Proprioception Based Behavioral Advances in a Hexapod Robot

We report on our progress in extending the behavioral repertoire of RHex, a compliant leg hexapod robot. We introduce two new controllers, one for climbing constant slope inclinations and one for achieving higher speeds via pronking, a gait that incorporates a, substantial aerial phase. In both cases, we make use of an underlying open-loop control strategy, combined with low bandwidth feedback to modulate its parameters. The inclination behavior arises from our initial alternating tripod walking controller and adjusts the angle offsets of individual leg motion profiles based on inertial sensing of the average surface slope. Similarly, the pronking controller makes use of a virtual leg touchdown sensing mechanism to adjust the frequency of the open-loop pronking, effectively synchronizing the controller with the natural oscillations of the mechanical system. Experimental results demonstrate good performance on slopes inclined up to /spl sim/250 and pronking up to speeds approaching 2 body lengths per second (/spl sim/1.0 m/s)

Characterization of Dynamic Behaviors in a Hexapod Robot

This paper investigates the relationship between energetic effi- ciency and the dynamical structure of a legged robot’s gait. We present an experimental data set collected from an untethered dynamic hexapod, EduBot [1] (a RHex-class [2] machine), operating in four distinct manually selected gaits. We study the robot’s single tripod stance dynamics of the robot which are identified by a purely jointspace-driven estimation method introduced in this paper. Our results establish a strong relationship between energetic efficiency (simultaneous reduction in power consumption and in- crease in speed) and the dynamical structure of an alternating tripod gait as measured by its fidelity to the SLIP mechanics—a dynamical pattern exhibit- ing characteristic exchanges of kinetic and spring-like potential energy [3]. We conclude that gaits that are dynamic in this manner give rise to better uti- lization of energy for the purposes of locomotion. This work is supported in part by the National Science Foundation (NSF) under a FIBR Award 0425878. Yasemin Ozkan Aydin is supported by International Research Fellowship Programme of the Scientific and Technological Research Council of Turkey (TUBITAK). For more information: Kod*La

Dynamic Legged Mobility---an Overview

Ability to translate to a goal position under the constrains imposed by complex environmental conditions is a key capability for biological and artificial systems alike. Over billions of years evolutionary processes have developed a wide range of solutions to address mobility needs in air, in water and on land. The efficacy of such biological locomotors is beyond the capabilities of engineering solutions that has been produced to this date. Nature has been and will surely remain to be a source of inspiration for engineers in their quest to bring real mobility to their creations. In recent years a new class of dynamic legged terrestrial robotic systems \cite{Autumn-Buehler-Cutkosky.SPIE2005,Raibert.Book1986,Raibert-Blankesport-Nelson.IFAC2008,Saranli-Buehler-Koditschek.IJRR2001} have been developed inspired by, but without mimicking, the examples from the Nature. The experimental work with these platforms over the past decade has led to an improved appreciation of legged locomotion. This paper is an overview of fundamental advantages dynamic legged locomotion offers over the classical wheeled and tracked approaches

Classification and Identification of Environment Through Dynamic Coupling

This paper presents a methodology enabling robotic systems to classify and identify their environment according to the mechanical properties of the local contact dynamics. Described approach employs existing proprioceptive sensors and requires no additional specialized hardware. Identification process is performed in real-time with temporal resolution of measurement updates determined by the periodicity of the limit behavior. While the basic concept has a wide application spectrum, our discussion focuses on terrestrial locomotion where contact properties, such a compliance, damping, sheer friction and surface topology, are important environmental markers. Accurate identification of environmental parameters enables two types of applications. In behavioral control, availability of measurements on environmental parameterization can facilitate better adaptation of actuation strategy. In localization and map building applications, such mechanical characteristics of the environment, which are typically hard to attain, can serve as a new set of classifiers. Presented approach is founded on the observation that locomotive behaviors, and particularly the dynamic ones, emerge from the interaction between the active actuation actions of the mechanism with its environment. To evaluate our concept in a systematic fashion we constructed a simplified numerical model of a dynamic hexapod robot. We present results on numerical simulations and outline a path for a physical implementation on dynamic hexapod robot

