A Modular Framework to Generate Robust Biped Locomotion: From Planning to Control

Biped robots are inherently unstable because of their complex kinematics as well as dynamics. Despite the many research efforts in developing biped locomotion, the performance of biped locomotion is still far from the expectations. This paper proposes a model-based framework to generate stable biped locomotion. The core of this framework is an abstract dynamics model which is composed of three masses to consider the dynamics of stance leg, torso and swing leg for minimizing the tracking problems. According to this dynamics model, we propose a modular walking reference trajectories planner which takes into account obstacles to plan all the references. Moreover, this dynamics model is used to formulate the controller as a Model Predictive Control (MPC) scheme which can consider some constraints in the states of the system, inputs, outputs and also mixed input-output. The performance and the robustness of the proposed framework are validated by performing several numerical simulations using MATLAB. Moreover, the framework is deployed on a simulated torque-controlled humanoid to verify its performance and robustness. The simulation results show that the proposed framework is capable of generating biped locomotion robustly

Locomoção de humanoides robusta e versátil baseada em controlo analítico e física residual

Humanoid robots are made to resemble humans but their locomotion abilities are far from ours in terms of agility and versatility. When humans walk on complex terrains or face external disturbances, they combine a set of strategies, unconsciously and efficiently, to regain stability. This thesis tackles the problem of developing a robust omnidirectional walking framework, which is able to generate versatile and agile locomotion on complex terrains. We designed and developed model-based and model-free walk engines and formulated the controllers using different approaches including classical and optimal control schemes and validated their performance through simulations and experiments. These frameworks have hierarchical structures that are composed of several layers. These layers are composed of several modules that are connected together to fade the complexity and increase the flexibility of the proposed frameworks. Additionally, they can be easily and quickly deployed on different platforms. Besides, we believe that using machine learning on top of analytical approaches is a key to open doors for humanoid robots to step out of laboratories. We proposed a tight coupling between analytical control and deep reinforcement learning. We augmented our analytical controller with reinforcement learning modules to learn how to regulate the walk engine parameters (planners and controllers) adaptively and generate residuals to adjust the robot’s target joint positions (residual physics). The effectiveness of the proposed frameworks was demonstrated and evaluated across a set of challenging simulation scenarios. The robot was able to generalize what it learned in one scenario, by displaying human-like locomotion skills in unforeseen circumstances, even in the presence of noise and external pushes.Os robôs humanoides são feitos para se parecerem com humanos, mas suas habilidades de locomoção estão longe das nossas em termos de agilidade e versatilidade. Quando os humanos caminham em terrenos complexos ou enfrentam distúrbios externos combinam diferentes estratégias, de forma inconsciente e eficiente, para recuperar a estabilidade. Esta tese aborda o problema de desenvolver um sistema robusto para andar de forma omnidirecional, capaz de gerar uma locomoção para robôs humanoides versátil e ágil em terrenos complexos. Projetámos e desenvolvemos motores de locomoção sem modelos e baseados em modelos. Formulámos os controladores usando diferentes abordagens, incluindo esquemas de controlo clássicos e ideais, e validámos o seu desempenho por meio de simulações e experiências reais. Estes frameworks têm estruturas hierárquicas compostas por várias camadas. Essas camadas são compostas por vários módulos que são conectados entre si para diminuir a complexidade e aumentar a flexibilidade dos frameworks propostos. Adicionalmente, o sistema pode ser implementado em diferentes plataformas de forma fácil. Acreditamos que o uso de aprendizagem automática sobre abordagens analíticas é a chave para abrir as portas para robôs humanoides saírem dos laboratórios. Propusemos um forte acoplamento entre controlo analítico e aprendizagem profunda por reforço. Expandimos o nosso controlador analítico com módulos de aprendizagem por reforço para aprender como regular os parâmetros do motor de caminhada (planeadores e controladores) de forma adaptativa e gerar resíduos para ajustar as posições das juntas alvo do robô (física residual). A eficácia das estruturas propostas foi demonstrada e avaliada em um conjunto de cenários de simulação desafiadores. O robô foi capaz de generalizar o que aprendeu em um cenário, exibindo habilidades de locomoção humanas em circunstâncias imprevistas, mesmo na presença de ruído e impulsos externos.Programa Doutoral em Informátic

