Analytic and Learned Footstep Control for Robust Bipedal Walking

Bipedal walking is a complex, balance-critical whole-body motion with inherently unstable inverted pendulum-like dynamics. Strong disturbances must be quickly responded to by altering the walking motion and placing the next step in the right place at the right time. Unfortunately, the high number of degrees of freedom of the humanoid body makes the fast computation of well-placed steps a particularly challenging task. Sensor noise, imprecise actuation, and latency in the sensomotoric feedback loop impose further challenges when controlling real hardware. This dissertation addresses these challenges and describes a method of generating a robust walking motion for bipedal robots. Fast modification of footstep placement and timing allows agile control of the walking velocity and the absorption of strong disturbances. In a divide and conquer manner, the concepts of motion and balance are solved separately from each other, and consolidated in a way that a low-dimensional balance controller controls the timing and the footstep locations of a high-dimensional motion generator. Central pattern generated oscillatory motion signals are used for the synthesis of an open-loop stable walk on flat ground, which lacks the ability to respond to disturbances due to the absence of feedback. The Central Pattern Generator exhibits a low-dimensional parameter set to influence the timing and the landing coordinates of the swing foot. For balance control, a simple inverted pendulum-based physical model is used to represent the principal dynamics of walking. The model is robust to disturbances in a way that it returns to an ideal trajectory from a wide range of initial conditions by employing a combination of Zero Moment Point control, step timing, and foot placement strategies. The simulation of the model and its controller output are computed efficiently in closed form, supporting high-frequency balance control at the cost of an insignificant computational load. Additionally, the sagittal step size produced by the controller can be trained online during walking with a novel, gradient descent-based machine learning method. While the analytic controller forms the core of reliable walking, the trained sagittal step size complements the analytic controller in order to improve the overall walking performance. The balanced whole-body walking motion arises by using the footstep coordinates and the step timing predicted by the low-dimensional model as control input for the Central Pattern Generator. Real robot experiments are presented as evidence for disturbance-resistant, omnidirectional gait control, with arguably the strongest push-recovery capabilities to date

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, today’s robots struggle to independently operate in such surroundings. There are many reasons for robots’ 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 hopping–usually described by hybrid differential equations–to 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

Feasibility of Muscle Synergy Outcomes in Clinics, Robotics, and Sports: A Systematic Review

In the last years, several studies have been focused on understanding how the central nervous system controls muscles to perform a specific motor task. Although it still remains an open question, muscle synergies have come to be an appealing theory to explain the modular organization of the central nervous system. Even though the neural encoding of muscle synergies remains controversial, a large number of papers demonstrated that muscle synergies are robust across different tested conditions, which are within a day, between days, within a single subject and between subjects that have similar demographic characteristics. Thus, muscle synergy theory has been largely used in several research fields, such as clinics, robotics and sports. The present systematical review aims at providing an overview on the applications of muscle synergy theory in clinics, robotics and sports; in particular, the review is focused on the papers that provide tangible information for: (i) diagnosis or pathology assessment in clinics; (ii) robot-control design in robotics; and (iii) athletes’ performance assessment or training guidelines in sports

The mechanics of the contact phase in trampolining

During the takeoff for a trampoline skill the trampolinist should produce sufficient vertical velocity and angular momentum to permit the required skill to be completed in the aerial phase without excessive horizontal travel. The aim of this study was to investigate the optimum technique to produce forward somersault rotation. A seven-segment, subject-specific torque-driven computer simulation model of the takeoff in trampolining was developed in conjunction with a model of the reaction forces exerted on the trampolinist by the trampoline suspension system. The ankle, knee, hip, and shoulder joints were torque-driven, with the metatarsal-phalangeal and elbow joints angle-driven. Kinematic data of trampolining performances were obtained using a Vicon motion capture system. Segmental inertia parameters were calculated from anthropometric measurements. Viscoelastic parameters governing the trampoline were determined by matching an angle-driven model to the performance data. The torque-driven model was matched to the performance data by scaling joint torque parameters from the literature, and varying the activation parameters of the torque generators using a simulated annealing algorithm technique. The torque-driven model with the scaled isometric strength was evaluated by matching the performance data. The evaluation produced close agreement between the simulations and the performance, with an average difference of 4.4% across three forward rotating skills. The model was considered able to accurately represent the motion of a trampolinist in contact with a trampoline and was subsequently used to investigate optimal performance. Optimisations for maximum jump height for different somersaulting skills and maximum rotation potential produced increases in jump height of up to 14% and increases of rotation potential up to 15%. The optimised technique for rotation potential showed greater shoulder flexion during the recoil of the trampoline and for jump height showed greater plantar flexion and later and quicker knee extension before takeoff. Future applications of the model can include investigations into the sensitivity of the model to changes in initial conditions, and activation, strength, and trampoline parameters

Exploiting inherent robustness and natural dynamics in the control of bipedal walking robots

