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Publications de l'équipe gepetto

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393documents trouvés

18021
01/10/2018

Historical Perspective of Humanoid Robot Research in Europe

Y.AOUSTIN, C.CHEVALLEREAU, J.P.LAUMOND

LS2N, GEPETTO

Ouvrage (contribution) : Humanoid Robotics: A Reference, Springer, N°ISBN 978-94-007-6045-5, Octobre 2018 , N° 18021

Lien : https://hal.archives-ouvertes.fr/hal-01697135

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142457
18003
14/06/2018

SLAM and vision-based humanoid navigation

O.STASSE

GEPETTO

Ouvrage (contribution) : Humanoid Robotics: A Reference, Springer, N°ISBN 978-94-007-6047-9, Juin 2018, 22p. , N° 18003

Lien : https://hal.archives-ouvertes.fr/hal-01674512

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142073
18065
14/03/2018

CROC: Convex Resolution Of Centroidal dynamics trajectories to provide a feasibility criterion for the multi contact planning problem

P.FERNBACH, S.TONNEAU, M.TAIX

GEPETTO

Rapport LAAS N°18065, Mars 2018, 7p.

Lien : https://hal.archives-ouvertes.fr/hal-01726155

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Abstract

We present a novel method for computing centroidal dynamic trajectories in multi-contact planning context. With dynamic motion it is necessary to respect kinematic and dynamic constraints during the contact planning step. Verifying the feasibility of a transition between contacts increase the success rate of the motion generation along the planned contacts. Our approach is based on a conservative but convex reformulation of the problem where we represent the center of mass trajectory as a Bezier curve, with control points constrained by the initial and final states and one free control point. Thanks to the convexity of this formulation, we can solve it efficiently with a Linear Program of low dimension. We use this LP as a feasibility criterion to test the contact transition candidates during multi-contact planning. By incorporating this criterion in an existing sampling-based contact planner, we are able to produce more robust contact sequences. We illustrate this application on various multi-contact scenarios. We also show that we can compute valuable initial guess, used to warm-start non-linear solvers for motion generation methods. This method could also be used for the 0 and 1-Step capturability problem.

142835
18051
01/02/2018

How do walkers behave when crossing the way of a mobile robot that replicates human interaction rules?

C.VASSALLO, A.H.OLIVIER, P.SOUERES, A.CRETUAL, O.STASSE, J.PETTRE

GEPETTO, M2S, IRISA

Revue Scientifique : Gait & Posture, Vol.60, pp.188-193, Février 2018 , N° 18051

Lien : https://hal-univ-rennes1.archives-ouvertes.fr/hal-01717722

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Abstract

Previous studies showed the existence of implicit interaction rules shared by human walkers when crossing each other. Especially, each walker contributes to the collision avoidance task and the crossing order, as set at the beginning, is preserved along the interaction. This order determines the adaptation strategy the first arrived increases his/her advance by slightly accelerating and changing his/her heading, whereas the second one slows down and moves in the opposite direction. In this study, we analyzed the behavior of human walkers crossing the trajectory of a mobile robot that was programmed to reproduce this human avoidance strategy. In contrast with a previous study, which showed that humans mostly prefer to give the way to a non-reactive robot, we observed similar behaviors between human-human avoidance and human-robot avoidance when the robot replicates the human interaction rules. We discuss this result in relation with the importance of controlling robots in a human-like way in order to ease their cohabitation with humans.

142781
18005
29/01/2018

Strain localization within a syn-tectonic intrusion in a back-arc extensional context : the Naxos monzogranite (Greece)

E.BESSIERE, A.RABILLARD, J.PRECIGOUT, L.ARBARET, L.JOLIVET, R.AUGIER, A.MENANT, N.MANSARD

ISTO, GEPETTO

Revue Scientifique : Tectonics, Janvier 2018, DOI: 10.1002/2017TC004801 , N° 18005

