40 research outputs found
Benchmarking and Validation for Nonlinear Mode Analysis
One research focus at the Robotics and Mechatronics Center of the German Aerospace Center in Oberpfaffenhofen is the improvement of robotic locomotion capabilities. Therefore, natural role models are analyzed. As an inspiration, mammalian locomotion is analyzed, which is unmatched in its energy efficiency and adaptility due to the opitmal integration of control strategies and intrinsic body dynamics. In an attempt to recreate this integration in robotic hardware, the compliant quadruped Bert has been developed and built as a test platform. As a contribution towards this goal, this thesis investigates the excitation of nonlinear intrinsic motions of one individual leg of the robot Bert. Springs in the joints of the leg enable dynamic motions. As first approach to model the individual leg in Matlab for the controller design process, an elastic double pendulum is set up. This is followed by the consideration of different modelling methods such as the Pfaffian constraints method and the active joints method. These methods lead to a leg model. For the analysis of the intrinsic dynamics, the concept of nonlinear normal modes is used which was recently explored and published by the German Aerospace Center. After the nonlinear normal modes for the leg are computed, the influence of parameter variation on the shapes of manifold and generators is evaluated. Subsequently, a nonlinear normal mode is found that is a prominate candidate to excite an energy efficient hopping motion in the oneleg of Bert. To initialize and stabilize the modal oscillation, a position mode controller is evolved from an existing torque mode controller. After the control framework is set up, tests are performed in the 3D physics simulation software Gazebo with a digital twin of the Bert leg. The experiments showed that some modifications will be needed for the implementation of the developed position controller to work on the real hardware of the Bert leg. Nevertheless, the simulation experiments also showed that the controller is capable
to stabilize modal oscillations with little control effort in an idealized system proving the
developed control strategy to be highly energy efficient. As a result, this thesis takes another
step towards the use of intrinsic system dynamics in the field of robotics based on
natural role models
Biomimetic Based Applications
The interaction between cells, tissues and biomaterial surfaces are the highlights of the book "Biomimetic Based Applications". In this regard the effect of nanostructures and nanotopographies and their effect on the development of a new generation of biomaterials including advanced multifunctional scaffolds for tissue engineering are discussed. The 2 volumes contain articles that cover a wide spectrum of subject matter such as different aspects of the development of scaffolds and coatings with enhanced performance and bioactivity, including investigations of material surface-cell interactions
Climbing and Walking Robots
With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information
Artifacts, Others, and Temporality: An Enactive and Phenomenological Approach to Material Agency
Artifacts, Others, and Temporality: An Enactive and Phenomenological Approach to Material Agenc
Computational Methods for Cognitive and Cooperative Robotics
In the last decades design methods in control engineering made substantial progress in
the areas of robotics and computer animation. Nowadays these methods incorporate the
newest developments in machine learning and artificial intelligence. But the problems
of flexible and online-adaptive combinations of motor behaviors remain challenging for
human-like animations and for humanoid robotics. In this context, biologically-motivated
methods for the analysis and re-synthesis of human motor programs provide new insights
in and models for the anticipatory motion synthesis.
This thesis presents the authorâs achievements in the areas of cognitive and developmental robotics, cooperative and humanoid robotics and intelligent and machine learning methods in computer graphics. The first part of the thesis in the chapter âGoal-directed Imitation for Robotsâ considers imitation learning in cognitive and developmental robotics.
The work presented here details the authorâs progress in the development of hierarchical
motion recognition and planning inspired by recent discoveries of the functions of mirror-neuron cortical circuits in primates. The overall architecture is capable of âlearning for
imitationâ and âlearning by imitationâ. The complete system includes a low-level real-time
capable path planning subsystem for obstacle avoidance during arm reaching. The learning-based path planning subsystem is universal for all types of anthropomorphic robot arms, and is capable of knowledge transfer at the level of individual motor acts.
Next, the problems of learning and synthesis of motor synergies, the spatial and spatio-temporal combinations of motor features in sequential multi-action behavior, and the
problems of task-related action transitions are considered in the second part of the thesis
âKinematic Motion Synthesis for Computer Graphics and Roboticsâ. In this part, a new
approach of modeling complex full-body human actions by mixtures of time-shift invariant
motor primitives in presented. The online-capable full-body motion generation architecture
based on dynamic movement primitives driving the time-shift invariant motor synergies
was implemented as an online-reactive adaptive motion synthesis for computer graphics
and robotics applications.
