Advanced human inspired walking strategies for humanoid robots

Cette thèse traite du problème de la locomotion des robots humanoïdes dans le contexte du projet européen KoroiBot. En s'inspirant de l'être humain, l'objectif de ce projet est l'amélioration des capacités des robots humanoïdes à se mouvoir de façon dynamique et polyvalente. Le coeur de l'approche scientifique repose sur l'utilisation du controle optimal, à la fois pour l'identification des couts optimisés par l'être humain et pour leur mise en oeuvre sur les robots des partenaires roboticiens. Cette thèse s'illustre donc par une collaboration à la fois avec des mathématiciens du contrôle et des spécialistes de la modélisation des primitives motrices. Les contributions majeures de cette thèse reposent donc sur la conception de nouveaux algorithmes temps-réel de contrôle pour la locomotion des robots humanoïdes avec nos collégues de l'université d'Heidelberg et leur intégration sur le robot HRP-2. Deux contrôleurs seront présentés, le premier permettant la locomotion multi-contacts avec une connaissance a priori des futures positions des contacts. Le deuxième étant une extension d'un travail réalisé sur de la marche sur sol plat améliorant les performances et ajoutant des fonctionnalitées au précédent algorithme. En collaborant avec des spécialistes du mouvement humain nous avons implementé un contrôleur innovant permettant de suivre des trajectoires cycliques du centre de masse. Nous présenterons aussi un contrôleur corps-complet utilisant, pour le haut du corps, des primitives de mouvements extraites du mouvement humain et pour le bas du corps, un générateur de marche. Les résultats de cette thèse ont été intégrés dans la suite logicielle "Stack-of-Tasks" du LAAS-CNRS.This thesis covers the topic of humanoid robot locomotion in the frame of the European project KoroiBot. The goal of this project is to enhance the ability of humanoid robots to walk in a dynamic and versatile fashion as humans do. Research and innovation studies in KoroiBot rely on optimal control methods both for the identification of cost functions used by human being and for their implementations on robots owned by roboticist partners. Hence, this thesis includes fruitful collaborations with both control mathematicians and experts in motion primitive modeling. The main contributions of this PhD thesis lies in the design of new real time controllers for humanoid robot locomotion with our partners from the University of Heidelberg and their integration on the HRP-2 robot. Two controllers will be shown, one allowing multi-contact locomotion with a prior knowledge of the future contacts. And the second is an extension of a previous work improving performance and providing additional functionalities. In a collaboration with experts in human motion we designed an innovating controller for tracking cyclic trajectories of the center of mass. We also show a whole body controller using upper body movement primitives extracted from human behavior and lower body movement computed by a walking pattern generator. The results of this thesis have been integrated into the LAAS-CNRS "Stack-of-Tasks" software suit

On the Use of Torque Measurement in Centroidal State Estimation

State of the art legged robots are either capable of measuring torque at the output of their drive systems, or have transparent drive systems which enable the computation of joint torques from motor currents. In either case, this sensor modality is seldom used in state estimation. In this paper, we propose to use joint torque measurements to estimate the centroidal states of legged robots. To do so, we project the whole-body dynamics of a legged robot into the nullspace of the contact constraints, allowing expression of the dynamics independent of the contact forces. Using the constrained dynamics and the centroidal momentum matrix, we are able to directly relate joint torques and centroidal states dynamics. Using the resulting model as the process model of an Extended Kalman Filter (EKF), we fuse the torque measurement in the centroidal state estimation problem. Through real-world experiments on a quadruped robot with different gaits, we demonstrate that the estimated centroidal states from our torque-based EKF drastically improve the recovery of these quantities compared to direct computation

