While physical reservoir computers (PRCs) have tremendous potential for applications in electromechanical and biomechanical systems, their adoption remains slow due to a limited understanding of the impact of mechanical parameters on computational properties. Here, we specifically investigate these relationships concerning the body structure, input parameters, and observed states using classical swinging body dynamical systems: soft tentacles and a simulated multilink pendulum. Principally, we show that the mechanical structure (including stiffness and damping) couples with input parameters (frequency and magnitude) to regulate the manifested computational capabilities, and the type of PRC (if any) that can be achieved. Further, we show that input rate drives a transition between linear memory-based and nonlinear calculations, while the mechanical structure alters the conversion between longer and shorter memories. By investigating sensory limitations, we show that a spatiotemporal structure of the computational properties exists that relates to the mechanical structure, and that can be exploited to improve selected computing tasks in soft tentacle PRCs. Using the parameter dependencies we additionally provide inferences into the computational archetypes of the bodies of established soft robots.

This paper presents the addition of two models for added mass to the fluid-field spring-loaded inverted pendulum (FF-SLIP) Model for legged swimming. The relative ability of these models to capture the increased fluid forces due to virtual mass displacement is evaluated using a two-legged swimming robot, Tadpole. We show that a simple addition to our reduced-order model can predict fluid-leg interaction forces while remaining computationally efficient.

Legged animals have developed a variety of modes of locomotion to adapt to the diverse and unknown terrain challenges posed in the natural world. Legged robots, however, have been largely limited to specializing in one domain, with few that have endeavored to bridge the gap between two. In this work we present the Scansorial, Terrestrial, and Aquatic Robot Quadruped (STARQ), a novel legged robot capable of bridging three different domains with three modes of locomotion: walking, climbing, and swimming. In this study we describe model-based design techniques as well as design innovations that have made multimodal locomotion possible including waterproof hips for 2-DOF high torque legs, legs capable of effective power transmission in three modes, and bi-directionally compliant feet for walking and attaching to vertical surfaces. To demonstrate the robot's capabilities we present locomotion test data including speed and cost of transport in each of these domains. We also demonstrate the capability to transition from walking to swimming in a natural environment.

In this paper we present swimming and modeling for Trident, a three-link lamprey inspired robot that is able to climb on flat smooth walls. We explore two gaits proposed to work for linear swimming, and three gaits for turning maneuvers. We compare the experimental results obtained from these swimming experiments with two different reduced order fluid interaction models, one a previously published potential flow model, and the other a slender cylinder model we developed. We find that depending on the the parameters of swimming chosen, we are able to move forward, backward and sideways with a peak speed of 2.5 cm/s. We identify the conditions when these models apply and aspects that will require additional complexity.

This paper describes the development of a single reduced-order dynamic model that captures running on land, running while submerged, and for the first time swimming on the surface of water. By capturing the effect of fluid forces on both the body and the leg, the Spring-Loaded Inverted Pendulum (SLIP) model is extended to operate in amphibious and aquatic regimes. Three distinct stable motion patterns, or dog-paddle type gaits are identified when swimming at the air-water interface. The model shows that, for surfaces swimming, alteration of the leg stroke frequency and length produces gaits that are either smooth and efficient or are vertically oscillatory and exhibit rapid disturbance rejection. Furthermore, when the model is examined at the physical parameter values corresponding to dogs (specifically Labrador Retrievers), the animal-based control parameters demonstrate nearly optimal performance.

This paper describes the design, control and initial experimental results of the quadruped robot LLAMA. Designed to operate in a human-scale world, this 67kg-class, all-electric robot is capable of rapid motion over a variety of terrains. Thanks to a unique leg configuration and custom high-torque, low gear-ratio motors, it can move omnidirectionally at speeds over 1 m/s. A hierarchical reactive control scheme allows for robust and efficient motion even under variable payloads. This paper describes the structure of the controller and outlines simulation results that probe the performance envelope of the robot suggesting payload capacities up to one third of its body weight. Initial testing shows robust motion over loose debris and a variety of ground slopes. Videos of the robot may be seen at https://tinyurl.com/llama-robot.

Autonomous navigation through unstructured terrains has been most effectively demonstrated by animals, who utilize a large set of locomotive styles to move through their native habitats. While legged robots have recently demonstrated several of these locomotion modalities (such as walking, running, jumping, and climbing vertical walls), motion planners have yet to be able to leverage these unique mobility characteristics. In this article, we outline some of the specific motion planning challenges faced when attempting to plan for legged systems with dynamic gaits, with specific instances of these demonstrated by the dynamic climbing platform TAILS. Using a unique implementation of sampling-based model predictive optimization, we demonstrate the ability to motion plan around obstacles on vertical walls and experimentally demonstrate this on TAILS by navigating through traditionally difficult narrow gap problems.

The design process for leg morphology has taken much of its inspiration from the manipulator community, including the concept of maximizing the workspace of a design. In this paper, we define the concept of Effective Dynamic Workspace, which examines the subset of the overall workspace capable of achieving the desired template dynamics. With this new design tool, the leg configuration of a new multi-modal platform BOBCAT is examined and refined. With the refined design, BOBCAT is able to achieve speeds of 2m/s while running and 0.17m/s while climbing a vertical wall.

In this paper, we examine the reduced order pendular dynamic climbing model with the addition of attachment windows based on prescribed body roll. With this model and on the new dynamic climbing platform, TAILS, we demonstrate dynamic downward climbing as well as identify distinct dynamic gaits within downward climbing. This, combined with the application of an asymmetric configuration of the rear legs enables strafing motions and thus dynamic maneuverability on walls in the vertical domain.