Advancing Musculoskeletal Robot Design for Dynamic and Energy-Efficient Bipedal Locomotion

Achieving bipedal robot locomotion performance that approaches human performance is a challenging research topic in the field of humanoid robotics, requiring interdisciplinary expertise from various disciplines, including neuroscience and biomechanics. Despite the remarkable results demonstrated by current humanoid robots---they can walk, stand, turn, climb stairs, carry a load, push a cart---the versatility, stability, and energy efficiency of humans have not yet been achieved. However, with robots entering our lives, whether in the workplace, in clinics, or in normal household environments, such improvements are increasingly important. The current state of research in bipedal robot locomotion reveals that several groups have continuously demonstrated enhanced locomotion performance of the developed robots. But each of these groups has taken a unilateral approach and placed the focus on only one aspect, in order to achieve enhanced movement abilities;---for instance, the motion control and postural stability or the mechanical design. The neural and mechanical systems in human and animal locomotion, however, are strongly coupled and should therefore not be treated separately. Human-inspired musculoskeletal design of bipedal robots offers great potential for enhanced dynamic and energy-efficient locomotion but also imposes major challenges for motion planning and control. In this thesis, we first present a detailed review of the problems related to achieving enhanced dynamic and energy-efficient bipedal locomotion, from various important perspectives, and examine the essential properties of the human locomotory apparatus. Subsequently, existing insights and approaches from biomechanics, to understand the neuromechanical motion apparatus, and from robotics, to develop more human-like robots that can move in our environment, are discussed in detail. These thorough investigations of the interrelated essential design decisions are used to develop a novel design for a musculoskeletal bipedal robot, BioBiped1, such that, in the long term, it is capable of realizing dynamic hopping, running, and walking motions. The BioBiped1 robot features a highly compliant tendon-driven actuation system that mimics key functionalities of the human lower limb system. In experiments, BioBiped1's locomotor function for the envisioned gaits is validated globally. It is shown that the robot is able to rebound passively, store and release energy, and actively push off from the ground. The proof of concept of BioBiped1's locomotor function, however, marks only the starting point for our investigations, since this novel design concept opens up a number of questions regarding the required design complexity for the envisioned motions and the appropriate motion generation and control concept. For this purpose, a simulator specifically designed for the requirements of musculoskeletally actuated robotic systems, including sufficiently realistic ground reaction forces, is developed. It relies on object-oriented design and is based on a numerical solver, without model switching, to enable the analysis of impact peak forces and the simulation of flight phases. The developed library also contains the models of the actuated and passive mono- and biarticular elastic tendons and a penalty-based compliant contact model with nonlinear damping, to incorporate the collision, friction, and stiction forces occurring during ground contact. Using these components, the full multibody system (MBS) dynamics model is developed. To ensure a sufficiently similar behavior of the simulated and the real musculoskeletal robot, various measurements and parameter identifications for sub-models are performed. Finally, it is shown that the simulation model behaves similarly to the real robot platform. The intelligent combination of actuated and passive mono- and biarticular tendons, imitating important human muscle groups, offers tremendous potential for improved locomotion performance but also requires a sophisticated concept for motion control of the robot. Therefore, a further contribution of this thesis is the development of a centralized, nonlinear model-based method for motion generation and control that utilizes the derived detailed dynamics models of the implemented actuators. The concept is used to realize both computer-generated hopping and human jogging motions. Additionally, the problem of appropriate motor-gear unit selection prior to the robot's construction is tackled, using this method. The thesis concludes with a number of simulation studies in which several leg actuation designs are examined for their optimality with regard to systematically selected performance criteria. Furthermore, earlier paradoxical biomechanical findings about biarticular muscles in running are presented and, for the first time, investigated by detailed simulation of the motion dynamics. Exploring the Lombard paradox, a novel reduced and energy-efficient locomotion model without knee extensor has been simulated successfully. The models and methods developed within this thesis, as well as the insights gained, are already being employed to develop future prototypes. In particular, the optimal dimensioning and setting of the actuators, including all mono- and biarticular muscle-tendon units, are based on the derived design guidelines and are extensively validated by means of the simulation models and the motion control method. These developments are expected to significantly enhance progress in the field of bipedal robot design and, in the long term, to drive improvements in rehabilitation for humans through an understanding of the neuromechanics underlying human walking and the application of this knowledge to the design of prosthetics