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references (p. 115-120).Walking is an easy task for most humans and animals. Two characteristics which make it easy are the inherent robustness (tolerance to variation) of the walking problem and the natural dynamics of the walking mechanism. In this thesis we show how understanding and exploiting these two characteristics can aid in the control of bipedal robots. Inherent robustness allows for the use of simple, low impedance controllers. Natural dynamics reduces the requirements of the controller. We present a series of simple physical models of bipedal walking. The insight gained from these models is used in the development of three planar (motion only in the sagittal plane) control algorithms. The first uses simple strategies to control the robot to walk. The second exploits the natural dynamics of a kneecap, compliant ankle, and passive swing-leg. The third achieves fast swing of the swing-leg in order to enable the robot to walk quickly (1.25m). These algorithms are implemented on Spring Flamingo, a planar bipedal walking robot, which was designed and built for this thesis. Using these algorithms, the robot can stand and balance, start and stop walking, walk at a range of speeds, and traverse slopes and rolling terrain. Three-dimensional walking on flat ground is implemented and tested in simulation. The dynamics of the sagittal plane are sufficiently decoupled from the dynamics of the frontal and transverse planes such that control.-of each can be treated separately. We achieve three-dimensional walking by adding lateral balance to the planar algorithms. Tests of this approach on a real three-dimensional robot will lead to a more complete understanding of the control of bipedal walking in robots and humans.by Jerry E. Pratt.Ph.D

Biomechanical Spectrum of Human Sport Performance

Writing or managing a scientific book, as it is known today, depends on a series of major activities, such as regrouping researchers, reviewing chapters, informing and exchanging with contributors, and at the very least, motivating them to achieve the objective of publication. The idea of this book arose from many years of work in biomechanics, health disease, and rehabilitation. Through exchanges with authors from several countries, we learned much from each other, and we decided with the publisher to transfer this knowledge to readers interested in the current understanding of the impact of biomechanics in the analysis of movement and its optimization. The main objective is to provide some interesting articles that show the scope of biomechanical analysis and technologies in human behavior tasks. Engineers, researchers, and students from biomedical engineering and health sciences, as well as industrial professionals, can benefit from this compendium of knowledge about biomechanics applied to the human body

MUSME 2011 4 th International Symposium on Multibody Systems and Mechatronics

El libro de actas recoge las aportaciones de los autores a través de los correspondientes artículos a la Dinámica de Sistemas Multicuerpo y la Mecatrónica (Musme). Estas disciplinas se han convertido en una importante herramienta para diseñar máquinas, analizar prototipos virtuales y realizar análisis CAD sobre complejos sistemas mecánicos articulados multicuerpo. La dinámica de sistemas multicuerpo comprende un gran número de aspectos que incluyen la mecánica, dinámica estructural, matemáticas aplicadas, métodos de control, ciencia de los ordenadores y mecatrónica. Los artículos recogidos en el libro de actas están relacionados con alguno de los siguientes tópicos del congreso: Análisis y síntesis de mecanismos ; Diseño de algoritmos para sistemas mecatrónicos ; Procedimientos de simulación y resultados ; Prototipos y rendimiento ; Robots y micromáquinas ; Validaciones experimentales ; Teoría de simulación mecatrónica ; Sistemas mecatrónicos ; Control de sistemas mecatrónicosUniversitat Politècnica de València (2011). MUSME 2011 4 th International Symposium on Multibody Systems and Mechatronics. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/13224Archivo delegad

Fabricate 2014

FABRICATE is an international peer reviewed conference that takes place every three years with a supporting publication on the theme of Digital Fabrication. Discussing the progressive integration of digital design with manufacturing processes, and its impact on design and making in the 21st century, FABRICATE brings together pioneers in design and making within architecture, construction, engineering, manufacturing, materials technology and computation. Discussion on key themes includes: how digital fabrication technologies are enabling new creative and construction opportunities from component to building scales, the difficult gap that exists between digital modelling and its realisation, material performance and manipulation, off-site and on-site construction, interdisciplinary education, economic and sustainable contexts. FABRICATE features cutting-edge built work from both academia and practice, making it a unique event that attracts delegates from all over the worl

Data-Driven Methods to Build Robust Legged Robots

For robots to ever achieve signicant autonomy, they need to be able to mitigate performance loss due to uncertainty, typically from a novel environment or morphological variation of their bodies. Legged robots, with their complex dynamics, are particularly challenging to control with principled theory. Hybrid events, uncertainty, and high dimension are all confounding factors for direct analysis of models. On the other hand, direct data-driven methods have proven to be equally dicult to employ. The high dimension and mechanical complexity of legged robots have proven challenging for hardware-in-the-loop strategies to exploit without signicant eort by human operators. We advocate that we can exploit both perspectives by capitalizing on qualitative features of mathematical models applicable to legged robots, and use that knowledge to strongly inform data-driven methods. We show that the existence of these simple structures can greatly facilitate robust design of legged robots from a data-driven perspective. We begin by demonstrating that the factorial complexity of hybrid models can be elegantly resolved with computationally tractable algorithms, and establish that a novel form of distributed control is predicted. We then continue by demonstrating that a relaxed version of the famous templates and anchors hypothesis can be used to encode performance objectives in a highly redundant way, allowing robots that have suffered damage to autonomously compensate. We conclude with a deadbeat stabilization result that is quite general, and can be determined without equations of motion.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155053/1/gcouncil_1.pd