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Research Papers

Selective-Compliance-Based Lagrange Model and Multilevel Noncollocated Feedback Control of a Humanoid Robot

[+] Author and Article Information
Emmanouil Spyrakos-Papastavridis

Dyson School of Design Engineering,
Imperial College London,
South Kensington Campus,
London SW7 2AZ, UK
e-mail: e.spyrakos-papastavridis@imperial.ac.uk

Jian S. Dai

Centre for Robotics Research,
King's College London,
Strand, London WC2R 2 LS, UK
e-mail: jian.dai@kcl.ac.uk

Peter R. N. Childs

Dyson School of Design Engineering,
Imperial College London,
South Kensington Campus,
London SW7 2AZ, UK
e-mail: p.childs@imperial.ac.uk

Nikos G. Tsagarakis

Department of Advanced Robotics,
Istituto Italiano di Tecnologia,
via Morego, 30,
Genova 16163, Italy
e-mail: nikos.tsagarakis@iit.it

1Corresponding author.

Contributed by the Mechanisms and Robotics Committee of ASME for publication in the JOURNAL OF MECHANISMS AND ROBOTICS. Manuscript received May 7, 2017; final manuscript received February 3, 2018; published online April 5, 2018. Assoc. Editor: Andreas Mueller.

J. Mechanisms Robotics 10(3), 031009 (Apr 05, 2018) (13 pages) Paper No: JMR-17-1137; doi: 10.1115/1.4039394 History: Received May 07, 2017; Revised February 03, 2018

This paper presents unified control schemes for compliant humanoid robots that are aimed at ensuring successful execution of both balancing tasks and walking trajectories for this class of bipeds, given the complexity of under-actuation. A set of controllers corresponding to the single-support (SS) and double-support (DS) walking phases has been designed based on the flexible sagittal joint dynamics of the system, accounting for both the motor and link states. The first controller uses partial state feedback (proportional–derivative–derivative (PDD)), whereas the second considers the full state of the robot (proportional–proportional–derivative–derivative (PPDD)), while both are mathematically proven to stabilize the closed-loop systems for regulation and trajectory tracking tasks. It is demonstrated mathematically that the PDD controller possesses better stability properties than the PPDD scheme for regulation tasks, even though the latter has the advantage of allowing for its associated gain-set to be generated by means of standard techniques, such as linear quadratic regulator (LQR) control. A switching condition relating the center-of-pressure (CoP) to the energy functions corresponding to the DS and SS models has also been established. The theoretical results are corroborated by means of balancing and walking experiments using the COmpliant huMANoid (COMAN), while a practical comparison between the designed controller and a classical PD controller for compliant robots has also been performed. Overall, and a key conclusion of this paper, the PPDD scheme has produced a significantly improved trajectory tracking performance, with 9%, 15%, and 20% lower joint space error for the hip, knee, and ankle, respectively.

Copyright © 2018 by ASME
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Figures

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Fig. 1

LSS (left), DS (center) and RSS (right) models, and picture of COMAN's legs (rightmost)

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Fig. 3

Actual joint responses (0.3 rad step)

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Fig. 2

Simulated joint responses (0.3 rad step)

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Fig. 4

Support polygon shape corresponding to DS stance

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Fig. 7

Walking strategy control loop block diagram including the FSM that modulates the feedforward and feedback terms

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Fig. 8

Walking trajectory tracking in simulation

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Fig. 9

Ankle, knee, and hip joint tracking

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Fig. 10

Cartesian X and Y CoM positions during walking

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Fig. 11

Right-foot GRFs during walking

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Fig. 12

Ankle, knee, and hip control voltages during walking

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Fig. 5

CoP when robot subjected to a single (above) and multiple (below) disturbance/s

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Fig. 6

Walking controller FSM

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Fig. 13

Y-CoM positions during walking (controllers A, B, C)

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Fig. 14

Absolute average X-CoM errors during walking

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Fig. 15

Ankle, knee, and hip joint tracking during walking when using controllers A, B, and C

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