Desenvolvimento de comportamentos para robô humanoide

Mestrado em Engenharia de Computadores e TelemáticaHumanoid robotics is an area of active research. Robots with human body are better suited to execute tasks in environments designed for humans. Moreover, people feel more comfortable interacting with robots that have a human appearance. RoboCup encourages robotic research by promoting robotic competitions. One of these competitions is the Standard Platform League (SPL) in which humanoid robots play soccer. The robot used is the Nao robot, created by Aldebaran Robotics. The di erence between the teams that compete in this league is the software that controls the robots. Another league promoted by RoboCup is the 3D Soccer Simulation League (3DSSL). In this league the soccer game is played in a computer simulation. The robot model used is also the one of the Nao robot. However, there are a few di erences in the dimensions and it has one more Degree of Freedom (DoF) than the real robot. Moreover, the simulator cannot reproduce reality with precision. Both these leagues are relevant for this thesis, since they use the same robot model. The objective of this thesis is to develop behaviors for these leagues, taking advantage of the previous work developed for the 3DSSL. These behaviors include the basic movements needed to play soccer, namely: walking, kicking the ball, and getting up after a fall. This thesis presents the architecture of the agent developed for the SPL, which is similar to the architecture of the FC Portugal team agent from the 3DSSL, hence allowing to port code between both leagues easily. It was also developed an interface that allows to control a leg in a more intuitive way. It calculates the joint angles of the leg, using the following parameters: three angles between the torso and the line connecting hip and ankle; two angles between the foot and the perpendicular of the torso; and the distance between the hip and the ankle. It was also developed an algorithm to calculate the three joint angles of the hip that produce the desired vertical rotation, since the Nao robot does not have a vertical joint in the hip. This thesis presents also the behaviors developed for the SPL, some of them based on the existing behaviors from the 3DSSL. It is presented a behavior that allows to create robot movements by de ning a sequence of poses, an open-loop omnidirectional walking algorithm, and a walk optimized in the simulator adapted to the real robot. Feedback was added to this last walk to make it more robust against external disturbances. Using the behaviors presented in this thesis, the robot achieved a forward velocity of 16 cm/s, a lateral velocity of 6 cm/s, and rotated at 40 deg/s. The work developed in this thesis allows to have an agent to control the Nao robot and execute the basic low level behaviors for competing in the SPL. Moreover, the similarities between the architecture of the agent for the SPL with that of the agent from the 3DSSL allow to use the same high level behaviors in both leagues.A robótica humanoide é uma área em ativo desenvolvimento. Os robôs com forma humana estão melhor adaptados para executarem tarefas em ambientes desenhados para humanos. Além disso, as pessoas sentem-se mais confortáveis quando interagem com robôs que tenham aparência humana. O RoboCup incentiva a investigação na área da robótica através da realização de competições de robótica. Uma destas competições é a Standard Platform League (SPL) na qual robôs humanoides jogam futebol. O robô usado é o robô Nao, criado pela Aldebaran Robotics. A diferença entre as equipas que competem nesta liga está no software que controla os robôs. Outra liga presente no RoboCup é a 3D Soccer Simulation League (3DSSL). Nesta liga o jogo de futebol é jogado numa simulação por computador. O modelo de robô usado é também o do robô Nao. Contudo, existem umas pequenas diferenças nas dimensões e este tem mais um grau de liberdade do que o robô real. O simulador também não consegue reproduzir a realidade com perfeição. Ambas estas ligas são importantes para esta dissertação, pois usam o mesmo modelo de robô. O objectivo desta dissertação é desenvolver comportamentos para estas ligas, aproveitando o trabalho prévio desenvolvido para a 3DSSL. Estes comportamentos incluem os movimentos básicos necessários para jogar futebol, nomeadamente: andar, chutar a bola e levantar-se depois de uma queda. Esta dissertação apresenta a arquitetura do agente desenvolvida para a SPL, que é similar á arquitetura do agente da equipa FC Portugal da 3DSSL, para permitir uma mais fácil partilha de código entre as ligas. Foi também desenvolvida uma interface que permite controlar uma perna de maneira mais intuitiva. Ela calcula os ângulos das juntas da perna, usando os seguintes parâmetros: três ângulos entre o torso e a linha que une anca ao tornozelo; dois ângulos entre o pé e a perpendicular do torso; e a distância entre a anca e o tornozelo. Nesta dissertação foi também desenvolvido um algoritmo para calcular os três ângulos das juntas da anca que produzam a desejada rotação vertical, visto o robô Nao não ter uma junta na anca que rode verticalmente. Esta dissertação também apresenta os comportamentos desenvolvidos para a SPL, alguns dos quais foram baseados nos comportamentos já existentes na 3DSSL. É apresentado um modelo de comportamento que permite criar movimentos para o robô de nindo uma sequência de poses, um algoritmo para um andar open-loop e omnidirecional e um andar otimizado no simulador e adaptado para o robô real. A este último andar foi adicionado um sistema de feedback para o tornar mais robusto. Usando os comportamentos apresentados nesta dissertação, o robô atingiu uma velocidade de 16 cm/s para frente, 6 cm/s para o lado e rodou sobre si pr oprio a 40 graus/s. O trabalho desenvolvido nesta dissertação permite ter um agente que controle o robô Nao e execute os comportamentos básicos de baixo nível para competir na SPL. Além disso, as semelhan cas entre a arquitetura do agente para a SPL com a arquitetura do agente da 3DSSL permite usar os mesmos comportamentos de alto nível em ambas as ligas

