Core Actuation Promotes Self-Manipulability on a Direct-Drive Quadrupedal Robot

For direct-drive legged robots operating in unstructured environments, workspace volume and force generation are competing, scarce resources. In this paper we demonstrate that introducing geared core actuation (i.e., proximal to rather than distal from the mass center) increases workspace volume and can provide a disproportionate amount of work-producing force to the mass center without affecting leg linkage transparency. These effects are analytically quantifiable up to modest assumptions, and are demonstrated empirically on a spined quadruped performing a leap both on level ground and from an isolated foothold (an archetypal feature of unstructured terrain)

Master of Science

thesisThis thesis describes the design, modeling, and gait control of a new bounding/rolling quadruped robot called the roll-U-ped. The robot has four uniquely-designed compliant legs for bounding gait locomotion, and the legs can reconfigure for passive and powered rolling. One of the main advantages of such a design is versatility as the robot can efficiently and quickly traverse over flat and downhill terrain via rolling and then transition to running for traveling over more complex terrain with a bounding gait. The contributions of this work are: (1) a detailed description of the robot design, (2) modeling and simulation of bounding motion, (3) investigation of bounding gait effectiveness using sinusoidal control inputs and inputs obtained from machine learning, and (4) prototype development and performance evaluation. Specifically, the prototype robot utilizes 3D-printed compliant legs for dynamic running and rolling, and the dual-purpose leg design minimizes the number of joints. Two functional prototypes are developed with on-board embedded electronics and a single-board computer running the Robot Operating System for motion control and evaluation. Simulations of the bounding gait locomotion are shown and compared to the performance of the prototype designs. Additionally, the robot's running motion is investigated for two types of inputs: a sinusoidal trajectory and a learned gait using the Q-learning technique, where results demonstrate effective running and rolling behavior. For example, using sinusoidal inputs, the robot can run with a bounding gait over a flat and stiff sandpaper-like surface at speeds of up to 0.21 m/s. On the other hand, over a flat and tacky-cushioned surface, the speed is measured at 0.14 m/s. Simulation results for Q-learning show gait speeds of 0.22 m/s for the tacky-cushioned surface, where experiments on the physical system yielded a gait speed of 0.15 m/s. For powered rolling, the robot was able to reach a speed of 0.53 m/s over a flat-smooth surface. The results demonstrate proof-of-concept of the design and feasibility of using machine learning to determine inputs for effective running locomotion. Finally, possible future improvements to the design, modeling, and motion control of the robot are discussed

Towards Automatic Discovery of Agile Gaits for Quadrupedal Robots

Developing control methods that allow legged robots to move with skill and agility remains one of the grand challenges in robotics. In order to achieve this ambitious goal, legged robots must possess a wide repertoire of motor skills. A scalable control architecture that can represent a variety of gaits in a unified manner is therefore desirable. Inspired by the motor learning principles observed in nature, we use an optimization approach to automatically discover and fine-tune parameters for agile gaits. The success of our approach is due to the controller parameterization we employ, which is compact yet flexible, therefore lending itself well to learning through repetition. We use our method to implement a flying trot, a bound and a pronking gait for StarlETH, a fully autonomous quadrupedal robot

System Design of a Cheetah Robot Toward Ultra-high Speed

High-speed legged locomotion pushes the limits of the most challenging problems of design and development of the mechanism, also the control and the perception method. The cheetah is an existence proof of concept of what we imitate for high-speed running, and provides us lots of inspiration on design. In this paper, a new model of a cheetah-like robot is developed using anatomical analysis and design. Inspired by a biological neural mechanism, we propose a novel control method for controlling the muscles' flexion and extension, and simulations demonstrate good biological properties and leg's trajectory. Next, a cheetah robot prototype is designed and assembled with pneumatic muscles, a musculoskeletal structure, an antagonistic muscle arrangement and a J-type cushioning foot. Finally, experiments of the robot legs swing and kick ground tests demonstrate its natural manner and validate the design of the robot. In the future, we will test the bounding behaviour of a real legged system

