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Publications de l'équipe gepetto

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387documents trouvés

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
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
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, 12p., Décembre 2017, DOI 10.1177/0278364917693292 , N° 16162

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

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Abstract

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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Abstract

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
17441
08/12/2017

Motion planning for challenging locomotion: a study of decoupled and coupled approaches

C.MASTALLI, I.HAVOUTIS, M.FOCCHI, D.G.CALDWELL, C.SEMINI

GEPETTO, IIT, Genova

Rapport LAAS N°17441, Décembre 2017, 21p.

Lien : https://hal.archives-ouvertes.fr/hal-01649836

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Abstract

Legged robots promise an advantage over traditional wheeled systems as they can offer greater mobility on challenging terrain. However, most legged robots are still confined to structured and flat environments. One of the main reasons for this is the difficulty in planning complex whole-body motions while taking into account the terrain conditions. Previous research in locomotion mainly focused either on generating reactive behaviors, that tackle small terrain changes, or on kinematically planning foothold locations with partial terrain information. Alternatively, legged motion planning approaches focus on synthesizing complex whole-body motions, but often do not consider terrain characteristics. This problem is high-dimensional; it requires to consider the robot's dynamics together with the terrain model in a suitable problem formulation. In this work, we address these challenges by studying two different motion planning methods: decoupled and coupled foothold and motion planning. First, we present a locomotion framework that kinematically plans online the foothold sequences from the terrain costmap and then generates dynamic whole-body motions (decoupled planning). For that, we build online and onboard the terrain costmap. Second, we propose a novel trajectory and foothold optimization method that plans dynamically both foothold locations and CoM motions (coupled planning). This second method jointly optimizes body motion, step duration and foothold selection considering the terrain topology. Finally, we include in our framework a whole-body controller that tracks compliantly trunk motions while avoids slippage, kinematic and torque limits. Additionally, we impose friction cone constraints in real-time using the estimated terrain normals from the terrain map. With the novel locomotion framework we can cross a wider range of terrain conditions compared with previous approaches validated on the hydraulic quadruped robot-HyQ. In fact, our coupled motion planner can be easily generalized to various terrain conditions (i.e. without re-tuning) thanks to a parametrized dynamic model, and an online terrain mapping for real-time whole-body control. We report it through experimental results and comparative evaluations.

141706
17418
05/12/2017

Angular momentum regulation strategies for highly dynamic landing in Parkour

G.MALDONADO, F.BAILLY, P.SOUERES, B.WATIER

GEPETTO

Revue Scientifique : Computer Methods in Biomechanics and Biomedical Engineering, Vol.20, pp.123-124, Décembre 2017 , N° 17418

Lien : https://hal.archives-ouvertes.fr/hal-01636353

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Abstract

Previous studies have shown that angular momentum is regulated during daily life activities like walking and during dynamic motions such as somersaults and twists. In this paper, we propose to extend these works by studying how the regulation of the angular momentum derivative AMD contributes to mechanical stability after a highly dynamic drop. To this end, five healthy Parkour experts participated in this study and were asked to perform the Parkour precision landing technique. The derivative of angular momentum expressed at the center of mass position and the contribution of each segment to its variation were analyzed. Results show that the AMD is regulated to zero throughout landing. Our study also reveals complex whole-body strategies of Parkour practitioners such as opposed segment cancellations and a temporal organization of the motion. This study provides a new basis to better understand dynamic landing performances. Results could also be used to generate landing motions with humanoid robots or virtual avatars (human-inspired motion).

141639
17483
01/12/2017

Motion planning for quadrupedal locomotion: coupled planning, terrain mapping and whole-body control

C.MASTALLI, I.HAVOUTIS, M.FOCCHI, D.G.CALDWELL, C.SEMINI

GEPETTO, IIT, Genova

Rapport LAAS N°17483, Décembre 2017, 21p.

Lien : https://hal.laas.fr/hal-01673438

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Abstract

Legged robots promise an advantage over traditional wheeled systems as they can offer greater mobility on challenging terrain. However, most legged robots are still confined to structured and flat environments. One of the main reasons for this is the difficulty in planning complex whole-body motions while taking into account the terrain conditions. Previous research in locomotion mainly focused either on generating reactive behaviors, that tackle only small terrain changes, or on kinematically planning foothold locations with partial terrain information. Alternatively, legged motion planning approaches focus on synthesizing complex whole-body motions, but often do not consider terrain characteristics. This problem is very high-dimensional as it considers the robot's dynamics together with the terrain model in a suitable problem formulation. In this work, we address these challenges by studying two different motion planning methods (decoupled and coupled foothold and motion planning), and by analyzing the effect of considering friction cones, kinematic limits and torque limits at the whole-body control level. For that, we first briefly introduce our decoupled motion planning approach. Second, we propose a novel trajectory and foothold optimization method that plans dynamically both foothold locations and CoM motions (coupled planning). This second method jointly optimizes body motion, step duration and foothold selection, considering the terrain topology. Finally, we introduce a whole-body controller that tracks compliantly trunk motions while avoiding slippage as well as kinematic and torque limits. Additionally, we impose friction cone constraints in real-time using terrain normals estimated from the terrain map. With this novel locomotion framework we can cross a wide range of terrain conditions—significantly more compared our previous approach—while we validate our novel framework on the hydraulic quadruped robot; HyQ. Additionally, our coupled motion planner can be easily generalize to various terrain conditions, thanks to a parametrized dynamic model, and an online terrain mapping that is used in our real-time whole-body controller. We report thorough experimental results and comparative evaluations over a set of terrains of progressively increasing difficulty.

