Humanoid Robot Soccer Locomotion and Kick Dynamics: Open Loop Walking, Kicking and Morphing into Special Motions on the Nao Robot

Striker speed and accuracy in the RoboCup (SPL) international robot soccer league is becoming increasingly important as the level of play rises. Competition around the ball is now decided in a matter of seconds. Therefore, eliminating any wasted actions or motions is crucial when attempting to kick the ball. It is common to see a discontinuity between walking and kicking where a robot will return to an initial pose in preparation for the kick action. In this thesis we explore the removal of this behaviour by developing a transition gait that morphs the walk directly into the kick back swing pose. The solution presented here is targeted towards the use of the Aldebaran walk for the Nao robot. The solution we develop involves the design of a central pattern generator to allow for controlled steps with realtime accuracy, and a phase locked loop method to synchronise with the Aldebaran walk so that precise step length control can be activated when required. An open loop trajectory mapping approach is taken to the walk that is stabilized statically through the use of a phase varying joint holding torque technique. We also examine the basic princples of open loop walking, focussing on the commonly overlooked frontal plane motion. The act of kicking itself is explored both analytically and empirically, and solutions are provided that are versatile and powerful. Included as an appendix, the broader matter of striker behaviour (process of goal scoring) is reviewed and we present a velocity control algorithm that is very accurate and efficient in terms of speed of execution

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

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

Climbing and Walking Robots

Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study

Information transfer and causality in the sensorimotor loop

This thesis investigates information-theoretic tools for detecting and describing causal influences in embodied agents. It presents an analysis of philosophical and statistical approaches to causation, and in particular focuses on causal Bayes nets and transfer entropy. It argues for a novel perspective that explicitly incorporates the epistemological role of information as a tool for inference. This approach clarifies and resolves some of the known problems associated with such methods. Here it is argued, through a series of experiments, mathematical results and some philosophical accounts, that universally applicable measures of causal influence strength are unlikely to exist. Instead, the focus should be on the role that information-theoretic tools can play in inferential tests for causal relationships in embodied agents particularly, and dynamical systems in general. This thesis details how these two approaches differ. Following directly from these arguments, the thesis proposes a concept of “hidden” information transfer to describe situations where causal influences passing through a chain of variables may be more easily detected at the end-points than at intermediate nodes. This is described using theoretical examples, and also appears in the information dynamics of computer-simulated and real robots developed herein. Practical examples include some minimal models of agent-environment systems, but also a novel complete system for generating locomotion gait patterns using a biologically-inspired decentralized architecture on a walking robotic hexapod

Spatial and Timing Regulation of Upper-Limb Movements in Rhythmic Tasks

Rhythmic movement is vital to humans and a foundation of such activities as locomotion, handwriting, and repetitive tool use. The spatiotemporal regularity characterizing such movements reflects a level of automaticity and coordination that is believed to emerge from mutually inhibitory or other pattern generating neural networks in the central nervous system. Although many studies have provided descriptions of this regularity and have illuminated the types of sensory information that influence rhythmic behavior, an understanding of how the brain uses sensory feedback to regulate rhythmic behavior on a cycle-by-cycle basis has been elusive. This thesis utilizes the model task of paddle juggling, or vertical ball bouncing, to address how three types of feedback---visual, auditory, and haptic---contribute to spatial and temporal regulation of rhythmic upper-limb movements. We use a multi-level approach in accordance with the well-known dictum of Marr and Poggio. The crux of this thesis describes a method and suite of experiments to understand how the brain uses visual, audio, and haptic feedback to regulate spatial or timing regularity, and formulate acycle-by-cycle description of this control: to wit, the nature and algorithms of sensory-feedback guided regulation. Part I motivates our interest in this problem, by discussing the biological ``hardware'' that the nervous system putatively employs in these movements, and reviewing insights from previous studies of paddle juggling that suggest how the ``hardware'' may manifest itself in these behaviors. The central experimental approach of this thesis is to train participants to perform the paddle juggling task with spatiotemporal regularity (in other words, to achieve limit-cycle behavior), and then interrogate how the brain applies regulates closed-loop performance by perturbing task feedback. In Part II, we review the development of a novel hard-real-time virtual-reality juggling simulator that enabled precise spatial and temporal feedback perturbations. We then outline the central experimental approach, in which we perturb spatial feedback of the ball at apex phase (vision), and timing feedback of collision- (audio and haptic) and apex-phase events to understand spatial and timing regulation. Part III describes two experiments that yield the main research findings of this thesis. In Experiment 1, we use a sinusoidal-perturbation-based system identification approach to determine that spatial and timing feedback are used in two dissociable and complementary control processes: spatial error correction and temporal synchronization. In Experiment 2, a combination of sinusoidal and step perturbations is used to establish that these complementary processes obey different dynamics. Namely, spatial correction is a proportional-integral process based on a one-step memory of feedback, while temporal synchronization is a proportional process that is dependent only on the most recent feedback. We close in Part IV with a discussion of how insights and approaches from this thesis can lead to improved rehabilitation approaches and understanding of the physiological basis of rhythmic movement regulation

