The Experts below are selected from a list of 57873 Experts worldwide ranked by ideXlab platform

Jean-paul Laumond - One of the best experts on this subject based on the ideXlab platform.

  • Vision-guided motion primitives for humanoid reactive walking: Decoupled versus coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    This paper proposes a novel visual servoing approach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of model predictive control MPC to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists of, first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC-based approach allows to avoid a number of limitations that appears in decoupled methods. In particular, visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence.

  • Vision-guided motion primitives for humanoid reactive walking: Decoupled versus coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    International audienceThis paper proposes a novel visual servoing ap-proach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of Model Predictive Control (MPC) to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists in first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC based approach allows to avoid a number of limitations that appears in decoupled methods. In particular visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence

  • Vision-guided motion primitives for humanoid reactive walking: decoupled vs. coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    This paper proposes a novel visual servoing ap-proach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of Model Predictive Control (MPC) to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists in first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC based approach allows to avoid a number of limitations that appears in decoupled methods. In particular visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence.

Claire Dune - One of the best experts on this subject based on the ideXlab platform.

  • Vision-guided motion primitives for humanoid reactive walking: Decoupled versus coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    This paper proposes a novel visual servoing approach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of model predictive control MPC to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists of, first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC-based approach allows to avoid a number of limitations that appears in decoupled methods. In particular, visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence.

  • Vision-guided motion primitives for humanoid reactive walking: Decoupled versus coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    International audienceThis paper proposes a novel visual servoing ap-proach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of Model Predictive Control (MPC) to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists in first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC based approach allows to avoid a number of limitations that appears in decoupled methods. In particular visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence

  • Vision-guided motion primitives for humanoid reactive walking: decoupled vs. coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    This paper proposes a novel visual servoing ap-proach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of Model Predictive Control (MPC) to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists in first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC based approach allows to avoid a number of limitations that appears in decoupled methods. In particular visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence.

  • Vision based control for Humanoid robots
    2011
    Co-Authors: Claire Dune, Olivier Stasse, Andrei Herdt, Pierre-brice Wieber, Eric Marchand, Eiichi Yoshida
    Abstract:

    This paper presents a visual servoing scheme to control humanoid dynamic walk. Whereas most of the existing approaches follow a perception-decision-action scheme, we hereby introduce a method that uses the on-line information given by an on-board camera. This close looped approach allows the system to react to changes in its environment and adapt to modelling error. Our approach is based on a new reactive pattern generator which modifies footsteps, center of mass and center of pressure trajectories at the control level for the center of mass to track a Reference Velocity. In this workshop, we present three ways of servoing dynamical humanoid walk : a naive one that compute a Reference Velocity using a visual servoing control law, a second one that takes into account the sway motion induced by the walk and an on going work on vision predictive control that directly introduces the visual error in the cost function of the pattern generator. The two first approaches have been validated on the HRP-2 robot. These close loop approaches give a more accurate positioning than the one obtained when executing a planned trajectory especially when rotational motion are involved.

  • Cancelling the sway motion of dynamic walking in visual servoing
    2010
    Co-Authors: Claire Dune, Olivier Stasse, Andrei Herdt, Pierre-brice Wieber, K. Yokoi, Eiichi Yoshida
    Abstract:

    This paper introduces a visual servoing scheme for humanoid walking. Though most of the existing approaches follow a perception-decision-action scheme, we close the loop so that the control is robust to model error. Our approach is based on a new reactive pattern generator which modifies, at the control level, the footsteps, the center of mass and the center of pressure trajectories for the center of mass to track a Reference Velocity. And, in this paper, the Reference Velocity is directly given by a visual servoing control law. Since, the HRP- 2 walk induces a sway motion that disturbs the regulation of the visual control law, we introduce a control law allowing convergence in the image space and taking into account this sway motion.

Olivier Stasse - One of the best experts on this subject based on the ideXlab platform.