A new biarticular actuator design facilitates control of leg function in BioBiped3

Bioinspired legged locomotion comprises different aspects, such as (i) benefiting from reduced complexity control approaches as observed in humans/animals, (ii) combining embodiment with the controllers and (iii) reflecting neural control mechanisms. One of the most important lessons learned from nature is the significant role of compliance in simplifying control, enhancing energy efficiency and robustness against perturbations for legged locomotion. In this research, we investigate how body morphology in combination with actuator design may facilitate motor control of leg function. Inspired by the human leg muscular system, we show that biarticular muscles have a key role in balancing the upper body, joint coordination and swing leg control. Appropriate adjustment of biarticular spring rest length and stiffness can simplify the control and also reduce energy consumption. In order to test these findings, the BioBiped3 robot was developed as a new version of BioBiped series of biologically inspired, compliant musculoskeletal robots. In this robot, three-segmented legs actuated by mono- and biarticular series elastic actuators mimic the nine major human leg muscle groups. With the new biarticular actuators in BioBiped3, novel simplified control concepts for postural balance and for joint coordination in rebounding movements (drop jumps) were demonstrated and approved

Bioinspired template-based control of legged locomotion

cient and robust locomotion is a crucial condition for the more extensive use of legged robots in real world applications. In that respect, robots can learn from animals, if the principles underlying locomotion in biological legged systems can be transferred to their artificial counterparts. However, legged locomotion in biological systems is a complex and not fully understood problem. A great progress to simplify understanding locomotion dynamics and control was made by introducing simple models, coined ``templates'', able to represent the overall dynamics of animal (including human) gaits. One of the most recognized models is the spring-loaded inverted pendulum (SLIP) which consists of a point mass atop a massless spring. This model provides a good description of human gaits, such as walking, hopping and running. Despite its high level of abstraction, it supported and inspired the development of successful legged robots and was used as explicit targets for control, over the years. Inspired from template models explaining biological locomotory systems and Raibert's pioneering legged robots, locomotion can be realized by basic subfunctions: (i) stance leg function, (ii) leg swinging and (iii) balancing. Combinations of these three subfunctions can generate different gaits with diverse properties. Using the template models, we investigate how locomotor subfunctions contribute to stabilize different gaits (hopping, running and walking) in different conditions (e.g., speeds). We show that such basic analysis on human locomotion using conceptual models can result in developing new methods in design and control of legged systems like humanoid robots and assistive devices (exoskeletons, orthoses and prostheses). This thesis comprises research in different disciplines: biomechanics, robotics and control. These disciplines are required to do human experiments and data analysis, modeling of locomotory systems, and implementation on robots and an exoskeleton. We benefited from facilities and experiments performed in the Lauflabor locomotion laboratory. Modeling includes two categories: conceptual (template-based, e.g. SLIP) models and detailed models (with segmented legs, masses/inertias). Using the BioBiped series of robots (and the detailed BioBiped MBS models; MBS stands for Multi-Body-System), we have implemented newly-developed design and control methods related to the concept of locomotor subfunctions on either MBS models or on the robot directly. In addition, with involvement in BALANCE project (\url{http://balance-fp7.eu/}), we implemented balance-related control approaches on an exoskeleton to demonstrate their performance in human walking. The outcomes of this research includes developing new conceptual models of legged locomotion, analysis of human locomotion based on the newly developed models following the locomotor subfunction trilogy, developing methods to benefit from the models in design and control of robots and exoskeletons. The main contribution of this work is providing a novel approach for modular control of legged locomotion. With this approach we can identify the relation between different locomotor subfunctions e.g., between balance and stance (using stance force for tuning balance control) or balance and swing (two joint hip muscles can support the swing leg control relating it to the upper body posture) and implement the concept of modular control based on locomotor subfunctions with a limited exchange of sensory information on several hardware platforms (legged robots, exoskeleton)

