1,036 research outputs found
Trajectory generation for multi-contact momentum-control
Simplified models of the dynamics such as the linear inverted pendulum model
(LIPM) have proven to perform well for biped walking on flat ground. However,
for more complex tasks the assumptions of these models can become limiting. For
example, the LIPM does not allow for the control of contact forces
independently, is limited to co-planar contacts and assumes that the angular
momentum is zero. In this paper, we propose to use the full momentum equations
of a humanoid robot in a trajectory optimization framework to plan its center
of mass, linear and angular momentum trajectories. The model also allows for
planning desired contact forces for each end-effector in arbitrary contact
locations. We extend our previous results on LQR design for momentum control by
computing the (linearized) optimal momentum feedback law in a receding horizon
fashion. The resulting desired momentum and the associated feedback law are
then used in a hierarchical whole body control approach. Simulation experiments
show that the approach is computationally fast and is able to generate plans
for locomotion on complex terrains while demonstrating good tracking
performance for the full humanoid control
Efficient Humanoid Contact Planning using Learned Centroidal Dynamics Prediction
Humanoid robots dynamically navigate an environment by interacting with it
via contact wrenches exerted at intermittent contact poses. Therefore, it is
important to consider dynamics when planning a contact sequence. Traditional
contact planning approaches assume a quasi-static balance criterion to reduce
the computational challenges of selecting a contact sequence over a rough
terrain. This however limits the applicability of the approach when dynamic
motions are required, such as when walking down a steep slope or crossing a
wide gap. Recent methods overcome this limitation with the help of efficient
mixed integer convex programming solvers capable of synthesizing dynamic
contact sequences. Nevertheless, its exponential-time complexity limits its
applicability to short time horizon contact sequences within small
environments. In this paper, we go beyond current approaches by learning a
prediction of the dynamic evolution of the robot centroidal momenta, which can
then be used for quickly generating dynamically robust contact sequences for
robots with arms and legs using a search-based contact planner. We demonstrate
the efficiency and quality of the results of the proposed approach in a set of
dynamically challenging scenarios
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
Dynamic whole-body motion generation under rigid contacts and other unilateral constraints
The most widely used technique for generating wholebody motions on a humanoid robot accounting for various tasks and constraints is inverse kinematics. Based on the task-function approach, this class of methods enables the coordination of robot movements to execute several tasks in parallel and account for the sensor feedback in real time, thanks to the low computation cost.
To some extent, it also enables us to deal with some of the robot constraints (e.g., joint limits or visibility) and manage the quasi-static balance of the robot. In order to fully use the whole range of possible motions, this paper proposes extending the task-function approach to handle the full dynamics of the robot multibody along with any constraint written as equality or inequality of the state and control variables. The definition of multiple objectives is made possible by ordering them inside a strict hierarchy. Several models of contact with the environment can be implemented in the framework. We propose a reduced formulation of the multiple rigid planar contact that keeps a low computation cost. The efficiency of this approach is illustrated by presenting several multicontact dynamic motions in simulation and on the real HRP-2 robot
Motion Planning and Feedback Control of Simulated Robots in Multi-Contact Scenarios
Diese Dissertation präsentiert eine optimale steuerungsbasierte Architektur für die Bewegungsplanung und Rückkopplungssteuerung simulierter Roboter in Multikontaktszenarien. Bewegungsplanung und -steuerung sind grundlegende Bausteine für die Erstellung wirklich autonomer Roboter. Während in diesen Bereichen enorme Fortschritte für Manipulatoren mit festem Sockel und Radrobotern in den letzten Jahren erzielt wurden, besteht das Problem der Bewegungsplanung und -steuerung für Roboter mit Armen und Beinen immer noch ein ungelöstes Problem, das die Notwendigkeit effizienterer und robusterer Algorithmen belegt. In diesem Zusammenhang wird in dieser Dissertation eine Architektur vorgeschlagen, mit der zwei Hauptherausforderungen angegangen werden sollen, nämlich die effiziente Planung von Kontaktsequenzen und Ganzkörperbewegungen für Floating-Base-Roboter sowie deren erfolgreiche Ausführung mit Rückkopplungsregelungsstrategien, die Umgebungsunsicherheiten bewältigen könne