Torque Controlled Locomotion of a Biped Robot with Link Flexibility

When a big and heavy robot moves, it exerts large forces on the environment and on its own structure, its angular momentum can varysubstantially, and even the robot's structure can deform if there is a mechanical weakness. Under these conditions, standard locomotion controllers can fail easily. In this article, we propose a complete control scheme to work with heavy robots in torque control. The full centroidal dynamics is used to generate walking gaits online, link deflections are taken into account to estimate the robot posture and all postural instructions are designed to avoid conflicting with each other, improving balance. These choices reduce model and control errors, allowing our centroidal stabilizer to compensate for the remaining residual errors. The stabilizer and motion generator are designed together to ensure feasibility under the assumption of bounded errors. We deploy this scheme to control the locomotion of the humanoid robot Talos, whose hip links flex when walking. It allows us to reach steps of 35~cm, for an average speed of 25~cm/sec, which is among the best performances so far for torque-controlled electric robots.Comment: IEEE-RAS International Conference on Humanoid Robots (Humanoids 2022), IEEE, Nov 2022, Ginowan, Okinawa, Japa

Crocoddyl: An Efficient and Versatile Framework for Multi-Contact Optimal Control

We introduce Crocoddyl (Contact RObot COntrol by Differential DYnamic Library), an open-source framework tailored for efficient multi-contact optimal control. Crocoddyl efficiently computes the state trajectory and the control policy for a given predefined sequence of contacts. Its efficiency is due to the use of sparse analytical derivatives, exploitation of the problem structure, and data sharing. It employs differential geometry to properly describe the state of any geometrical system, e.g. floating-base systems. We have unified dynamics, costs, and constraints into a single concept-action-for greater efficiency and easy prototyping. Additionally, we propose a novel multiple-shooting method called Feasibility-prone Differential Dynamic Programming (FDDP). Our novel method shows a greater globalization strategy compared to classical Differential Dynamic Programming (DDP) algorithms, and it has similar numerical behavior to state-of-the-art multiple-shooting methods. However, our method does not increase the computational complexity typically encountered by adding extra variables to describe the gaps in the dynamics. Concretely, we propose two modifications to the classical DDP algorithm. First, the backward pass accepts infeasible state-control trajectories. Second, the rollout keeps the gaps open during the early "exploratory" iterations (as expected in multiple-shooting methods). We showcase the performance of our framework using different tasks. With our method, we can compute highly-dynamic maneuvers for legged robots (e.g. jumping, front-flip) in the order of milliseconds

Stratégie de marche avancée et inspirée de l'être humain pour les robots humanoïdes

National audienceThis thesis covers the topic of humanoid robot locomotion in the frame of the European project KoroiBot. The goal of this project is to enhance the ability of humanoid robots to walk in a dynamic and versatile fashion as humans do. Research and innovation studies in KoroiBot rely on optimal control methods both for the identification of cost functions used by human being and for their implementations on robots owned by roboticist partners. Hence, this thesis includes fruitful collaborations with both control mathematicians and experts in motion primitive modeling. The main contributions of this PhD thesis lies in the design of new real time controllers for humanoid robot locomotion with our partners from the University of Heidelberg and their integration on the HRP-2 robot. Two controllers will be shown, one allowing multi-contact locomotion with a prior knowledge of the future contacts. And the second is an extension of a previous work improving performance and providing additional functionalities. In a collaboration with experts in human motion we designed an innovating controller for tracking cyclic trajectories of the center of mass. We also show a whole body controller using upper body movement primitives extracted from human behavior and lower body movement computed by a walking pattern generator. The results of this thesis have been integrated into the LAAS-CNRS "Stack-of-Tasks" software suit.Cette thèse traite du problème de la locomotion des robots humanoïdes dans le contexte du projet européen KoroiBot. En s'inspirant de l'être humain, l'objectif de ce projet est l'amélioration des capacités des robots humanoïdes à se mouvoir de façon dynamique et polyvalente. Le coeur de l'approche scientifique repose sur l'utilisation du controle optimal, à la fois pour l'identification des couts optimisés par l'être humain et pour leur mise en oeuvre sur les robots des partenaires roboticiens. Cette thèse s'illustre donc par une collaboration à la fois avec des mathématiciens du contrôle et des spécialistes de la modélisation des primitives motrices. Les contributions majeures de cette thèse reposent donc sur la conception de nouveaux algorithmes temps-réel de contrôle pour la locomotion des robots humanoïdes avec nos collégues de l'université d'Heidelberg et leur intégration sur le robot HRP-2. Deux contrôleurs seront présentés, le premier permettant la locomotion multi-contacts avec une connaissance a priori des futures positions des contacts. Le deuxième étant une extension d'un travail réalisé sur de la marche sur sol plat améliorant les performances et ajoutant des fonctionnalitées au précédent algorithme. En collaborant avec des spécialistes du mouvement humain nous avons implementé un contrôleur innovant permettant de suivre des trajectoires cycliques du centre de masse. Nous présenterons aussi un contrôleur corps-complet utilisant, pour le haut du corps, des primitives de mouvements extraites du mouvement humain et pour le bas du corps, un générateur de marche. Les résultats de cette thèse ont été intégrés dans la suite logicielle "Stack-of-Tasks" du LAAS-CNRS

