Modeling and Control of Legged Robots

Wieber, Pierre-Brice; Tedrake, Russ; Kuindersma, Scott

doi:10.1007/978-3-319-32552-1_48

Cited by 156 publications

(173 citation statements)

References 168 publications

(212 reference statements)

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“…In practice, we evaluated the integral of the norm of the joint torques (during one locomotion cycle) and we compared it with the norm of the joint torques related to inertial forces. For the range of walking speed of our locomotion experiments, [5,10,15,15] cm/s, we found that the inertial forces accounted only for [9.5,11.5,15, 22]% of the total joint torques. Therefore, since the influence of the trunk inertia tensor is minor, its identification is out of the scope of this work.…”

Section: Online Trunk Com Identificationmentioning

confidence: 80%

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Online payload identification for quadruped robots

Tournois

Focchi

Prete³

et al. 2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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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.

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Section: Online Trunk Com Identificationmentioning

confidence: 80%

“…In addition, most stability criteria in legged locomotion are heavily affected by model errors as they depend on the estimation of the robot CoM [10]. A common strategy to increase robustness against CoM uncertainties [11] is to ensure a reasonable stability margin inside the support polygon.…”

Section: Introductionmentioning

confidence: 99%

Online payload identification for quadruped robots

Tournois

Focchi

Prete³

et al. 2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…The unilateral nature of this interaction (feet can only push on the ground) limits the motion that a legged robot can realize and plays a crucial role in its stability. When walking on a flat ground, this corresponds to having the Center of Pressure (CoP) stay within the support polygon [25]. Model Predictive Control (MPC) is one of few suitable methods to handle such constraints [17], and has been used therefore extensively for the control of legged robots.…”

Section: Introductionmentioning

confidence: 99%

“…These sources of uncertainty can always be reduced with more precise (and more expensive) hardware or we can try to estimate them, but only up to a point: there always remains a certain amount of uncertainty. And as a result, there always remains a certain amount of tracking error when trying to follow a reference motion [5], [12], [9], [25], [15]. In order to satisfy all constraints in the presence of such tracking error, the usual approach is to introduce hand tuned safety margins [24].…”

Section: Introductionmentioning

confidence: 99%

Model predictive control of biped walking with bounded uncertainties

Villa

Wieber

2017

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)

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Abstract-A biped walking controller for humanoid robots has to handle together hard constraints, dynamic environments, and uncertainties. Model Predictive Control (MPC) is a suitable and widely used control method to handle the first two issues. Uncertainties on the robot imply a non-zero tracking error when trying to follow a reference motion. A standard solution for this issue is to use tighter constraints by introducing some hand tuned safety margins, for the reference motion generation to ensure that the actual robot motion will satisfy all constraints even in presence of the tracking error. In this article, we find bounds for the tracking error and we show how such safety margins can be precisely computed from the tracking error bounds. Also, a tracking control gain is proposed to reduce the restrictiveness introduced with the safety margins. MPC with these considerations ensure the correct operation of the biped robot under a given degree of uncertainties when it is implemented in open-loop. Nevertheless, the straightforward way to implement an MPC closed-loop scheme fails. We discuss the reasons for this failure and propose a robust closed-loop MPC scheme.

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“…Methods to make robots walk [1], run [2] and jump [3] exist and they are well understood [4]. However, such methods are usually specifically designed for a given task and robot morphology.…”

Section: Introductionmentioning

confidence: 99%

Hybrid direct collocation and control in the constraint-consistent subspace for dynamic legged robot locomotion

Pardo

Neunert

Winkler

et al. 2017

Robotics: Science and Systems XIII

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Abstract-In this paper, we present an algorithm for planning and control of legged robot locomotion. Given the desired contact sequence, this method generates gaits and dynamic motions for legged robots without resorting to simplified stability criteria. The method uses direct collocation for searching for solutions within the constraint-consistent subspace defined by the robot's contact configuration. For the differential equation constraints of the collocation algorithm, we use the so-called direct dynamics of a constrained multibody system. The dynamics of a legged robot is different for each contact configuration. Our method deals with such a hybrid nature, and it allows for velocity discontinuities when contacts are made. We introduce the projected impact dynamics constraint to enforce consistency during mode switching. We stabilize the plan using an inverse dynamics controller compatible with the optimal feed-forward control of the motion plan. As a whole, this approach reduces the complexity associated with specifying dynamic motions of a floating-base robot under the constant influence of contact forces. We apply this method on a hydraulically-actuated quadruped robot. We show two types of gaits (walking and trotting) as well as diverse jumping motions (forward, sideways, turning) on the real system. The results presented here are one of the few examples of an optimal control problem solved and satisfactorily transferred to a real torquecontrolled legged robot.

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Modeling and Control of Legged Robots

Cited by 156 publications

References 168 publications

Online payload identification for quadruped robots

Online payload identification for quadruped robots

Model predictive control of biped walking with bounded uncertainties

Hybrid direct collocation and control in the constraint-consistent subspace for dynamic legged robot locomotion

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