Generating whole body movements for dynamics anthropomorphic systems under constraints
Cette thèse étudie la question de la génération de mouvements corps-complet pour des systèmes anthropomorphes. Elle considère le problème de la modélisation et de la commande en abordant la question difficile de la génération de mouvements ressemblant à ceux de l'homme. En premier lieu, un modèle dynamique du robot humanoïde HRP-2 est élaboré à partir de l'algorithme récursif de Newton-Euler pour les vecteurs spatiaux. Un nouveau schéma de commande dynamique est ensuite développé, en utilisant une cascade de programmes quadratiques (QP) optimisant des fonctions coûts et calculant les couples de commande en satisfaisant des contraintes d'égalité et d'inégalité. La cascade de problèmes quadratiques est définie par une pile de tâches associée à un ordre de priorité. Nous proposons ensuite une formulation unifiée des contraintes de contacts planaires et nous montrons que la méthode proposée permet de prendre en compte plusieurs contacts non coplanaires et généralise la contrainte usuelle du ZMP dans le cas où seulement les pieds sont en contact avec le sol. Nous relions ensuite les algorithmes de génération de mouvement issus de la robotique aux outils de capture du mouvement humain en développant une méthode originale de génération de mouvement visant à imiter le mouvement humain. Cette méthode est basée sur le recalage des données capturées et l'édition du mouvement en utilisant le solveur hiérarchique précédemment introduit et la définition de tâches et de contraintes dynamiques. Cette méthode originale permet d'ajuster un mouvement humain capturé pour le reproduire fidèlement sur un humanoïde en respectant sa propre dynamique. Enfin, dans le but de simuler des mouvements qui ressemblent à ceux de l'homme, nous développons un modèle anthropomorphe ayant un nombre de degrés de liberté supérieur à celui du robot humanoïde HRP2. Le solveur générique est utilisé pour simuler le mouvement sur ce nouveau modèle. Une série de tâches est définie pour décrire un scénario joué par un humain. Nous montrons, par une simple analyse qualitative du mouvement, que la prise en compte du modèle dynamique permet d'accroitre naturellement le réalisme du mouvement.This thesis studies the question of whole body motion generation for anthropomorphic systems. Within this work, the problem of modeling and control is considered by addressing the difficult issue of generating human-like motion. First, a dynamic model of the humanoid robot HRP-2 is elaborated based on the recursive Newton-Euler algorithm for spatial vectors. A new dynamic control scheme is then developed adopting a cascade of quadratic programs (QP) optimizing the cost functions and computing the torque control while satisfying equality and inequality constraints. The cascade of the quadratic programs is defined by a stack of tasks associated to a priority order. Next, we propose a unified formulation of the planar contact constraints, and we demonstrate that the proposed method allows taking into account multiple non coplanar contacts and generalizes the common ZMP constraint when only the feet are in contact with the ground. Then, we link the algorithms of motion generation resulting from robotics to the human motion capture tools by developing an original method of motion generation aiming at the imitation of the human motion. This method is based on the reshaping of the captured data and the motion editing by using the hierarchical solver previously introduced and the definition of dynamic tasks and constraints. This original method allows adjusting a captured human motion in order to reliably reproduce it on a humanoid while respecting its own dynamics. Finally, in order to simulate movements resembling to those of humans, we develop an anthropomorphic model with higher number of degrees of freedom than the one of HRP-2. The generic solver is used to simulate motion on this new model. A sequence of tasks is defined to describe a scenario played by a human. By a simple qualitative analysis of motion, we demonstrate that taking into account the dynamics provides a natural way to generate human-like movements
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