Motion Planning and Control for the Locomotion of Humanoid Robot

This thesis aims to contribute on the motion planning and control problem of the locomotion of humanoid robots. For the motion planning, various methods were proposed in different levels of model dependence. First, a model free approach was proposed which utilizes linear regression to estimate the relationship between foot placement and moving velocity. The data-based feature makes it quite robust to handle modeling error and external disturbance. As a generic control philosophy, it can be applied to various robots with different gaits. To reduce the risk of collecting experimental data of model-free method, based on the simplified linear inverted pendulum model, the classic planning method of model predictive control was explored to optimize CoM trajectory with predefined foot placements or optimize them two together with respect to the ZMP constraint. Along with elaborately designed re-planning algorithm and sparse discretization of trajectories, it is fast enough to run in real time and robust enough to resist external disturbance. Thereafter, nonlinear models are utilized for motion planning by performing forward simulation iteratively following the multiple shooting method. A walking pattern is predefined to fix most of the degrees of the robot, and only one decision variable, foot placement, is left in one motion plane and therefore able to be solved in milliseconds which is sufficient to run in real time. In order to track the planned trajectories and prevent the robot from falling over, diverse control strategies were proposed according to the types of joint actuators. CoM stabilizer was designed for the robots with position-controlled joints while quasi-static Cartesian impedance control and optimization-based full body torque control were implemented for the robots with torque-controlled joints. Various scenarios were set up to demonstrate the feasibility and robustness of the proposed approaches, like walking on uneven terrain, walking with narrow feet or straight leg, push recovery and so on

Locomotion Trajectory Generation and Dynamic Control for Bipedal Walking Robots

Ph.DDOCTOR OF PHILOSOPH

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

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

Pre-computation for controlling character behavior in interactive physical simulations

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 129-136).The development of advanced computer animation tools has allowed talented artists to create digital actors, or characters, in films and commercials that move in a plausible and compelling way. In interactive applications, however, the artist does not have total control over the scenarios the character will experience. Unexpected changes in the environment of the character or unexpected interactions with dynamic elements of the virtual world can lead to implausible motions. This work investigates the use of physical simulation to automatically synthesize plausible character motions in interactive applications. We show how to simulate a realistic motion for a humanoid character by creating a feedback controller that tracks a motion capture recording. By applying the right forces at the right time, the controller is able to recover from a range of interesting changes to the environment and unexpected disturbances. Controlling physically simulated humanoid characters is non-trivial as they are governed by non-linear, non-smooth, and high-dimensional equations of motion. We simplify the problem by using a linearized and simplified dynamics model near a reference trajectory. Tracking a reference trajectory is an effective way of getting a character to perform a single task. However, simulated characters need to perform many tasks form a variety of possible configurations. This work also describes a method for combining existing controllers by adding their output forces to perform new tasks. This allows one to reuse existing controllers. A surprising fact is that combined controllers can perform optimally under certain conditions. These methods allow us to interactively simulate many interesting humanoid character behaviors in two and three dimensions. These characters have many more degrees of freedom than typical robot systems and move much more naturally. Simulation is fast enough that the controllers could soon be used to animate characters in interactive games. It is also possible that these simulations could be used to test robotic designs and biomechanical hypotheses.by Marco Jorge Tome da Silva.Ph.D

Mechanisms of Stability and Energy Expenditure in Human Locomotion.

