diverse design spaces afforded by existing platforms, enabling a performance comparison through the shared task space. We analyze examples from the literature and find advantages to each body type, but conclude that tails provide the highest potential performance for reasonable designs. Thus motivated, we build a physical example by retrofitting a tail to a RHex robot and present empirical evidence of its efficacy.

In this work, we propose a control scheme for attitude control of a falling, two link active tailed robot with only two degrees of freedom of actuation. We derive a simplified expression for the robot's angular momentum and invert this expression to solve for the shape velocities that drive the body's angular momentum to a desired value. By choosing a body angular velocity vector parallel to the axis of error rotation, the controller steers the robot towards its desired orientation. The proposed scheme is accomplished through feedback laws as opposed to feedforward trajectory generation, is fairly robust to model uncertainties, and is simple enough to implement on a miniature microcontroller. We verify our approach by implementing the controller on a small (175 g) robot platform, enabling rapid maneuvers approaching the spectacular capability of animals.

We present a novel approach to stabilizing rapid locomotion in mobile terrestrial robots inspired by the tail function of lizards.We built a 177 (g) robot with inertial sensors and a single degree-of-freedom active tail. By utilizing both contact forces and zero net angular momentum maneuvering, our tailed robot can rapidly right itself in a fall, avoid flipping over after a large perturbation, and smoothly transition between surfaces of different slopes. We also use a modeling approach to show that a tail-like design offers significant advantages to other alternatives, including reaction wheels, when the speed of response is important.

The interplay between robotics and neuromechanics facilitates discoveries in both fields: nature provides roboticists with design ideas, while robotics research elucidates critical features that confer performance advantages to biological systems. Here, we explore a system particularly well suited to exploit the synergies between biology and robotics: high-speed antenna-based wall following of the American cockroach (Periplaneta americana). Our approach integrates mathematical and hardware modeling with behavioral and neurophysiological experiments. Specifically, we corroborate a prediction from a previously reported wall-following template - the simplest model that captures a behavior - that a cockroach antenna-based controller requires the rate of approach to a wall in addition to distance, e.g., in the form of a proportional-derivative (PD) controller. Neurophysiological experiments reveal that important features of the wall-following controller emerge at the earliest stages of sensory processing, namely in the antennal nerve. Furthermore, we embed the template in a robotic platform outfitted with a bio-inspired antenna. Using this system, we successfully test specific PD gains (up to a scale) fitted to the cockroach behavioral data in a "real-world" setting, lending further credence to the surprisingly simple notion that a cockroach might implement a PD controller for wall following. Finally, we embed the template in a simulated lateral-leg-spring (LLS) model using the center of pressure as the control input. Importantly, the same PD gains fitted to cockroach behavior also stabilize wall following for the LLS model.