Muscle‐Like Compliance in Knee Articulations Improves Biped Robot Walkings

This chapter focuses on the compliance effect of dynamic humanoid robot walking. This compliance is generated with an articular muscle emulator system, which is designed using two neural networks (NNs). One NN models a muscle and a second learns to tune the proportional integral derivative (PID) of the articulation DC motor, allowing it to behave analogously to the muscle model. Muscle emulators are implemented in the knees of a three‐dimensional (3D) simulated biped robot. The simulation results show that the muscle emulator creates compliance in articulations and that the dynamic walk, even in walk‐halt‐stop transitions, improves. If an external thrust unbalances the biped during the walk, the muscle emulator improves the control and prevents the robot from falling. The total power consumption is significantly reduced, and the articular trajectories approach human trajectories

The Poppy Humanoid Robot: Leg Design for Biped Locomotion

International audienceWe introduce a novel humanoid robotic platform designed to jointly address three central goals of humanoid robotics: 1) study the role of morphology in biped locomotion; 2) study full-body compliant physical human-robot interaction; 3) be robust while easy and fast to duplicate to facilitate experimentation. The taken approach relies on functional modeling of certain aspects of human morphology, optimizing materials and geometry, as well as on the use of 3D printing techniques. In this article, we focus on the presentation of the design of specific morphological parts related to biped locomotion: the hip, the thigh, the limb mesh and the knee. We present initial experiments showing properties of the robot when walking with the physical guidance of a human

Towards understanding human locomotion

Die zentrale Frage, die in der vorliegenden Arbeit untersucht wurde, ist, wie man die komplizierte Dynamik des menschlichen Laufens besser verstehen kann. In der wissenschaftlichen Literatur werden zur Beschreibung von Laufbewegungen (Gehen und Rennen) oftmals minimalistische "Template"-Modelle verwendet. Diese sehr einfachen Modelle beschreiben nur einen ausgewählten Teil der Dynamik, meistens die Schwerpunktsbahn. In dieser Arbeit wird nun versucht, mittels Template-Modellen das Verständnis des Laufens voranzubringen. Die Analyse der Schwerpunktsbewegung durch Template-Modelle setzt eine präzise Bestimmung der Schwerpunktsbahn im Experiment voraus. Hierfür wird in Kapitel 2.3 eine neue Methode vorgestellt, welche besonders robust gegen die typischen Messfehler bei Laufexperimenten ist. Die am häfigsten verwendeten Template-Modelle sind das Masse-Feder-Modell und das inverse Pendel, welche zur Beschreibung der Körperschwerpunktsbewegung gedacht sind und das Drehmoment um den Schwerpunkt vernachlässigen. Zur Beschreibung der Stabilisierung der Körperhaltung (und damit der Drehimpulsbilanz) wird in Abschnitt 3.3 das Template-Modell "virtuelles Pendel" für das menschliche Gehen eingeführt und mit experimentellen Daten verglichen. Die Diskussion möglicher Realisierungsmechanismen legt dabei nahe, dass die Aufrichtung des menschlichen Gangs im Laufe der Evolution keine große mechanische Hürde war. In der Literatur wird oft versucht, Eigenschaften der Bewegung wie Stabilität durch Eigenschaften der Template-Modelle zu erklären. Dies wird in modifizierter Form auch in der vorliegen Arbeit getan. Hierzu wird zunächst eine experimentell bestimmte Schwerpunktsbewegung auf das Masse-Feder-Modell übertragen. Anschließend wird die Kontrollvorschrift der Schritt-zu-Schritt-Anpassung der Modellparameter identifiziert sowie eine geeignete Näherung angegeben, um die Stabilität des Modells, welches mit dieser Kontrollvorschrift ausgestattet wird, zu analysieren. Der Vergleich mit einer direkten Bestimmung der Stabilität aus einem Floquet-Modell zeigt qualitativ gute Übereinstimmung. Beide Ansätze führen auf das Ergebnis, dass beim langsamen menschlichen Rennen Störungen innerhalb von zwei Schritten weitgehend abgebaut werden. Zusammenfassend wurde gezeigt, wie Template-Modelle zum Verständnis der Laufbewegung beitragen können. Gerade die Identifikation der individuellen Kontrollvorschrift auf der Abstraktionsebene des Masse-Feder-Modells erlaubt zukünftig neue Wege, aktive Prothesen oder Orthesen in menschenähnlicher Weise zu steuern und ebnet den Weg, menschliches Rennen auf Roboter zu übertragen.Human locomotion is part of our everyday life, however the mechanisms are not well enough understood to be transferred into technical devices like orthoses, protheses or humanoid robots. In biomechanics often minimalistic so-called template models are used to describe locomotion. While these abstract models in principle offer a language to describe both human behavior and technical control input, the relation between human locomotion and locomotion of these templates was long unclear. This thesis focusses on how human locomotion can be described and analyzed using template models. Often, human running is described using the SLIP template. Here, it is shown that SLIP (possibly equipped with any controller) cannot show human-like disturbance reactions, and an appropriate extension of SLIP is proposed. Further, a new template to describe postural stabilization is proposed. Summarizing, this theses shows how simple template models can be used to enhance the understanding of human gait