Lien : https://hal-insu.archives-ouvertes.fr/insu-01680181

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Abstract

Although fundamental to the understanding of crustal dynamics in extensional setting, the relationships between the emplacement of granitic intrusions and activity of detachments still remain very elusive. Through a multi-scale approach, we here document a continuous deformation history between the monzogranitic intrusion of Naxos and the Naxos-Paros Detachment System (Cyclades, Greece). Field observations first show an early magmatic deformation followed by solid-state, ductile and then brittle deformation when approaching the detachment zone, as evidenced by the overprinting of mylonites by cataclastes and pseudotachylites. From these observations, we define six strain facies that characterize a positive strain gradient from core to rim of the Naxos monzogranite. Based on field pictures, X-ray tomography and Electron BackScatter Diffraction (EBSD) analyses along the strain gradient, we then quantify the intensity of mineralogical fabrics in 2D and 3D and better characterize the deformation mechanisms. Our measured shape variations of the strain ellipsoid corroborate the large-scale strain gradient, showing a good correlation between qualitative and quantitative studies. In addition, EBSD data indicate that dislocation creep was predominant during cooling from more than 500°C to temperature conditions of the ductile-to-brittle transition. However, 1) a weakening of quartz lattice preferred orientation with increasing strain and 2) evidence of numerous four-grain junctions in high-strain shear bands also indicate that grain boundary sliding significantly contributed to the deformation. Although the source of grain boundary sliding remains to be constrained, it provides a consistent approach to account for strain localization in Naxos.

142172
16242
01/01/2018

Joint position and velocity bounds in discrete-time acceleration/torque control of robot manipulators

A.DEL PRETE

GEPETTO

Revue Scientifique : IEEE Robotics and Automation Letters, Vol.3, N°1, pp.281-288, Janvier 2018, DOI: 10.1109/LRA.2017.2738321 , N° 16242

Lien : https://hal.archives-ouvertes.fr/hal-01356989

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Abstract

This letter deals with the problem of controlling a robotic system whose joints have bounded position, velocity, and acceleration/torque. Assuming a discrete-time acceleration control, we compute tight bounds on the current joint accelerations that ensure the existence of a feasible trajectory in the future. Despite the clear practical importance of this issue, no complete and exact solution has been proposed yet, and all existing control architectures rely on hand-tuned heuristics. We also extend this methodology to torque-controlled robots, for which joint accelerations are only indirectly bounded by the torque limits. Numerical simulations are presented to validate the proposed method, which is computationally efficient and hence suitable for high-frequency control.

140657
17519
13/12/2017

Handling uncertainty and variability in robot control

N.GIFTSUN

GEPETTO

Doctorat : INSA de Toulouse, 13 Décembre 2017, 115p., Président: P.PLOEGER, Rapporteurs: V.PADOIS, Examinateurs: A.DEL PRETE, Directeurs de thèse: F.LAMIRAUX , N° 17519

Lien : https://hal.laas.fr/tel-01713007

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Abstract

Amidst a lot of research in motion planning and control in concern with robotic applications, the mankind has never reached a point yet, where the robots are perfectly functional and autonomous in dynamic settings. Though it is controversial to discuss about the necessity of such robots, it is very important to address the issues that stop us from achieving such a level of autonomy. Industrial robots have evolved to be very reliable and highly productive with more than 1.5 million operational robots in a variety of industries. These robots work in static settings and they literally do what they are programmed for specific usecases, though the robots are flexible enough to be programmed for a variety of tasks. This research work makes an attempt to address these issues that separate both these settings in a profound way with special focus on uncertainties. Practical impossibilities of precise sensing abilities lead to a variety of uncertainties in scenarios where the robot is mobile or the environment is dynamic. This work focuses on developing smart strategies to improve the ability to handle uncertainties robustly in humanoid and industrial robots. First, we focus on a dynamical obstacle avoidance framework proposed for industrial robots equipped with skin sensors for reactivity. Path planning and motion control are usually formalized as separate problems in robotics. High dimensional configuration spaces, changing environment and uncertainties do not allow to plan real-time motion ahead of time requiring a controller to execute the planned trajectory. The fundamental inability to unify both these problems has led to handle the planned trajectory amidst perturbations and unforeseen obstacles using various trajectory execution and deformation mechanisms. The proposed framework uses ’Stack of Tasks’, a hierarchical controller using proximity information to avoid obstacles. Experiments are performed on a UR5 robot to check the validity of the framework and its potential use for collaborative robot applications. Second, we focus on a strategy to model inertial parameters uncertainties in a balance controller for legged robots. Model-based control has become more and more popular in the legged robots community in the last ten years. The key idea is to exploit a model of the system to compute precise motor commands that result in the desired motion. This allows to improve the quality of the motion tracking, while using lower feedback gains, leading so to higher compliance. However, the main flaw of this approach is typically its lack of robustness to modeling errors. In this paper we focus on the robustness of inverse-dynamics control to errors in the inertial parameters of the robot. We assume these parameters to be known, but only with a certain accuracy. We then propose a computationally-efficient optimization-based controller that ensures the balance of the robot despite these uncertainties. We used the proposed controller in simulation to perform different reaching tasks with the HRP-2 humanoid robot, in the presence of various modeling errors. Comparisons against a standard inverse-dynamics controller through hundreds of simulations show the superiority of the proposed controller in ensuring the robot balance.