Optimum Gait Selection for Quadruped Robots

This paper studies periodic gaits of quadruped animals and its application to multilegged artificial locomotion systems. The purpose is to determine the best set of gait and locomotion variables during walking, for different robot velocities and intrabody compliance characteristics, based on two formulated performance measures. A set of experiments reveals the influence of the gait and locomotion variables upon the proposed indices, namely that the gait and the locomotion parameters should be adapted to the robot forward velocity and to the robot intra-body compliance characteristics.N/

Optimal energy gaits for quadrupeds under variable locomotion conditions

This paper studies the adoption of periodic gaits of quadruped animals by multilegged artificial locomotion exercise. The purpose is to determine the gait to adopt at different velocities, under distinct robot and locomotion conditions, based on two performance measures. A set of experiments reveals the influence of the gait and the body and ground parameters upon the proposed indices. It is verified that the gait should be adapted to the robot forward velocity and to the conditions under which the robot is moving. The experiments also reveal that a gait that decreases the energy consumption generally implies an increase in the trajectory following errors.N/

Modular Hopping and Running via Parallel Composition

Though multi-functional robot hardware has been created, the complexity in its functionality has been constrained by a lack of algorithms that appropriately manage flexible and autonomous reconfiguration of interconnections to physical and behavioral components. Raibert pioneered a paradigm for the synthesis of planar hopping using a composition of ``parts\u27\u27: controlled vertical hopping, controlled forward speed, and controlled body attitude. Such reduced degree-of-freedom compositions also seem to appear in running animals across several orders of magnitude of scale. Dynamical systems theory can offer a formal representation of such reductions in terms of ``anchored templates,\u27\u27 respecting which Raibert\u27s empirical synthesis (and the animals\u27 empirical performance) can be posed as a parallel composition. However, the orthodox notion (attracting invariant submanifold with restriction dynamics conjugate to a template system) has only been formally synthesized in a few isolated instances in engineering (juggling, brachiating, hexapedal running robots, etc.) and formally observed in biology only in similarly limited contexts. In order to bring Raibert\u27s 1980\u27s work into the 21st century and out of the laboratory, we design a new family of one-, two-, and four-legged robots with high power density, transparency, and control bandwidth. On these platforms, we demonstrate a growing collection of $\{$body, behavior$\}$ pairs that successfully embody dynamical running / hopping ``gaits\u27\u27 specified using compositions of a few templates, with few parameters and a great deal of empirical robustness. We aim for and report substantial advances toward a formal notion of parallel composition---embodied behaviors that are correct by design even in the presence of nefarious coupling and perturbation---using a new analytical tool (hybrid dynamical averaging). With ideas of verifiable behavioral modularity and a firm understanding of the hardware tools required to implement them, we are closer to identifying the components required to flexibly program the exchange of work between machines and their environment. Knowing how to combine and sequence stable basins to solve arbitrarily complex tasks will result in improved foundations for robotics as it goes from ad-hoc practice to science (with predictive theories) in the next few decades

X-RHex: A Highly Mobile Hexapedal Robot for Sensorimotor Tasks

We report on the design and development of X-RHex, a hexapedal robot with a single actuator per leg, intended for real-world mobile applications. X-RHex is an updated version of the RHex platform, designed to offer substantial improvements in power, run-time, payload size, durability, and terrain negotiation, with a smaller physical volume and a comparable footprint and weight. Furthermore, X-RHex is designed to be easier to build and maintain by using a variety of commercial off-the-shelf (COTS) components for a majority of its internals. This document describes the X-RHex architecture and design, with a particular focus on the new ability of this robot to carry modular payloads as a laboratory on legs. X-RHex supports a variety of sensor suites on a small, mobile robotic platform intended for broad, general use in research, defense, and search and rescue applications. Comparisons with previous RHex platforms are presented throughout, with preliminary tests indicating that the locomotive capabilities of X-RHex can meet or exceed the previous platforms. With the additional payload capabilities of X-RHex, we claim it to be the first robot of its size to carry a fully programmable GPU for fast, parallel sensor processing

