Online adaptation of reference trajectories for the control of walking systems

Wieber, Pierre-Brice; Chevallereau, Christine

doi:10.1016/j.robot.2006.04.007

Cited by 39 publications

(26 citation statements)

References 11 publications

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“…This restricts the motions that a walking system can realize, strongly limiting its capacity to follow a predefined motion in the presence of perturbations [22]. There is a strong interest therefore in being able to generate walking motions online, continuously adapting them to the current dynamics of the system.…”

Section: Introductionmentioning

confidence: 99%

Online Walking Motion Generation with Automatic Footstep Placement

et al. 2010

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The goal of this paper is to demonstrate the capacity of Model Predictive Control to generate stable walking motions without the use of predefined foot steps. Building up on well-known Model Predictive Control schemes for walking motion generation, we show that a minimal modification of these schemes allows designing an online walking motion generator which can track a given reference speed of the robot and decide automatically the foot step placement. Simulation results are proposed on the HRP-2 humanoid robot, showing a significant improvement over previous approaches.

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Section: Introductionmentioning

confidence: 99%

Online Walking Motion Generation with Automatic Footstep Placement

et al. 2010

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“…The online adaptation of the choice of the reference trajectory proposed in [6] for the control of a 40 kg walking robot allowed to compensate a perturbation of 750 N in the sagittal plane during 25 ms. This would be analogous to a mass M corresponding to 15% of the total mass of the robot hitting it as in figure 4: the scheme proposed here appears to perform much better.…”

Section: Discussionmentioning

confidence: 99%

“…Classical trajectory tracking control laws are structurally unable to deal with such strong constraints on the dynamics of a system, especially when having to face strong perturbations. They have been regularly completed therefore with higher-level adaptation schemes of the trajectories being tracked [2], [3], [4], [5], [6]. But all of these schemes are based on predefined sets of possible motions which may not be able to adapt to all the situations a humanoid robot may have to face.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong Perturbations

Wieber

2006

2006 6th IEEE-RAS International Conference on Humanoid Robots

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Abstract-A humanoid walking robot is a highly nonlinear dynamical system that relies strongly on contact forces between its feet and the ground in order to realize stable motions, but these contact forces are unfortunately severely limited. Model Predictive Control, also known as Receding Horizon Control, is a general control scheme specifically designed to deal with such contrained dynamical systems, with the potential ability to react efficiently to a wide range of situations. Apart from the question of computation time which needs to be taken care of carefully (these schemes can be highly computation intensive), the initial question of which optimal control problems should be considered to be solved online in order to lead to the desired walking movements is still unanswered. A key idea for answering to this problem can be found in the ZMP Preview Control scheme. After presenting here this scheme with a point of view slightly different from the original one, we focus on the problem of compensating strong perturbations of the dynamics of the robot and propose a new Linear Model Predictive Control scheme which is an improvement of the original ZMP Preview Control scheme.

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“…The viable region of a trajectory-based controller can be increased by using a library of multiple trajectories, producing a controller that performs well in the union of the tubes around each trajectory in the library [4] [5]. Models and prediction can be avoided entirely by doing direct policy search [6] [7], typically with parametric policies.…”

Section: A Related Workmentioning

confidence: 99%

Control of a walking biped using a combination of simple policies

Whitman

Atkeson

2009

2009 9th IEEE-RAS International Conference on Humanoid Robots

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Abstract-We present a decoupled controller for a simulated three-dimensional biped. To handle the high-dimensionality of the system, we break the dynamics down into multiple subsystems, which we control separately. For both the sagittal and coronal plane dynamics, we use dynamic programming to simultaneously optimize body motion, foot placement, and step timing for a two link inverted pendulum model. To use these simplified policies we map the full state to a simplified state, and then map the control action back onto the full system. The swing leg is controlled via continuously updated desired trajectories. These separate policies are then coordinated by the estimated time until touchdown, which is provided by the sagittal policy. By varying the lean angle or changing the sagittal policy we are able to contol the walking speed. We also evaluate the performance of our controller in terms of robustness to perturbations.

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Online adaptation of reference trajectories for the control of walking systems

Cited by 39 publications

References 11 publications

Online Walking Motion Generation with Automatic Footstep Placement

Online Walking Motion Generation with Automatic Footstep Placement

Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong Perturbations

Control of a walking biped using a combination of simple policies

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