  • Vision-guided motion primitives for humanoid reactive walking: Decoupled versus coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    This paper proposes a novel visual servoing approach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of model predictive control MPC to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists of, first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC-based approach allows to avoid a number of limitations that appears in decoupled methods. In particular, visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence.

  • Vision-guided motion primitives for humanoid reactive walking: Decoupled versus coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    International audienceThis paper proposes a novel visual servoing ap-proach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of Model Predictive Control (MPC) to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists in first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC based approach allows to avoid a number of limitations that appears in decoupled methods. In particular visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence

  • Vision-guided motion primitives for humanoid reactive walking: decoupled vs. coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    This paper proposes a novel visual servoing ap-proach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of Model Predictive Control (MPC) to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists in first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC based approach allows to avoid a number of limitations that appears in decoupled methods. In particular visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence.

  • Vision based control for Humanoid robots
    2011
    Co-Authors: Claire Dune, Olivier Stasse, Andrei Herdt, Pierre-brice Wieber, Eric Marchand, Eiichi Yoshida
    Abstract:

    This paper presents a visual servoing scheme to control humanoid dynamic walk. Whereas most of the existing approaches follow a perception-decision-action scheme, we hereby introduce a method that uses the on-line information given by an on-board camera. This close looped approach allows the system to react to changes in its environment and adapt to modelling error. Our approach is based on a new reactive pattern generator which modifies footsteps, center of mass and center of pressure trajectories at the control level for the center of mass to track a Reference Velocity. In this workshop, we present three ways of servoing dynamical humanoid walk : a naive one that compute a Reference Velocity using a visual servoing control law, a second one that takes into account the sway motion induced by the walk and an on going work on vision predictive control that directly introduces the visual error in the cost function of the pattern generator. The two first approaches have been validated on the HRP-2 robot. These close loop approaches give a more accurate positioning than the one obtained when executing a planned trajectory especially when rotational motion are involved.

  • Cancelling the sway motion of dynamic walking in visual servoing
    2010
    Co-Authors: Claire Dune, Olivier Stasse, Andrei Herdt, Pierre-brice Wieber, K. Yokoi, Eiichi Yoshida
    Abstract:

    This paper introduces a visual servoing scheme for humanoid walking. Though most of the existing approaches follow a perception-decision-action scheme, we close the loop so that the control is robust to model error. Our approach is based on a new reactive pattern generator which modifies, at the control level, the footsteps, the center of mass and the center of pressure trajectories for the center of mass to track a Reference Velocity. And, in this paper, the Reference Velocity is directly given by a visual servoing control law. Since, the HRP- 2 walk induces a sway motion that disturbs the regulation of the visual control law, we introduce a control law allowing convergence in the image space and taking into account this sway motion.

Mauricio Garcia - One of the best experts on this subject based on the ideXlab platform.

  • Vision-guided motion primitives for humanoid reactive walking: Decoupled versus coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    This paper proposes a novel visual servoing approach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of model predictive control MPC to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists of, first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC-based approach allows to avoid a number of limitations that appears in decoupled methods. In particular, visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence.

  • Vision-guided motion primitives for humanoid reactive walking: Decoupled versus coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    International audienceThis paper proposes a novel visual servoing ap-proach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of Model Predictive Control (MPC) to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists in first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC based approach allows to avoid a number of limitations that appears in decoupled methods. In particular visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence

  • Vision-guided motion primitives for humanoid reactive walking: decoupled vs. coupled approaches
    The International Journal of Robotics Research, 2014
    Co-Authors: Mauricio Garcia, Olivier Stasse, Jean-bernard Hayet, Claire Dune, Claudia Esteves, Jean-paul Laumond
    Abstract:

    This paper proposes a novel visual servoing ap-proach to control the dynamic walk of a humanoid robot. Online visual information is given by an on-board camera. It is used to drive the robot towards a specific goal. Our work is built upon a recent reactive pattern generator that make use of Model Predictive Control (MPC) to modify footsteps, center of mass and center of pressure trajectories to track a Reference Velocity. The contribution of the paper is to formulate the MPC problem considering visual feedback. We compare our approach with a scheme decoupling visual servoing and walking gait generation. Such a decoupled scheme consists in first, computing a Reference Velocity from visual servoing; then, the Reference Velocity is the input of the pattern generator. Our MPC based approach allows to avoid a number of limitations that appears in decoupled methods. In particular visual constraints can be introduced directly inside the locomotion controller, while camera motions do not have to be accounted for separately. Both approaches are compared numerically and validated in simulation. Our MPC method shows a faster convergence.

He Bai - One of the best experts on this subject based on the ideXlab platform.

  • Two-time-scale adaptive internal model designs for motion coordination
    Automatica, 2016
    Co-Authors: He Bai
    Abstract:

    We study a motion coordination problem where a group of agents is required to reach consensus while tracking a leader's sinusoidal Reference Velocity. We assume that the frequency of the Reference Velocity is available only to the leader. Building on a passivity-based control, we develop decentralized two-time-scale adaptive internal model control algorithms that estimate the unknown frequency information and achieve consensus of the group. We establish exponential stability of the algorithms using two-time-scale averaging theory. Simulation results with first order and second order agent dynamics illustrate the effectiveness of the proposed controls.

  • ACC - Adaptive motion coordination with an unknown Reference Velocity
    2015 American Control Conference (ACC), 2015
    Co-Authors: He Bai
    Abstract:

    We study a motion coordination problem where a group of agents is required to reach consensus while tracking a leader's sinusoidal Reference Velocity. We assume that the frequency of the Reference Velocity is available only to the leader. Building on an existing passivity-based internal model control design, we develop a decentralized two-time-scale adaptive control that estimates the unknown frequency information and achieves consensus of the group. We establish uniform asymptotic stability of the adaptive design using a two-time-scale averaging theory. Simulation results illustrate the effectiveness of the proposed control.

  • Adaptive Design for Reference Velocity Recovery: Parameterization Approach
    Cooperative Control Design, 2011
    Co-Authors: He Bai, Murat Arcak, John T. Wen
    Abstract:

    The designs in Sections 3.3 and 3.5 restrict the Reference Velocity v(t) to be constant or periodically time-varying. In this section, we present adaptive designs that are applicable to any time-varying, uniformly bounded and C1 Reference Velocity v(t) that can be parameterized.

  • Adaptive Design for Reference Velocity Recovery: Internal Model Approach
    Cooperative Control Design, 2011
    Co-Authors: He Bai, Murat Arcak, John T. Wen
    Abstract:

    The passivity-based design in Chapter 2 assumed that the Reference Velocity of the group is available to each agent and developed control laws that made use of this information. A more realistic situation is when a leader, say agent 1, in the group possesses this information. In this chapter, we exploit the design flexibility offered by the passivity-based framework and develop adaptive designs with which the other agents reconstruct Reference Velocity information.

  • Brief paper: Adaptive motion coordination: Using relative Velocity feedback to track a Reference Velocity
    Automatica, 2009
    Co-Authors: He Bai, Murat Arcak, John T. Wen
    Abstract:

    We study a coordination problem where the objective is to steer a group of agents to a formation that translates with a prescribed Reference Velocity. In Bai et al. [Bai, H., Arcak, M., & Wen, J. (2008). Adaptive design for Reference Velocity recovery in motion coordination. Systems and Control Letters, 57(8), 602-610.] we considered the situation where the Reference Velocity information is available only to a leader, and developed a decentralized adaptive design that uses relative position feedback. Although Bai et al. (please see above Reference) guaranteed the desired formation, it did not ensure tracking of the Reference Velocity with the exception of special cases. We now propose a new adaptive redesign that guarantees tracking of the Reference Velocity by incorporating relative Velocity feedback in addition to relative position feedback.