Towards Agility: Definition, Benchmark and Design Considerations for Small, Quadrupedal Robots

Agile quadrupedal locomotion in animals and robots is yet to be fully understood, quantified or achieved. An intuitive notion of agility exists, but neither a concise definition nor a common benchmark can be found. Further, it is unclear, what minimal level of mechatronic complexity is needed for this particular aspect of locomotion. In this thesis we address and partially answer two primary questions: (Q1) What is agile legged locomotion (agility) and how can wemeasure it? (Q2) How can wemake agile legged locomotion with a robot a reality? To answer our first question, we define agility for robot and animal alike, building a common ground for this particular component of locomotion and introduce quantitative measures to enhance robot evaluation and comparison. The definition is based on and inspired by features of agility observed in nature, sports, and suggested in robotics related publications. Using the results of this observational and literature review, we build a novel and extendable benchmark of thirteen different tasks that implement our vision of quantitatively classifying agility. All scores are calculated from simple measures, such as time, distance, angles and characteristic geometric values for robot scaling. We normalize all unit-less scores to reach comparability between different systems. An initial implementation with available robots and real agility-dogs as baseline finalize our effort of answering the first question. Bio-inspired designs introducing and benefiting from morphological aspects present in nature allowed the generation of fast, robust and energy efficient locomotion. We use engineering tools and interdisciplinary knowledge transferred from biology to build low-cost robots able to achieve a certain level of agility and as a result of this addressing our second question. This iterative process led to a series of robots from Lynx over Cheetah-Cub-S, Cheetah-Cub-AL, and Oncilla to Serval, a compliant robot with actuated spine, high range of motion in all joints. Serval presents a high level of mobility at medium speeds. With many successfully implemented skills, using a basic kinematics-duplication from dogs (copying the foot-trajectories of real animals and replaying themotion on the robot using a mathematical interpretation), we found strengths to emphasize, weaknesses to correct and made Serval ready for future attempts to achieve even more agile locomotion. We calculated Servalâs agility scores with the result of it performing better than any of its predecessors. Our small, safe and low-cost robot is able to execute up to 6 agility tasks out of 13 with the potential to reachmore after extended development. Concluding, we like to mention that Serval is able to cope with step-downs, smooth, bumpy terrain and falling orthogonally to the ground

Affordances And Control Of A Spine Morphology For Robotic Quadrupedal Locomotion

How does a robot\u27s body affect what it can do? This thesis explores the question with respect to a body morphology common to biology but rare in contemporary robotics: the presence of a bendable back. In this document, we introduce the Canid and Inu quadrupedal robots designed to test hypotheses related to the presence of a robotic sagittal-plane bending back (which we refer to as a ``spine morphology\u27\u27). The thesis then describes and quantifies several advantages afforded by this morphological design choice that can be evaluated against its added weight and complexity, and proposes control strategies to both deal with the increase in degrees-of-freedom from the spine morphology and to leverage an increase in agility to reactively navigate irregular terrain. Specifically, we show using the metric of ``specific agility\u27\u27 that a spine can provides a reservoir of elastic energy storage that can be rapidly converted to kinetic energy, that a spine can augment the effective workspace of the legs without diminishing their force generation capability, and that -- in cases of direct-drive or nearly direct-drive leg actuation -- the spine motors can contribute more work in stance than the same actuator weight used in the legs, but can do so without diminishing the platform\u27s proprioceptive capabilities. To put to use the agility provided by a suitably designed robotic platform, we introduce a formalism to approximate a set of transitional navigational tasks over irregular terrain such as leaping over a gap that lend itself to doubly reactive control synthesis. We also directly address the increased complexity introduced by the spine joint with a modular compositional control framework with nice stability properties that begins to offer insight into the role of spines for steady-state running. A central theme to both the reactive navigation and the modular control frameworks is that analytical tractability is achieved by approximating the modes driving the environmental interactions with constant-acceleration dynamics