142064
17055
17/11/2017

TALOS: A new humanoid research platform targeted for industrial applications

O.STASSE, T.FLAYOLS, R.BUDHIRAJA, K.GIRAUD ESCLASSE, J.CARPENTIER, A.DEL PRETE, P.SOUERES, N.MANSARD, F.LAMIRAUX, J.P.LAUMOND, L.MARCHIONNI, H.TOME, F.FERRO

GEPETTO, Pal Robotics

Manifestation avec acte : IEEE-RAS International Conference on Humanoid Robots ( HUMANOIDS ) 2017 du 15 novembre au 17 novembre 2017, Birmingham (UK), Novembre 2017, 8p. , N° 17055

Lien : https://hal.archives-ouvertes.fr/hal-01485519

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Abstract

The upcoming generation of humanoid robots will have to be equipped with state-of-the-art technical features along with high industrial quality, but they should also offer the prospect of effective physical human interaction. In this paper we introduce a new humanoid robot capable of interacting with a human environment and targeting a whole range of industrial applications. This robot is able to handle weights of 6 Kg with an outstretched arm, and has powerful motors to carry out movements unavailable in previous generations of humanoid robots. Its kinematics has been specially designed for screwing and drilling motions. In order to make interaction possible with human operators, this robot is equipped with torque sensors to measure joint effort and high resolution encoders to measure both motor and joint positions. The humanoid robotics field has reached a stage where robustness and repeatibility is the next watershed. We believe that, this robot has the potential to become a powerful tool for the research community to successfully navigate this turning point, as the humanoid robot HRP-2 was in its own time.

141593
17277
17/11/2017

Experimental evaluation of simple estimators for humanoid robots

T.FLAYOLS, A.DEL PRETE, P.WENSING, A.MIFSUD, M.BENALLEGUE, O.STASSE

GEPETTO, UND, AIST

Manifestation avec acte : IEEE-RAS International Conference on Humanoid Robots ( HUMANOIDS ) 2017 du 15 novembre au 17 novembre 2017, Birmingham (UK), Novembre 2017, 7p. , N° 17277

Lien : https://hal.archives-ouvertes.fr/hal-01574819

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Abstract

This paper introduces and evaluates a family of new simple estimators to reconstruct the pose and velocity of the floating base. The estimation of the floating-base state is a critical challenge to whole-body control methods that rely on full-state information in high-rate feedback. Although the kinematics of grounded limbs may be used to estimate the pose and velocity of the body, modelling errors from ground irregularity, foot slip, and structural flexibilities limit the utility of estimation from kinematics alone. These difficulties have motivated the development of sensor fusion methods to augment body-mounted IMUs with kinematic measurements. Existing methods often rely on extended Kalman filtering, which lack convergence guarantees and may present difficulties in tuning. This paper proposes two new simplifications to the floating-base state estimation problem that make use of robust off-the-shelf orientation estimators to bootstrap development. Experiments for in-place balance and walking with the HRP-2 show that the simplifications yield results on par with the accuracy reported in the literature for other methods. As further benefits, the structure of the proposed estimators prevents divergence of the estimates, simplifies tuning, and admits efficient computation. These benefits are envisioned to help accelerate the development of baseline estimators in future humanoids.

141594
17381
23/10/2017

2PAC: Two point attractors for center of mass trajectories in multi contact scenarios

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

GEPETTO, IRISA

Rapport LAAS N°17381, https://hal.archives-ouvertes.fr/hal-01609055, Octobre 2017, 10p.

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Abstract

Synthesizing motions for legged characters in arbitrary environments is a long-standing problem that has recently received a lot of attention from the computer graphics community. We tackle this problem with a procedural approach that is generic, fully automatic and independent from motion capture data. The main contribution of this paper is a point-mass-model-based method to synthesize Center Of Mass trajectories. These trajectories are then used to generate the whole-body motion of the character. The use of a point mass model often results in physically inconsistent motions and joint limit violations. We mitigate these issues through the use of a novel formulation of the kinematic constraints which allows us to generate a quasi-static Center Of Mass trajectory, in a way that is both user-friendly and computationally efficient. We also show that the quasi-static constraint can be relaxed to generate motions usable for applications of computer graphics (on average 83% of a given trajectory remain physically consistent). Our method was integrated in our open-source contact planner and tested with different scenarios-some never addressed before-featuring legged characters performing non-gaited motions in cluttered environments. The computational efficiency of our trajectory generation algorithm (under ten ms to compute one second of motion) enables us to synthesize motions in a few seconds, one order of magnitude faster than state-of-the-art methods.

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