The last chapter of the thesis entitled âContraction Theory and Self-organized Scenarios
in Computer Graphics and Roboticsâ is dedicated to optimal control strategies in multi-agent scenarios of large crowds of agents expressing highly nonlinear behaviors. This last
part presents new mathematical tools for stability analysis and synthesis of multi-agent
cooperative scenarios.In den letzten Jahrzehnten hat die Forschung in den Bereichen der Steuerung und Regelung
komplexer Systeme erhebliche Fortschritte gemacht, insbesondere in den Bereichen
Robotik und Computeranimation. Die Entwicklung solcher Systeme verwendet heutzutage
neueste Methoden und Entwicklungen im Bereich des maschinellen Lernens und der
kĂŒnstlichen Intelligenz. Die flexible und echtzeitfĂ€hige Kombination von motorischen Verhaltensweisen
ist eine wesentliche Herausforderung fĂŒr die Generierung menschenĂ€hnlicher
Animationen und in der humanoiden Robotik. In diesem Zusammenhang liefern biologisch
motivierte Methoden zur Analyse und Resynthese menschlicher motorischer Programme
neue Erkenntnisse und Modelle fĂŒr die antizipatorische Bewegungssynthese.
Diese Dissertation prÀsentiert die Ergebnisse der Arbeiten des Autors im Gebiet der
kognitiven und Entwicklungsrobotik, kooperativer und humanoider Robotersysteme sowie
intelligenter und maschineller Lernmethoden in der Computergrafik. Der erste Teil der
Dissertation im Kapitel âZielgerichtete Nachahmung fĂŒr Roboterâ behandelt das Imitationslernen
in der kognitiven und Entwicklungsrobotik. Die vorgestellten Arbeiten beschreiben
neue Methoden fĂŒr die hierarchische Bewegungserkennung und -planung, die durch
Erkenntnisse zur Funktion der kortikalen Spiegelneuronen-Schaltkreise bei Primaten inspiriert
wurden. Die entwickelte Architektur ist in der Lage, âdurch Imitation zu lernenâ
und âzu lernen zu imitierenâ. Das komplette entwickelte System enthĂ€lt ein echtzeitfĂ€higes
Pfadplanungssubsystem zur Hindernisvermeidung wĂ€hrend der DurchfĂŒhrung von Armbewegungen.
Das lernbasierte Pfadplanungssubsystem ist universell und fĂŒr alle Arten von
anthropomorphen Roboterarmen in der Lage, Wissen auf der Ebene einzelner motorischer
Handlungen zu ĂŒbertragen.
Im zweiten Teil der Arbeit âKinematische Bewegungssynthese fĂŒr Computergrafik und
Robotikâ werden die Probleme des Lernens und der Synthese motorischer Synergien, d.h.
von rÀumlichen und rÀumlich-zeitlichen Kombinationen motorischer Bewegungselemente
bei Bewegungssequenzen und bei aufgabenbezogenen Handlungs ĂŒbergĂ€ngen behandelt.
Es wird ein neuer Ansatz zur Modellierung komplexer menschlicher Ganzkörperaktionen
durch Mischungen von zeitverschiebungsinvarianten Motorprimitiven vorgestellt. Zudem
wurde ein online-fĂ€higer Synthesealgorithmus fĂŒr Ganzköperbewegungen entwickelt, der
auf dynamischen Bewegungsprimitiven basiert, die wiederum auf der Basis der gelernten
verschiebungsinvarianten Primitive konstruiert werden. Dieser Algorithmus wurde fĂŒr
verschiedene Probleme der Bewegungssynthese fĂŒr die Computergrafik- und Roboteranwendungen
implementiert.
Das letzte Kapitel der Dissertation mit dem Titel âKontraktionstheorie und selbstorganisierte
Szenarien in der Computergrafik und Robotikâ widmet sich optimalen Kontrollstrategien
in Multi-Agenten-Szenarien, wobei die Agenten durch eine hochgradig nichtlineare
Kinematik gekennzeichnet sind. Dieser letzte Teil prÀsentiert neue mathematische Werkzeuge
fĂŒr die StabilitĂ€tsanalyse und Synthese von kooperativen Multi-Agenten-Szenarien
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On the discretisation of actuation in locomotion: Impulse- and shape-based modelling for hopping robots
In an age where computers challenge the smartest human beings in cognitive tasks, the
conspicuous discrepancy between robot and animal locomotion appears paradoxical. While
animals can move around autonomously in complex environments, todayâs robots struggle
to independently operate in such surroundings. There are many reasons for robotsâ inferior
performance, but arguably the most important one is our missing understanding of complexity.
This thesis introduces the notion of discrete actuation for the study of locomotion in
robots and animals. The actuation of a system with discrete actuation is restricted to be
applied at a finite number of instants in time and is impulsive. We find that, despite their
simplicity, such systems can predict various experimental observations and inspire novel
technologies for robot design and control. We further find that, through the study of discrete
actuation, causal relationships between actuation and resulting behaviour are revealed and
become quantifiable, which relates the findings presented in this thesis to the broader concepts
of complexity, self-organisation, and self-stability.