142375
17608
12/12/2017

Planification interactive de mouvement avec contact

N.BLIN

GEPETTO

Doctorat : INP de Toulouse, Décembre 2017, 134p., Président: R.ZAPATA, Rapporteurs: V.PERDEREAU, B.FOUAD, Examinateurs: , Directeurs de thèse: J.Y.FOURQUET, M.TAIX, P.FILLATREAU , N° 17608

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Abstract

Designing new industrial products requires to develop prototypes prior to their launch phase. An interesting solution to speedup the development phase and reduce its costs is to use virtual prototypes as long as possible. Some steps of the development consist in assembly or disassembly operations. These operations can be done manually or automatically using a motion planning algorithm. Motion planning is a method allowing a computer to simulate the motion of an object from a start point to a goal point while avoiding obstacles. The following research work brings solutions for the interaction between a human operator and a motion planning algorithm of virtual objects for the exploration of free space. Research time is split between the human and the machine according to an authority sharing parameter determining the percentage of time allocated to one or the other entity. The simultaneous use of a human and a machine greatly speedup the exploration in comparison to the time needed by any of the former two alone. This work then presents a new interactive motion planner with contact. This method permits to generate trajectories at the surface of obstacles instead of free space trajectories. Contact motion planning allows specific operations such as sliding or insertion. This greatly diminishes the solving time of motion planning problems in cluttered environments. Detecting the intentions of a user when he interacts with a machine is a good way to convey orders efficiently and intuitively. An algorithm for interactive contact planning with intention detection techniques is proposed. This algorithm uses a haptic robot allowing a user to feel virtual obstacles when manipulating a virtual object in a virtual reality environment. The interactive algorithm adapts to the actions of the user in real time for a pertinent exploration of the surfaces of obstacles. This work has been done partly in LAAS-CNRS laboratory in Toulouse in Gepetto team and partly in LGP-ENIT laboratory in Tarbes in DIDS team. We wish to thank the Midi-Pyrénées region for funding this research.

Résumé

La conception de nouveaux produits industriels nécessite le développement de prototypes avant leur déploiement grand public. Afin d’accélérer cette phase et de réduire les coûts qui en découlent, une solution intéressante consiste a utiliser des prototypes virtuels le plus longtemps possible en particulier dans la phase de conception. Certaines des étapes de la conception consistent à effectuer des opérations d’assemblage ou de désassemblage. Ces opérations peuvent être effectuées manuellement ou automatiquement à l’aide d’un algorithme de planification de mouvement. La planification de mouvement est une méthode permettant à un ordinateur de simuler le déplacement d’un objet d’un point de départ à un point d’arrivée tout en évitant les obstacles. Le travail de recherche de cette thèse apporte des solutions afin d’améliorer l’interaction entre un humain et un algorithme de planification de mouvement pendant l’exploration de l’espace libre. Le temps de recherche est partagé entre l’humain et la machine selon un paramètre de partage d’autorité permettant de déterminer le pourcentage d’allocation du temps à l’une ou l’autre entité. L’utilisation simultanée de ces deux entités permet d’accélérer grandement la vitesse d’exploration par rapport à la vitesse d’un humain seul ou d’un algorithme seul. Ces travaux apportent ensuite une nouvelle méthode de planification de mouvement avec contact permettant de générer des trajectoires à la surface des obstacles au lieu de les générer uniquement dans l’espace libre. La planification au contact permet d’effectuer des opérations spécifiques telles que le glissement ou l’insertion utiles pour la résolution de problèmes de planification dans des environnements encombrés. Enfin, détecter les intentions d’un utilisateur lorsqu’il interagit avec une machine permet de lui fournir des ordres efficacement et intuitivement. Dans le cadre de la planification interactive au contact, un algorithme de détection d’intention est proposé. Ce dernier s’appuie sur l’utilisation d’un robot haptique permettant à un opérateur de ressentir les obstacles virtuels lors de la manipulation d’un objet virtuel dans un environnement de réalité virtuelle. L’algorithme interactif s’adapte en temps réel aux actions de l’opérateur pour une exploration pertinente de la surface des obstacles. Ces travaux ont été menés en partie au laboratoire toulousain LAAS au sein de l’équipe Gepetto et en partie dans le laboratoire LGP de l’ENIT au sein de l’équipe DIDS. Nous remercions la région Midi-Pyrénées pour avoir financé ces recherches.