A Versatile and Efficient Pattern Generator for Generalized Legged Locomotion

International audienceThis paper presents a generic and efficient approach to generate dynamically consistent motions for under-actuated systems like humanoid or quadruped robots. The main contribution is a walking pattern generator, able to compute a stable trajectory of the center of mass of the robot along with the angular momentum, for any given configuration of contacts (e.g. on uneven, sloppy or slippery terrain, or with closed-gripper). Unlike existing methods, our solver is fast enough to be applied as a model-predictive controller. We then integrate this pattern generator in a complete framework: an acyclic contact planner is first used to automatically compute the contact sequence from a 3D model of the environment and a desired final posture; a stable walking pattern is then computed by the proposed solver; a dynamically-stable whole-body trajectory is finally obtained using a second-order hierarchical inverse kinematics. The implementation of the whole pipeline is fast enough to plan a step while the previous one is executed. The interest of the method is demonstrated by real experiments on the HRP-2 robot, by performing long-step walking and climbing a staircase with handrail support

Closed loop control of walking motions with adaptive choice of directions for the iCub humanoid robot

International audienceThe widely spread iCub humanoid robot has proved to be able to walk straight forward by means of an offline pattern generator, which did not allow for online adjustments and interactions. In this paper, we present a closed-loop control framework based on a Nonlinear Model Predictive Control pattern generator with feedback at the Center of Mass (CoM) position. This framework allows us to extend the walking capabilities of iCub to different walking directions, such as curved, sideways and backward walking. When compared to existing methods, the walking speed of iCub is increased by approximately 75% and the step period decreased by 45%. It was successfully tested with a reduced version of the iCub (HeiCub), but it was also shown to be applicable to the full iCub in simulation. The measured outcomes of the experiments are the walking velocity, the cost of transport, tracking precision of the Zero-Moment Point (ZMP), CoM and joint trajectories. The online feedback was shown to improve the walking stability by means of an improvement of the CoM tracking precision by 30% and the ZMP tracking precision by 60% compared to the same method without CoM position feedback control

METAPOD Template META-programming applied to dynamics: CoP-CoM trajectories filtering

International audienceIn this contribution, Metapod, a novel C++ library computing efficiently dynamic algorithms is presented. It uses template-programming techniques together with code-generation. The achieved performances shows some advantage over the state-of-the art dynamic library RBDL mostly on ATOM processor and for the inertia matrix computation, which are relevant for robotics application. On recent desktop computer, the ratio of the gain is not so obvious and in general the time achieved by both library is not significantly different for inverse dynamics. The advantage of this library is that it is open-source and does not rely on any external symbolic computational software. A main drawback is the increase complexity in debugging the code source due to template programming. Additionnaly we show how it can help in current control problems for humanoid robots, and more specifically for dynamic filtering of walking gait trajectories