Unified Modeling and Control of Walking and Running on the Spring-Loaded Inverted Pendulum

Shahbazi, Mohammad; Babuška, Robert; Lopes, Gabriel

doi:10.1109/tro.2016.2593483

Cited by 52 publications

(25 citation statements)

References 54 publications

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“…This makes it possible to find a solution to the problem of stabilizing the mobile structure in dynamics, by adding internal degrees of freedom. It is proposed to assign the stabilization tasks to a system of two flywheels operating as an ordinary pendulum with a flywheel [13], [14], but in contrast to these studies, it is proposed to combine the mass centers of two flywheels at one point and obtain a more compact design (see Fig. 6).…”

Section: Self-stabilization Of the Platformmentioning

confidence: 99%

Design and Control of Self-Stabilizing Angular Robotics Anywalker

Ryadchikov¹,

Sechenev²,

Sinitsa³

et al. 2017

ijacsa

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Abstract-Walking robots are designed to overcome obstacles when moving. The walking robot AnyWallker is developed, in the design of which the task of self-stabilization of the center of the mass is solved; a special type of chassis is developed, providing movement on high cross-country capability. The paper presents the results of designing and controlling the robot, the architecture of the software complex provides management and mastification of the hardware platform. AnyWalker is actually a chassis which can be used to build robots for many different purposes, such as surveying complex environment, industrial operations, and work in hazardous environment.

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Section: Self-stabilization Of the Platformmentioning

confidence: 99%

Design and Control of Self-Stabilizing Angular Robotics Anywalker

Ryadchikov¹,

Sechenev²,

Sinitsa³

et al. 2017

ijacsa

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“…We prove that our algorithm returns safe policies that have non-decreasing performance. Finally, we demonstrate the effectiveness of our approach on the discretized Spring Loaded Inverted Pendulum (SLIP) [21].…”

Section: Introductionmentioning

confidence: 99%

Iterative Model Predictive Control for Piecewise Systems

Rosolia

Ames

2022

IEEE Control Syst. Lett.

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In this paper, we present an iterative Model Predictive Control (MPC) design for piecewise nonlinear systems. We consider finite time control tasks where the goal of the controller is to steer the system from a starting configuration to a goal state while minimizing a cost function. First, we present an algorithm that leverages a feasible trajectory that completes the task to construct a control policy which guarantees that state and input constraints are recursively satisfied and that the closed-loop system reaches the goal state in finite time. Utilizing this construction, we present a policy iteration scheme that iteratively generates safe trajectories which have nondecreasing performance. Finally, we test the proposed strategy on a discretized Spring Loaded Inverted Pendulum (SLIP) model with massless legs. We show that our methodology is robust to changes in initial conditions and disturbances acting on the system. Furthermore, we demonstrate the effectiveness of our policy iteration algorithm in a minimum time control task.

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“…Consequently, a twostep iteration with high accuracy is provided for predicting the apex state of the SLIP system. Shahbazi et al [12] extended the approach from a single-leg configuration to a bipedal case. An analytical approximate representation for double-stance walking is derived and then used to construct an apex return map (ARM) without relying on numerical integration.…”

Section: Introductionmentioning

confidence: 99%

Sagittal SLIP-anchored task space control for a monopode robot traversing irregular terrain

Gao

Ding

et al. 2020

Front. Mech. Eng.

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As a well-explored template that captures the essential dynamical behaviors of legged locomotion on sagittal plane, the spring-loaded inverted pendulum (SLIP) model has been extensively employed in both biomechanical study and robotics research. Aiming at fully leveraging the merits of the SLIP model to generate the adaptive trajectories of the center of mass (CoM) with maneuverability, this study presents a novel two-layered sagittal SLIP-anchored (SSA) task space control for a monopode robot to deal with terrain irregularity. This work begins with an analytical investigation of sagittal SLIP dynamics by deriving an approximate solution with satisfactory apex prediction accuracy, and a two-layered SSA task space controller is subsequently developed for the monopode robot. The higher layer employs an analytical approximate representation of the sagittal SLIP model to form a deadbeat controller, which generates an adaptive reference trajectory for the CoM. The lower layer enforces the monopode robot to reproduce a generated CoM movement by using a task space controller to transfer the reference CoM commands into joint torques of the multi-degree of freedom monopode robot. Consequently, an adaptive hopping behavior is exhibited by the robot when traversing irregular terrain. Simulation results have demonstrated the effectiveness of the proposed method.

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Unified Modeling and Control of Walking and Running on the Spring-Loaded Inverted Pendulum

Cited by 52 publications

References 54 publications

Design and Control of Self-Stabilizing Angular Robotics Anywalker

Design and Control of Self-Stabilizing Angular Robotics Anywalker

Iterative Model Predictive Control for Piecewise Systems

Sagittal SLIP-anchored task space control for a monopode robot traversing irregular terrain

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