Although humans normally walk with both stability and energy economy, either feature may be challenging for persons with disabilities. For example, in patients with lower-limb amputation, falling is pervasive, and may lead to activity avoidance. Similarly, energy expenditure is higher than for healthy subjects and may deter patients from walking, reducing mobility. A better understanding of the fundamental principles of stability and economy could lead to better prostheses that increase quality of life for patients. When designing a mechanism to assist or mimic human gait, such as orthoses or walking robots, the stability and economy of the resulting gait should be considered. To further our understanding of these fundamental principles of gait, I explore a lesser known balance mechanism, foot heading, as well as the role of muscle force production costs in gait. To investigate the stabilizing role of foot heading, I first characterize a method of measuring natural human gait variability outside of lab environments using foot mounted inertial sensors. Accuracy is found comparable to motion capture, while allowing capture of gait in natural environments. Then, using both a simple model of walking, and a variability analysis of human walking, I present evidence that humans stabilize gait laterally by altering foot heading step-to-step. I then consider the metabolic cost of force production in human locomotion. First, an optimization study of a simple model of locomotion shows that force fluctuation costs have a stronger role in determining gait than force amplitude costs. I then illustrate the connection between force fluctuation and a cost for calcium pumping in muscles using a simple muscle model. Finally, a human subject experiment altering force fluctuation in walking demonstrates the higher metabolic cost of fluctuating forces. While human locomotion is a complex activity involving many muscles, sensory systems, and neural circuitry, we can use basic mechanical models to study underlying principles of gait. A better understanding of stability and economy could have applications to many fields involving locomotion, such as the diagnosis of fall-risk in elderly subjects, the development of rehabilitation techniques, the design of prostheses, and the creation of robust and practical walking machines.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/108908/1/jrebula_1.pd

Rich and Robust Bio-Inspired Locomotion Control for Humanoid Robots

Bipedal locomotion is a challenging task in the sense that it requires to maintain dynamic balance while steering the gait in potentially complex environments. Yet, humans usually manage to move without any apparent difficulty, even on rough terrains. This requires a complex control scheme which is far from being understood. In this thesis, we take inspiration from the impressive human walking capabilities to design neuromuscular controllers for humanoid robots. More precisely, we control the robot motors to reproduce the action of virtual muscles commanded by stimulations (i.e. neural signals), similarly to what is done during human locomotion. Because the human neural circuitry commanding these muscles is not completely known, we make hypotheses about this control scheme to simplify it and progressively refine the corresponding rules. This thesis thus aims at developing new walking algorithms for humanoid robots in order to obtain fast, human-like and energetically efficient gaits. In particular, gait robustness and richness are two key aspects of this work. In other words, the gaits developed in the thesis can be steered by an external operator, while being resistant to external perturbations. This is mainly tested during blind walking experiments on COMAN, a 95 cm tall humanoid robot. Yet, the proposed controllers can be adapted to other humanoid robots. In the beginning of this thesis, we adapt and port an existing reflex-based neuromuscular model to the real COMAN platform. When tested in a 2D simulation environment, this model was capable of reproducing stable human-like locomotion. By porting it to real hardware, we show that these neuromuscular controllers are viable solutions to develop new controllers for robotics locomotion. Starting from this reflex-based model, we progressively iterate and transform the stimulation rules to add new features. In particular, gait modulation is obtained with the inclusion of a central pattern generator (CPG), a neural circuit capable of producing rhythmic patterns of neural activity without receiving rhythmic inputs. Using this CPG, the 2D walker controllers are incremented to generate gaits across a range of forward speeds close to the normal human one. By using a similar control method, we also obtain 2D running gaits whose speed can be controlled by a human operator. The walking controllers are later extended to 3D scenarios (i.e. no motion constraint) with the capability to adapt both the forward speed and the heading direction (including steering curvature). In parallel, we also develop a method to automatically learn stimulation networks for a given task and we study how flexible feet affect the gait in terms of robustness and energy efficiency. In sum, we develop neuromuscular controllers generating human-like gaits with steering capabilities. These controllers recruit three main components: (i) virtual muscles generating torque references at the joint level, (ii) neural signals commanding these muscles with reflexes and CPG signals, and (iii) higher level commands controlling speed and heading. Interestingly, these developments target humanoid robots locomotion but can also be used to better understand human locomotion. In particular, the recruitment of a CPG during human locomotion is still a matter open to debate. This question can thus benefit from the experiments performed in this thesis