We present four case studies in Chapters 3-6 which demonstrate how the concept of
discrete actuation can be employed to understand the physics of locomotion and to facilitate
novel robot technologies. We first introduce the impulsive eccentric wheel model which is
a discretely actuated system for the study of hopping locomotion. We find that the model
predicts robot hopping trajectories and animal related hopping characteristics by reducing the
dynamics of hoppingâusually described by hybrid differential equationsâto analytic maps.
The reduction of complexity of the model equations reveals the underlying physics of the
locomotion process, and we identify the importance of robot shape and mass distribution
for the locomotion performance. As a concrete application of the model, we compare the
energetics of hopping and rolling locomotion in environments with obstacles and find when
it is better to hop than to roll, based on the fundamental physical principles we discover in
the model analysis. The theoretical insights of this modelling approach enable new actuation
techniques and design for robots which we display in Robbit; a robot that uses strictly convex
foot shapes and rotational impulses to induce hopping locomotion. We show that such
systems outperform hopping with non-strictly convex shapes in terms of energy effective and robust locomotion. A system with discrete actuation motivates the exploitation of shape
and the environment to improve locomotion dynamics, which reveals advantageous effect
of inelastic impacts between the robot foot and the environment. We support this idea with
experimental results from the robot CaneBot which can change its foot shape to induce timed
impacts with the environment. Even though inelastic impacts are commonly considered
detrimental for locomotion dynamics, we show that their appropriate control improves the
locomotion speed considerably.
The findings presented in this thesis show that discrete actuation for locomotion inspires
novel ways to appreciate locomotion dynamics and facilitates unique control and design
technologies for robots. Furthermore, discrete actuation emphasises the definition of causality
in complex systems which we believe will bring robots closer to the locomotion behaviour of
animals, enabling more agile and energy effective robots
Afferent information modulates spinal network activity in vitro and in preclinical animal models
Primary afferents are responsible for the transmission of peripheral sensory information to the spinal cord. Spinal circuits involved in sensory processing and in motor activity are directly modulated by incoming input conveyed by afferent fibres. Current neurorehabilitation exploits primary afferent information to induce plastic changes within lesioned spinal circuitries. Plasticity and neuromodulation promoted by activity-based interventions are suggested to support both the functional recovery of locomotion and pain relief in subjects with sensorimotor disorders. The present study was aimed at assessing spinal modifications mediated by afferent information.
At the beginning of my PhD project, I adopted a simplified in vitro model of isolated spinal cord from the newborn rat. In this preparation, dorsal root (DR) fibres were repetitively activated by delivering trains of electrical stimuli. Responses of dorsal sensory-related and ventral motor-related circuits were assessed by extracellular recordings. I demonstrated that electrostimulation protocols able to activate the spinal CPG for locomotion, induced primary afferent hyperexcitability, as well. Thus, evidence of incoming signals in modulating spinal circuits was provided. Furthermore, a robust sensorimotor interplay was reported to take place within the spinal cord.
I further investigated hyperexcitability conditions in a new in vivo model of peripheral neuropathic pain. Adult rats underwent a surgical procedure where the common peroneal nerve was crushed using a calibrated nerve clamp (modified spared nerve injury, mSNI). Thus, primary afferents of the common peroneal nerve were activated through the application of a noxious compression, which presumably elicited ectopic activity constitutively generated in the periphery. One week after surgery, animals were classified into two groups, with (mSNI+) and without (mSNI-) tactile hypersensitivity, based on behavioral tests assessing paw withdrawal threshold. Interestingly, the efficiency of the mSNI in inducing tactile hypersensitivity was halved with respect to the classical SNI model. Moreover, mSNI animals with tactile hypersensitivity (mSNI+) showed an extensive neuroinflammation within the dorsal horn, with activated microglia and astrocytes being significantly increased with respect to mSNI animals without tactile hypersensitivity (mSNI-) and to sham-operated animals. Lastly, RGS4 (regulator of G protein signaling 4) was reported to be enhanced in lumbar dorsal root ganglia (DRGs) and dorsal horn ipsilaterally to the lesion in mSNI+ animals. Thus, a new molecular marker was demonstrated to be involved in tactile hypersensitivity in our preclinical model of mSNI.