Mots-Clés / Keywords
Planification au contact; Planification de mouvement; Robotique; Informatique; Réalité virtuelle; Retour haptique; Détection d'intention; Computer science; Robotics; Motion planning; Virtual reality; Haptic feedback; Intention detection;

143213
16162
11/12/2017

The Yoyo-Man

J.P.LAUMOND, M.BENALLEGUE, J.CARPENTIER, A.BERTHOZ

GEPETTO, AIST, LPPA

Revue Scientifique : International Journal of Robotics Research, Vol.36, N°13-14, pp.1508-1520, Décembre 2017, DOI 10.1177/0278364917693292 , N° 16162

Lien : https://hal.archives-ouvertes.fr/hal-01316032

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The paper reports on two results issued from a multidisciplinary research action tending to explore the motor synergies of anthropomorphic walking. By combining biomechanics, neurophysiology and robotics perspectives, it is intended to better understand the human locomotion with the ambition to better design bipedal robot architectures. The motivation of the research starts from the simple observation that humans may stumble when following a simple reflex-based locomotion on uneven terrains. The rationale combines two well established results in robotics and neuroscience respectively: • Passive robot walkers, which are very efficient in terms of energy consumption, can be modelled by a simple rotating rimless wheel; • Humans and animals stabilize their head when moving. The seminal hypothesis is then to consider a wheel equipped with a top-down control as a plausible model of bipedal walking. The two results presented in the paper comfort the hypothesis: • From a motion capture data basis of twelve human walkers we first identify the center of mass (CoM) as a geometric center from which the motions of the feet are organized. • After introducing a ground texture model that allows to quantify the stability performance of walker control schemes, we show how compass-like passive walkers are better controlled when equipped with a stabilized 2-degree-of-freedom moving mass on top of them. CoM and head then play complementary roles that define what we call the Yoyo-Man. Beyond the two results presented in the paper, the Yoyo-Man model opens new perspectives to explore the computational foundations of anthropomorphic walking.

141740
17448
11/12/2017

Zero step capturability for legged robots in multi contact

A.DEL PRETE, S.TONNEAU, N.MANSARD

GEPETTO

Rapport LAAS N°17448, Décembre 2017, 14p.

Lien : https://hal.archives-ouvertes.fr/hal-01574687

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The ability to anticipate a fall is fundamental for any robot that has to balance. Currently, fast fall-prediction algorithms only exist for simple models, such as the Linear Inverted Pendulum Model (LIPM), whose validity breaks down in multi-contact scenarios (i.e. when contacts are not limited to a flat ground). This paper presents a fast fall-prediction algorithm based on the point-mass model, which remains valid in multi-contact scenarios. The key assumption of our algorithm is that, in order to come to a stop without changing its contacts, a robot only needs to accelerate its center of mass in the direction opposite to its velocity. This assumption allows us to predict the fall by means of a convex optimal control problem, which we solve with a fast custom algorithm (less than 10 ms of computation time). We validated the approach through extensive simulations with the humanoid robot HRP-2 in randomly-sampled scenarios. Comparisons with standard LIPM-based methods demonstrate the superiority of our algorithm in predicting the fall of the robot, when controlled with a state-of-the-art balance controller. This work lays the foundations for the solution of the challenging problem of push recovery in multi-contact scenarios.

141722
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