A Systematic Approach to the Design of Embodiment with Application to Bio-Inspired Compliant Legged Robots

Bio-inspired legged robots with compliant actuation can potentially achieve motion properties in real world scenarios which are superior to conventionally actuated robots. In this thesis, a methodology is presented to systematically design and tailor passive and active control elements for elastically actuated robots. It is based on a formal specification of requirements derived from the main design principles for embodied agents as proposed by Pfeifer et al. which are transfered to dynamic model based multi objective optimization problems. The proposed approach is demonstrated and applied for the design of a biomechanically inspired, musculoskeletal bipedal robot to achieve walking and human-like jogging

Optimal elastic coupling in form of one mechanical spring to improve energy efficiency of walking bipedal robots

This paper presents a method to optimize the energy efficiency of walking bipedal robots by more than 80% in a speed range from 0.3 to 2.3 m/s using elastic couplings – mechanical springs with movement speed independent parameters. The considered planar robot consists of a trunk, two two-segmented legs, two actuators in the hip joints, two actuators in the knee joints and an elastic coupling between the shanks. It is modeled as underactuated system to make use of its natural dynamics and feedback controlled via input-output linearization. A numerical optimization of the joint angle trajectories as well as the elastic couplings is performed to minimize the average energy expenditure over the whole speed range. The elastic couplings increase the swing leg motion’s natural frequency thus making smaller steps more efficient which reduce the impact loss at the touchdown of the swing leg. The process of energy turnover is investigated in detail for the robot with and without elastic coupling between the shanks. Furthermore, the influences of the elastic couplings’ topology and of joint friction are analyzed. It is shown that the optimization of the robot’s motion and elastic coupling towards energy efficiency leads to a slightly slower convergence rate of the controller, yet no loss of stability but a lower sensitivity with respect to disturbances. The optimal elastic coupling discovered via numerical optimization is a linear torsion spring with transmissions between the shanks. A design proposal for this elastic coupling – which does not affect the robot’s trunk and parallel shank motion and can be used to enhance an existing robot – is given for planar as well as spatial robots

Common Dimensional Autoencoder for Learning Redundant Muscle-Posture Mappings of Complex Musculoskeletal Robots

It has been widely considered that a distinctive feature of musculoskeletal structures is that both the joint angle and stiffness can be changed by exploiting the agonistantagonist driving of the joint. However, musculoskeletal systems in animals and humans are typically highly complex, and the simple agonist-antagonist driving is rarely found. Therefore, in accordance with the increasing complexity of musculoskeletal robots, the feature that causes the robot to assume a posture with different stiffness values becomes difficult to achieve, owing to the difficulty in modeling the kinematics. Although datadriven approaches such as the neural network are regarded as suitable for modeling complex relationships, the training data are difficult to obtain because measuring joint stiffness is typically extremely difficult in contrast to measuring an actuator\u27s state and posture. Hence, we herein propose the common dimensional autoencoder where the encoded feature exhibits identical dimensions to the original input vector. In the proposed network, in parallel with the original unsupervised training using the data of the actuators\u27 states, supervised training at part of the encoded features is performed using posture data. Consequently, features expressing the redundancy of inverse kinematics appear at the remaining part of the encoded features without using data such as joint stiffness. The validity of the proposed method was confirmed successfully through an experiment using a 10 degrees-of-freedom complex musculoskeletal robot arm driven by pneumatic artificial muscles.IEEE/RSJ International Conference on Intelligent Robots and Systems (iROS2019), November 4 - 8, 2019, Macau, Chin