Biped locomotion control through a biologically-inspired closed-loop controller

Dissertação de mestrado integrado em Engenharia BiomédicaCurrently motor disability in industrialized countries due to neural and physical impairments is an increasingly worrying phenomenon and the percentage of patients is expected to be increasing continuously over the coming decades due to a process of ageing the world is undergoing. Additionally, rising retirement ages, higher demand of elderly people for an independent, dignified life and mobility, huge cost in the provision of health care are some other determinants that motivate the restoration of motor function as one of the main goals of rehabilitation. Modern concepts of motor learning favor a task-specific training in which all movements in daily life should be trained/assisted repetitively in a physically correct fashion. Considering the functional activity of the neuronal circuits within the spinal cord, namely the central pattern generator (CPG), as the foundation to human locomotion, motor relearning should be based on intensive training strategies directed to the stimulation and reorganization of such neural pathways through mechanisms addressed by neural plasticity. To this end, neuromodelings are required to simulate the human locomotion control to overcome the current technological challenges such as developing smaller, intelligent and cost-effective devices for home and work rehabilitation scenarios which can enable a continuous therapy/ assistance to guide the impaired limbs in a gentle manner, avoiding abrupt perturbations and providing as little assistance as necessary. Biomimetic models, taking neurological and biomechanical inspiration from biological animals, have been embracing these challenges and developing effective solutions on refining the locomotion models in terms of energy efficiency, simplicity in the structure and robust adaptability to environment changes and unexpected perturbations. Thus, the aim target of this work is to study the applicability of the CPG model for gait rehabilitation, either for assistance and/or therapy purposes. Focus is developed on the locomotion control to increase the knowledge of the underlying principles useful for gait restoration, exploring the brainstem-spinal-biomechanics interaction more fully. This study has great application in the project of autonomous robots and in the rehabilitation technology, not only in the project of prostheses and orthoses, but also in the searching of procedures that help to recuperate motor functions of human beings. Encouraging results were obtained which pave the way towards the simulation of more complex behaviors and principles of human locomotion, consequently contributing for improved automated motor rehabilitation adapted to the rehabilitation emerging needs.Actualmente a debilidade motora em países industrializados devido a deficiências neurais e físicas é um fenómeno crescente de apreensão sendo expectável um contínuo aumento do rácio de pacientes nas próximas décadas devido ao processo de envelhecimento. Inclusivé, o aumento da idade de reforma, a maior procura por parte dos idosos para uma mobilidade e vida autónoma e condigna, o elevado custo nos cuidados de saúde são incentivos para a restauração da função motora como um dos objectivos principais da reabilitação. Conceitos recentes de aprendizagem motora apoiam um treino de tarefas específicas no qual movimentos no quotidiano devem ser treinados/assistidos de forma repetitiva e fisicamente correcta. Considerando a actividade funcional dos circuitos neurais na medula, nomeadamente o gerador de padrão central (CPG), como a base da locomoção, a reaprendizagem motora deve-se basear em estratégias intensivas de treino visando a estimulação e reorganização desses vias neurais através de mecanismos abordados pela plasticidade neural. Assim, são necessários modelos neurais para simular o controlo da locomoção humana de modo a superar desafios tecnológicos actuais tais como o desenvolvimento de dispositivos mais compactos, inteligentes e económicos para os cenários de reabilitação domiciliar e laboral que podem permitir uma terapia/assistência contínua na guia dos membros debilitados de uma forma suave, evitando perturbações abruptas e fornecendo assistência na medida do necessário. Modelos biomiméticos, inspirando-se nos princípios neurológicos e biomecânicos dos animais, têm vindo a abraçar esses desafios e a desenvolver soluções eficazes na refinação de modelos de locomoção em termos da eficiência de energia, da simplicidade na estrutura e da adaptibilidade robusta face a alterações ambientais e perturbações inesperadas. Então, o objectivo principal do trabalho é estudar a aplicabilidade do modelo de CPG para a reabilitação da marcha, para efeitos de assistência e/ou terapia. É desenvolvido um foco no controlo da locomoção para maior entendimento dos princípios subjacentes úteis para a recuperação da marcha, explorando a interacção tronco cerebral-espinal medula-biomecânica de forma mais detalhada. Este estudo tem potencial aplicação no projecto de robôs autónomos e na tecnologia de reabilitação, não só no desenvolvimento de ortóteses e próteses, mas também na procura de procedimentos úteis para a recuperação da função motora. Foram obtidos resultados promissores susceptíveis de abrir caminho à simulação de comportamentos e princípios mais complexos da marcha, contribuindo consequentemente para uma aprimorada reabilitação motora automatizada adaptada às necessidades emergentes