Lastly, we developed a novel in vitro model of newborn rat, where hindlimbs were functionally connected to a partially dissected spinal cord and passively-driven by a robotic device (Bipedal Induced Kinetic Exercise, BIKE). I aimed at studying whether spinal activity was influenced by afferent signals evoked during passive cycling. I first demonstrated that BIKE could actually evoke an afferent feedback from the periphery. Then, I determined that spinal circuitries were differentially affected by training sessions of different duration. On one side, a short exercise session could not directly activate the locomotor CPG, but was able to transiently facilitate an electrically-induced locomotor-like activity. Moreover, no changes in reflex or spontaneous activity of dorsal and ventral networks were promoted by a short training. On the other side, a long BIKE session caused a loss in facilitation of spinal locomotor networks and a depression in the area of motor reflexes. Furthermore, activity in dorsal circuits was long-term enhanced, with a significant increase in both electrically-evoked and spontaneous antidromic discharges. Thus, the persistence of training-mediated effects was different, with spinal locomotor circuits being only transiently modulated, whereas dorsal activity being strongly and stably enhanced. Motoneurons were also affected by a prolonged training, showing a reduction in membrane resistance and an increase in the frequency of post-synaptic currents (PSCs), with both fast- and slow-decaying synaptic inputs being augmented. Changes in synaptic transmission onto the motoneuron were suggested to be responsible for network effects mediated by passive training.
In conclusion, I demonstrated that afferent information might induce changes within the spinal cord, involving both neuronal and glial cells. In particular, spinal networks are affected by incoming peripheral signals, which mediate synaptic, cellular and molecular modifications. Moreover, a strong interplay between dorsal and ventral spinal circuits was also reported. A full comprehension of basic mechanisms underlying sensory-mediated spinal plasticity and bidirectional interactions between functionally different spinal networks might lead to the development of neurorehabilitation strategies which simultaneously promote locomotor recovery and pain relief
Advanced human inspired walking strategies for humanoid robots
Cette thĂšse traite du problĂšme de la locomotion des robots humanoĂŻdes dans le contexte du projet europĂ©en KoroiBot. En s'inspirant de l'ĂȘtre humain, l'objectif de ce projet est
l'amĂ©lioration des capacitĂ©s des robots humanoĂŻdes Ă se mouvoir de façon dynamique et polyvalente. Le coeur de l'approche scientifique repose sur l'utilisation du controle optimal, Ă la fois pour l'identification des couts optimisĂ©s par l'ĂȘtre humain et pour leur mise en oeuvre sur les robots des partenaires roboticiens. Cette thĂšse s'illustre donc par une collaboration Ă la fois avec des mathĂ©maticiens du contrĂŽle et des spĂ©cialistes de la modĂ©lisation des primitives motrices. Les contributions majeures de cette thĂšse reposent donc sur la conception de nouveaux algorithmes temps-rĂ©el de contrĂŽle pour la locomotion des robots humanoĂŻdes avec nos collĂ©gues de l'universitĂ© d'Heidelberg et leur intĂ©gration sur le robot HRP-2. Deux contrĂŽleurs seront prĂ©sentĂ©s, le premier permettant la locomotion multi-contacts avec une connaissance a priori des futures positions des contacts. Le deuxiĂšme Ă©tant une extension d'un travail rĂ©alisĂ© sur de la marche sur sol plat amĂ©liorant les performances et ajoutant des fonctionnalitĂ©es au prĂ©cĂ©dent algorithme. En collaborant avec des spĂ©cialistes du mouvement humain nous avons implementĂ© un contrĂŽleur innovant permettant de suivre des trajectoires cycliques du centre de masse. Nous prĂ©senterons aussi un contrĂŽleur corps-complet utilisant, pour le haut du corps, des primitives de mouvements extraites du mouvement humain et pour le bas du corps, un gĂ©nĂ©rateur de marche. Les rĂ©sultats de cette thĂšse ont Ă©tĂ© intĂ©grĂ©s dans la suite logicielle "Stack-of-Tasks" du LAAS-CNRS.This thesis covers the topic of humanoid robot locomotion in the frame of the European project KoroiBot. The goal of this project is to enhance the ability of humanoid robots
to walk in a dynamic and versatile fashion as humans do. Research and innovation studies in KoroiBot rely on optimal control methods both for the identification of cost
functions used by human being and for their implementations on robots owned by roboticist partners. Hence, this thesis includes fruitful collaborations with both control
mathematicians and experts in motion primitive modeling. The main contributions of this PhD thesis lies in the design of new real time controllers for humanoid robot locomotion
with our partners from the University of Heidelberg and their integration on the HRP-2 robot. Two controllers will be shown, one allowing multi-contact locomotion with a
prior knowledge of the future contacts. And the second is an extension of a previous work improving performance and providing additional functionalities. In a
collaboration with experts in human motion we designed an innovating controller for tracking cyclic trajectories of the center of mass. We also show a whole body controller
using upper body movement primitives extracted from human behavior and lower body movement computed by a walking pattern generator. The results of this thesis have been
integrated into the LAAS-CNRS "Stack-of-Tasks" software suit