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Publications de l'équipe gepetto

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376documents trouvés

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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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
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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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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17340
03/10/2017

Geometric and Numerical Foundations of Movements

J.P.LAUMOND, N.MANSARD, J.B.LASSERRE

GEPETTO, MAC

Ouvrage (éditeur) : Geometric and Numerical Foundations of Movements, Springer, N°ISBN 978-3-319-51546-5, Octobre 2017, 425p. , N° 17340

Lien : https://hal.laas.fr/hal-01590779

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This book aims at gathering roboticists, control theorists, neuroscientists, and mathematicians, in order to promote a multidisciplinary research on movement analysis. It follows the workshop “ Geometric and Numerical Foundations of Movements ” held at LAAS-CNRS in Toulouse in November 2015[1]. Its objective is to lay the foundations for a mutual understanding that is essential for synergetic development in motion research. In particular, the book promotes applications to robotics --and control in general-- of new optimization techniques based on recent results from real algebraic geometry.

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17347
03/10/2017

Using a memory of motion to efficiently warm-start a nonlinear predictive controller

N.MANSARD, A.DEL PRETE, M.GEISERT, S.TONNEAU, O.STASSE

GEPETTO

Rapport LAAS N°17347, Octobre 2017, 9p.

Lien : https://hal.archives-ouvertes.fr/hal-01591373

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Abstract

Predictive control is an efficient model-based methodology to control complex dynamical systems. In general, it boils down to the resolution at each control cycle of a large nonlinear optimization problem. A critical issue is then to provide a good guess to initialize the nonlinear solver so as to speed up convergence. This is particularly important when disturbances or changes in the environment prevent the use of the trajectory computed at the previous control cycle as initial guess. In this paper, we introduce an original and very efficient solution to automatically build this initial guess. We propose to rely on off-line computation to build an approximation of the optimal trajectories, that can be used on-line to initialize the predictive controller. To that end, we combined the use of sampling-based planning, policy learning with generic representations (such as neural networks), and direct optimal control. We first propose an algorithm to simultaneously build a kinodynamic probabilistic roadmap (PRM) and approximate value function and control policy. This algorithm quickly converges toward an approximation of the optimal state-control trajectories (along with an optimal PRM). Then, we propose two methods to store the optimal trajectories and use them to initialize the predictive controller. We experimentally show that directly storing the state-control trajectories leads the predictive controller to quickly converges (2 to 5 iterations) toward the (global) optimal solution. The results are validated in simulation with an unmanned aerial vehicle (UAV) and other dynamical systems.

141128
17095
28/09/2017

Online payload identification for quadruped robots

G.TOURNOIS, M.FIOCCHI, A.DEL PRETE, R.ORSOLINO, D.G.CALDWELL, C.SEMINI

IIT, Genova, GEPETTO

Manifestation avec acte : IEEE/RSJ International Conference on Intelligent Robots and Systems ( IROS ) 2017 du 24 septembre au 28 septembre 2017, Vancouver (Canada), Septembre 2017, 8p. , N° 17095

Lien : https://hal.laas.fr/hal-01575033

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Abstract

The identification of inertial parameters is crucial to achieve high-performance model-based control of legged robots. The inertial parameters of the legs are typically not altered during expeditions and therefore are best identified offline. On the other hand, the trunk parameters depend on the modules mounted on the robot, like a motor to provide the hydraulic power, or different sets of cameras for perception. This motivates the use of recursive approaches to identify online mass and the position of the Center of Mass (CoM) of the robot trunk, when a payload change occurs. We propose two such approaches and analyze their robustness in simulation. Furthermore, experimental trials on our 80-kg quadruped robot HyQ show the applicability of our strategies during locomotion to cope with large payload changes that would otherwise severely compromise the balance of the robot.

140693
17054
24/09/2017

A Kinodynamic steering-method for legged multi-contact locomotion

P.FERNBACH, S.TONNEAU, A.DEL PRETE, M.TAIX

GEPETTO

Manifestation avec acte : IEEE/RSJ International Conference on Intelligent Robots and Systems ( IROS ) 2017 du 24 septembre au 28 septembre 2017, Vancouver (Canada), Septembre 2017, 7p. , N° 17054

Lien : https://hal.laas.fr/hal-01486933

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We present a novel method for synthesizing collision-free, dynamic locomotion behaviors for legged robots, including jumping, going down a very steep slope, or recovering from a push using the arms of the robot. The approach is automatic and generic: non-gaited motions, comprising arbitrary contact postures can be generated along any environment. At the core of our framework is a new steering method that generates trajectories connecting two states of the robot. These trajectories account for the state-dependent, centroidal dynamic constraints inherent to legged robots. The method, of low dimension, formulated as a Linear Program, is really efficient to compute, and can find an application in various problems related to legged locomotion. By incorporating this steering method into an existing sampling-based contact planner, we propose the first kinodynamic contact planner for legged robots.