Humanoid robot omnidirectional walking trajectory generation and control

Walking humanoid machines, once only seen or read in science fiction, became reality with the intensive research of the last four decades. However, there is a long way to go in the direction of technical achievements before humanoid robots can be used widely as human assistants. The design of a controller which can achieve a steady and stable walk is central in humanoid robotics. This control cannot be achieved if the reference trajectories are not generated suitably. The Zero Moment Point (ZMP) is the most widely used stability criterion for trajectory generation. The Center of Mass (CoM) reference can be obtained from the ZMP reference in a number of ways. A natural ZMP reference trajectory and a Fourier series approximation based method for computing the CoM reference from it, was previously proposed and published for the Sabanci University Robotics ReseArch Laboratory Platform (SURALP), for a straight walk. This thesis improves these techniques by modifying the straight walk reference trajectory into an omnidirectional one. The second contribution of this thesis is controller designs in order to cope with the changing slopes of the walking surface. The proposed controllers employ the trunk link rotational motion to adapt to the ground surface. A virtual pelvis link is introduced for the robots which do not posses roll and pitch axis in pelvis link. The proposed reference generation and control algorithms are tested on the humanoid robot SURALP. The experiments indicate that these methods are successful under various floor conditions

Development of a Locomotion and Balancing Strategy for Humanoid Robots

The locomotion ability and high mobility are the most distinguished features of humanoid robots. Due to the non-linear dynamics of walking, developing and controlling the locomotion of humanoid robots is a challenging task. In this thesis, we study and develop a walking engine for the humanoid robot, NAO, which is the official robotic platform used in the RoboCup Spl. Aldebaran Robotics, the manufacturing company of NAO provides a walking module that has disadvantages, such as being a black box that does not provide control of the gait as well as the robot walk with a bent knee. The latter disadvantage, makes the gait unnatural, energy inefficient and exert large amounts of torque to the knee joint. Thus creating a walking engine that produces a quality and natural gait is essential for humanoid robots in general and is a factor for succeeding in RoboCup competition. Humanoids robots are required to walk fast to be practical for various life tasks. However, its complex structure makes it prone to falling during fast locomotion. On the same hand, the robots are expected to work in constantly changing environments alongside humans and robots, which increase the chance of collisions. Several human-inspired recovery strategies have been studied and adopted to humanoid robots in order to face unexpected and avoidable perturbations. These strategies include hip, ankle, and stepping, however, the use of the arms as a recovery strategy did not enjoy as much attention. The arms can be employed in different motions for fall prevention. The arm rotation strategy can be employed to control the angular momentum of the body and help to regain balance. In this master\u27s thesis, I developed a detailed study of different ways in which the arms can be used to enhance the balance recovery of the NAO humanoid robot while stationary and during locomotion. I model the robot as a linear inverted pendulum plus a flywheel to account for the angular momentum change at the CoM. I considered the role of the arms in changing the body\u27s moment of inertia which help to prevent the robot from falling or to decrease the falling impact. I propose a control algorithm that integrates the arm rotation strategy with the on-board sensors of the NAO. Additionally, I present a simple method to control the amount of recovery from rotating the arms. I also discuss the limitation of the strategy and how it can have a negative impact if it was misused. I present simulations to evaluate the approach in keeping the robot stable against various disturbance sources. The results show the success of the approach in keeping the NAO stable against various perturbations. Finally,I adopt the arm rotation to stabilize the ball kick, which is a common reason for falling in the soccer humanoid RoboCup competitions

Modeling, Simulation and Control of the Walking of Biped Robotic Devices—Part III: Turning while Walking

In part II of this group of papers, the control of the gait of a biped robot during rectilinear walk was considered. The modeling approach and simulation, using Kane’s method with implementation leveraged by Autolev, a symbolic computational environment that is complementary, was discussed in part I. Performing turns during the walk is technically more complex than the rectilinear case and deserves further investigation. The problem is solved in the present part III as an extension of part II. The robot executes a rectilinear walk on a local reference frame whose progression axis is always tangent, and its origin performs the involute of the path curve. The curve is defined by its curvature (osculating circle) and center of curvature (evolute) along the path. Radius of curvature and center can change continuously (in practice at every sampling time). For postural equilibrium, Center of Gravity and Zero Moment Point (COG/ZMP) follow the same preview reference proposed for rectilinear walk (c o g R e f x ( t ) , c o g ˙ R e f x ( t ), c o g R e f y ( t ) , c o g ˙ R e f y ( t )). The effect of the turn on the sagittal plane is negligible and is ignored, while on the frontal plane it is accounted for by an offset on COG reference to compensate for the centrifugal acceleration. The body trunk and local frame rotation, and the generation of the references on this moving frame of the free foot trajectory during the swing deserve attention