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

Super Ball Bot - Structures for Planetary Landing and Exploration, NIAC Phase 2 Final Report

Small, light-weight and low-cost missions will become increasingly important to NASA's exploration goals. Ideally teams of small, collapsible, light weight robots, will be conveniently packed during launch and would reliably separate and unpack at their destination. Such robots will allow rapid, reliable in-situ exploration of hazardous destination such as Titan, where imprecise terrain knowledge and unstable precipitation cycles make single-robot exploration problematic. Unfortunately landing lightweight conventional robots is difficult with current technology. Current robot designs are delicate, requiring a complex combination of devices such as parachutes, retrorockets and impact balloons to minimize impact forces and to place a robot in a proper orientation. Instead we are developing a radically different robot based on a "tensegrity" structure and built purely with tensile and compression elements. Such robots can be both a landing and a mobility platform allowing for dramatically simpler mission profile and reduced costs. These multi-purpose robots can be light-weight, compactly stored and deployed, absorb strong impacts, are redundant against single-point failures, can recover from different landing orientations and can provide surface mobility. These properties allow for unique mission profiles that can be carried out with low cost and high reliability and which minimizes the inefficient dependance on "use once and discard" mass associated with traditional landing systems. We believe tensegrity robot technology can play a critical role in future planetary exploration

On the Development of Postural Stability During Infancy as a Process of Growth and Active, Exploratory Sensorimotor Tuning

The process by which humans stabilize bipedal stance represents a confluence of changes associated with musculoskeletal maturation and experience-based sensorimotor learning. While investigations have documented a variety of changes with increased bipedal experience, such as reduced velocity and frequency of postural sway and concomitant refinements in muscle activation sequences, the extent to which these changes may be ascribed to growth versus learning processes has not been well characterized. For example, reduced sway frequency is a natural consequence of increasing body height but alternatively, may be explained by active modulations in motor commands specifying the timing and magnitude of muscular activation sequences. It is clear that both types of influences are needed to explain postural development. However, a parsimonious framework for understanding and explaining postural development has yet to be clearly articulated and validated against empirical observations. As such, the purpose of this dissertation was to initiate the development of such an account through a combination of empirical and computational studies. In this dissertation, data are presented from a longitudinal study of upright posture in infants ranging from the onset of independent sitting until 9 months of walking experience; this dissertation focused on the particular period spanning from walk onset onward. Infants participated in a quiet stance task involving hand contact with a surface that was either static or dynamic as well as an independent stance condition. Empirical analyses were performed to estimate the statistical properties of sway and characterize adaptations to static and dynamic manipulations utilizing the touch surface. An unexpected lack of significance for sway magnitude was observed in all conditions. Robust effects, however, were found across measures of rate properties of sway. Taken in the context of previous literature, the empirical observations were used to guide a final study utilizing computational techniques to test hypotheses regarding potential sources of change in postural development. First, the mechanical and computational requirements for postural stabilization were systematically assessed through a review of extant models of both stance and motor learning. Armed with insights from this review, the final study examined an autonomous reinforcement learning algorithm, that was designed to capture the essence of how a human may stabilize his or her posture under the tutelage of exploratory action. Simulation results provided evidence in support of conclusions regarding changes in rate-properties of postural sway and underlying associations with physical growth as well as calibration of both sensory and motor system parameters. Further, simulations emphasized the importance of inclusion of noise in biologically-relevant aspects of the model, such as in sensory and motor processes, as well as the need to consider physical morphology as a primary constraint on sensorimotor learning in the context of upright postural development