Autonomous Legged Hill and Stairwell Ascent

This paper documents near-autonomous negotiation of synthetic and natural climbing terrain by a rugged legged robot, achieved through sequential composition of appropriate perceptually triggered locomotion primitives. The first, simple composition achieves autonomous uphill climbs in unstructured outdoor terrain while avoiding surrounding obstacles such as trees and bushes. The second, slightly more complex composition achieves autonomous stairwell climbing in a variety of different buildings. In both cases, the intrinsic motor competence of the legged platform requires only small amounts of sensory information to yield near-complete autonomy. Both of these behaviors were developed using X-RHex, a new revision of RHex that is a laboratory on legs, allowing a style of rapid development of sensorimotor tasks with a convenience near to that of conducting experiments on a lab bench. Applications of this work include urban search and rescue as well as reconnaissance operations in which robust yet simple-to-implement autonomy allows a robot access to difficult environments with little burden to a human operator

Integrative Biomimetics of Autonomous Hexapedal Locomotion

Dürr V, Arena PP, Cruse H, et al. Integrative Biomimetics of Autonomous Hexapedal Locomotion. Frontiers in Neurorobotics. 2019;13: 88.Despite substantial advances in many different fields of neurorobotics in general, and biomimetic robots in particular, a key challenge is the integration of concepts: to collate and combine research on disparate and conceptually disjunct research areas in the neurosciences and engineering sciences. We claim that the development of suitable robotic integration platforms is of particular relevance to make such integration of concepts work in practice. Here, we provide an example for a hexapod robotic integration platform for autonomous locomotion. In a sequence of six focus sections dealing with aspects of intelligent, embodied motor control in insects and multipedal robots—ranging from compliant actuation, distributed proprioception and control of multiple legs, the formation of internal representations to the use of an internal body model—we introduce the walking robot HECTOR as a research platform for integrative biomimetics of hexapedal locomotion. Owing to its 18 highly sensorized, compliant actuators, light-weight exoskeleton, distributed and expandable hardware architecture, and an appropriate dynamic simulation framework, HECTOR offers many opportunities to integrate research effort across biomimetics research on actuation, sensory-motor feedback, inter-leg coordination, and cognitive abilities such as motion planning and learning of its own body size

A Leg Configuration Measurement System for Full-Body Pose Estimates in a Hexapod Robot

We report on a continuous-time rigid-body pose estimator for a walking hexapod robot. Assuming at least three legs remain in ground contact at all times, our algorithm uses the outputs of six leg-configuration sensor models together with a priori knowledge of the ground and robot kinematics to compute instantaneous estimates of the 6-degrees-of-freedom (6-DOF) body pose. We implement this estimation procedure on the robot RHex by means of a novel sensory system incorporating a model relating compliant leg member strain to leg configuration delivered to the onboard CPU over a customized cheap high-performance local wireless network. We evaluate the performance of this algorithm at widely varying body speeds and over dramatically different ground conditions by means of a 6-DOF vision-based ground-truth measurement system (GTMS). We also compare the odometry performance to that of sensorless schemes—both legged as well as on a wheeled version of the robot—using GTMS measurements of elapsed distance

Robots as Powerful Allies for the Study of Embodied Cognition from the Bottom Up

A large body of compelling evidence has been accumulated demonstrating that embodiment – the agent’s physical setup, including its shape, materials, sensors and actuators – is constitutive for any form of cognition and as a consequence, models of cognition need to be embodied. In contrast to methods from empirical sciences to study cognition, robots can be freely manipulated and virtually all key variables of their embodiment and control programs can be systematically varied. As such, they provide an extremely powerful tool of investigation. We present a robotic bottom-up or developmental approach, focusing on three stages: (a) low-level behaviors like walking and reflexes, (b) learning regularities in sensorimotor spaces, and (c) human-like cognition. We also show that robotic based research is not only a productive path to deepening our understanding of cognition, but that robots can strongly benefit from human-like cognition in order to become more autonomous, robust, resilient, and safe