Real-time Model Predictive Control for Versatile Dynamic Motions in Quadrupedal Robots

Ding, Yanran; Pandala, Abhishek; Park, Hae Won

doi:10.1109/icra.2019.8793669

Cited by 84 publications

(59 citation statements)

References 23 publications

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“…Model predictive control (MPC) can resolve this problem by addressing a long-time horizon optimal control. It anticipates the results of the robot's actions and finds an optimal control input for a longer time horizon, at the cost of higher computational complexity [21]- [24]. More recently, combinations of MPC-WBC have been proposed to take benefits of both methods [25], [26].…”

Section: A Quadrupedal Locomotion Controlmentioning

confidence: 99%

Animal Gaits on Quadrupedal Robots Using Motion Matching and Model-Based Control

Kang

Zimmermann

Coros

2021

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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In this paper, we explore the challenge of generating animal-like walking motions for legged robots. To this end, we propose a versatile and robust control pipeline that combines a state-of-the-art model-based controller with a datadriven technique that is commonly used in computer animation. We demonstrate the efficacy of our control framework on a variety of quadrupedal robots in simulation. We show, in particular, that our approach can automatically reproduce key characteristics of animal motions, including speed-specific gaits, unscripted footfall patterns for nonperiodic motions, and natural small variations in overall body movements.

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Section: A Quadrupedal Locomotion Controlmentioning

confidence: 99%

Animal Gaits on Quadrupedal Robots Using Motion Matching and Model-Based Control

Kang

Zimmermann

Coros

2021

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…These principles of variations along a reference trajectory are next applied to the reduced-order dynamics of the Mini Cheetah in order to complete the linearization. Using the variation formulae in (17) and (19), the approximate linear error s ∈ R 12 for the state of the reduced-order model of the quadruped (10) is given by…”

Section: Application To Mini Cheetah Dynamicsmentioning

confidence: 99%

“…To avoid non-convexity in the MPC formulation, other MPC strategies often make model simplifications to work with linear dynamic models [18], [19]. The linear dynamic model allows the OCP to be posed as a single convex optimization problem, which avoids the issue of local optima and allows for enforcement of inputs constraints.…”

Section: Introductionmentioning

confidence: 99%

Variational-Based Optimal Control of Underactuated Balancing for Dynamic Quadrupeds

Chignoli

Wensing

2020

IEEE Access

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This paper presents a control strategy for quadruped balancing that enables postural control in underactuated contact configurations (e.g., when standing on two point feet). Underactuated balancing has received considerable attention with prototype control models such as the cart pendulum or acrobot. Yet, when attempting to transition these solutions to balance in legged robots, technical challenges related to friction-limited contacts and the underlying manifold structure of the configuration space prevent straightforward application. This paper presents a new balance control framework that combines constrained optimal control strategies with recent variational-based linearization approaches to solve the balancing problem for a common simplified quadruped model. The controller is implemented as a convex quadratic program (QP) that uses an unconstrained optimal control solution to approximate a friction-constrained optimal policy. Unlike state-of-the-art QP-based balance controllers, the method is able to handle balance in underactuated regimes. Via comparison to model-predictive control strategies, the proposed formulation is highly compact, requiring less computation, while still showing the ability to handle extreme friction limitations. Simulation and hardware results with the MIT Mini Cheetah demonstrate the capabilities of the controller to exploit body angular momentum for disturbance recovery on two feet, and to recover from cases where the center of mass exits the support polygon. These results and the generality of the formulation suggest exploration for further application to bipeds and humanoids.

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“…Thanks to recent computational advances, Model Predictive Control (MPC) has shown real-time applicability on highdimensional systems [14], [15]. However, the performance of nominal MPC degrades in the presence of model uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Adaptive CLF-MPC With Application to Quadrupedal Robots

Minniti

Grandia

Farshidian

et al. 2022

IEEE Robot. Autom. Lett.

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Real-time Model Predictive Control for Versatile Dynamic Motions in Quadrupedal Robots

Cited by 84 publications

References 23 publications

Animal Gaits on Quadrupedal Robots Using Motion Matching and Model-Based Control

Animal Gaits on Quadrupedal Robots Using Motion Matching and Model-Based Control

Variational-Based Optimal Control of Underactuated Balancing for Dynamic Quadrupeds

Adaptive CLF-MPC With Application to Quadrupedal Robots

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