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17313
21/09/2017

Modification of the spontaneous seat-to-stand transition in cycling with bodyweight and cadence variations

B.WATIER, A.COSTES, N.TURPIN

GEPETTO, Toulouse III, CRIR

Rapport LAAS N°17313, doi 10.1016/j.jbiomech.2017.08.003, Septembre 2017

Lien : https://hal.laas.fr/hal-01584024

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When a high power output is required in cycling, a spontaneous transition by the cyclist from a seated to a standing position generally occurs. In this study, by varying the cadence and cyclist bodyweight, we tested whether the transition is better explained by the greater power economy of a standing position or by the emergence of mechanical constraints that force cyclists to stand. Ten males participated in five experimental sessions corresponding to different bodyweights (80%, 100%, or 120%) and cadences (50 RPM, 70 RPM, or 90 RPM). In each session, we first determined the seat-to-stand transition power (SSTP) in an incremental test. The participants then cycled at 20%, 40%, 60%, 80%, 100%, or 120% of the SSTP in the seated and standing positions, for which we recorded the saddle forces and electromyogram (EMG) signals of eight lower limb muscles. We estimated the cycling cost using an EMG cost function (ECF) and the minimal saddle forces in the seated position as an indicator of the mechanical constraints. Our results show the SSTP to vary with respect to both cadence and bodyweight. The ECF was lower in the standing position above the SSTP value (i.e., at 120%) in all experimental sessions. The minimal saddle forces varied significantly with respect to both cadence and bodyweight. These results suggest that optimization of the muscular cost function, rather than mechanical constraints, explain the seat-to-stand transition in cycling.

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17277
06/09/2017

Experimental evaluation of simple estimators for humanoid robots

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

GEPETTO, UND, AIST

Rapport LAAS N°17277, Septembre 2017, 7p.

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

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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.

140663
17249
04/09/2017

A human-inspired mechanical criterion for multi-contact locomotion in humanoids

F.BAILLY, J.CARPENTIER, B.PINET, P.SOUERES, B.WATIER

GEPETTO

Rapport LAAS N°17249, Septembre 2017, 7p.

Lien : https://hal.laas.fr/hal-01569252

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This work aims at experimentally identifying a mechanical principle of locomotion stability in humans and demonstrating that this principle can be used for generating stable multi-contact motions for humanoids. For this purpose, a destabilizing setup was built on which five different experiments were carried out by 15 human volunteers. We first show experimentally that when humans balance is perturbed (walking on a destabilizing setup, increasing walking speed, grasping or not a fixed element), the distance between the center of mass (CoM) and the central axis of the external contact wrench significantly increases. This result is coupled with a theoretical reasoning in mechanics in order to exhibit how lowering this distance amounts to lower the body's angular acceleration and thus constitutes a good strategy against falling. Finally, we illustrate the interest of this result for humanoid robot motion generation by embedding the minimization of the distance between the CoM and the central axis of the external contact wrench in an optimal control formulation in order generate multi-contact locomotion.

140582
17400
01/09/2017

Robot Choreography: the use of the kinetography laban system to notate robot action and motion

P.SALARIS, N.ABE, J.P.LAUMOND

INRIA Sophia, GEPETTO

Revue Scientifique : IEEE Robotics and Automation Magazine, Vol.24, N°3, pp.30-40, Septembre 2017 , N° 17400

Lien : https://hal.inria.fr/hal-01623920

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Roboticists aim to segment robot actions into a sequence of motion primitives to simplify the robot programming phase. Choreographers aim to capture the essence of human body movements within a sequence of symbols that can be understood by dancers. To that extent, roboticists and choreographers pursue the same quest. We have undertaken a pluridisciplinary approach, combining a dance notation system (the Kinetography Laban system) with a robot programming system [the Stack of Task (SoT)]. Motion scores are used instead of quantitative data to compare and enlighten differences in robot and human movements. We then discuss plausible origins of these differences, taking into account the implicit rules of the Kinetography Laban system on how a movement is executed by humans. This comparison, in the light of the Kinetography Laban system, opens some challenging questions related to motion segmentation and motion naturalness.

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