of Biped Locomotion Yoonsang Lee 1 Kyungho Lee 2 Soon-Sun Kwon 3 - - PowerPoint PPT Presentation

Push-Recovery ry Stability

• f Biped Locomotion

Yoonsang Lee1 Kyungho Lee2 Soon-Sun Kwon3 Jiwon Jeong1 Carol O’Sullivan4 Moon Seok Park5 Jehee Lee2

1 Samsung Electronics Co., Ltd. 2 Seoul National University 3 Ajou University 4 Disney Research 5 Seoul National University Bundang Hospital

Two fundamental goals:

• Human-likeness (i.e., normal gait)
• Robustness against perturbation

Biped Controller Design

[Lee et al. 2010]

Normal Gait

• Gait pattern that humans normally adopt
• More energy efficient than other gaits
• Many questions still remain regarding stability

Questions |

| Gait it St Stabil ilit ity

• Under what conditions is human gait more stable?
• Is normal gait more stable than abnormal gait?

Questions |

| Bip iped Control

• How much are existing biped controllers human-

like?

• Are they as stable as human locomotion?
• Also influenced by the gait factors that affect humans?

Goal

Correlation between gait and stability

• which aspects of gaits affect balance-recovering capabilities
• how these factors affect to computer-simulated bipeds

Better understanding of existing biped controllers & how to improve controller design

• Standing postures stability
• Gait stability

[Bauby and Kuo 2000] [England and Granata 2007] [Bruijn et al. 2009]

• Our work: Recovery response for moderate push while walking

Background | Measurin

ing St Stabil ilit ity

[Rogers et al. 2001] [Brauer et al. 2001]

Background |

| Bip Biped Co Control

• Bipedal Locomotion
• Stability to external pushes
• Stomping gait controllers were better - affect of gait type?

[Wang et al. 2010] [Lee et al. 2010] [Lee et al. 2014] [Wang et al. 2010] [Yin et al. 2007] [Wang et al. 2010, 2012] [Geijtenbeek et al.2013] [Mordatch et al.2013] [Kwon and Hodgins 2010] [Coros et al. 2010] [de Lasa et al. 2010] [Yin et al. 2007] [da Silva et al. 2008] …

Side view Top view

• Stability measure : Lateral deviation from a line
• Experiments with human participants & simulated

biped

Design of f Experiments

Experiments wit ith Human Part rticipants

• 30 healthy participants ( 15 males / 15 females)
• Measure 31 variables:
• Level of crouch (0˚,20˚, 30˚, 60˚)
• Stride length
• Walking speed
• Timing, magnitude and direction of the push
• Height, weight, BMI, and leg lengths
• Angle of the feet at ground contact
• …

Collected Data fr from Experiments

Group 1

• The lateral displacement

peaked within one step

• Easily recovered balance

Group 2

• The lateral displacement

peaked within three steps

• Experienced difficulties

recovering balance

Collected Data fr from Experiments

• Multivariate, repeated, unbalanced, and clustered
• Outcome is a time series of complex articulated structures
• Measured twice on the same outcome
• Difficult to collect well-balanced data with so many variables
• Linear Mixed Model (LMM)
• General method for handling the between- and within-

subject variability in the repeated, unbalanced data.

• Model selection
• LMM with walking speed, push magnitude and timing

minimize AIC & BIC

Result |

| Overall ll Analy lysis is

• The gait detours less if (for both human & simulation)
• Level of crouch

It crouches mild

• Walking speed

Walks faster

• Magnitude of push

Push is weaker

• Timing of push

Push happens later

• Height, weight, BMI were irrelevant.

Simulation Experiments | Bip

iped Con

• ntroll

ller

• Data-driven biped controller [Lee et al 2010]
• Imitating reference gait

Simulation Experiments | Bip

iped Con

• ntroll

ller

• Feedback rules to maintain balance
• stance hip & ankle, swing hip & foot height
• Feedback parameter vector θ

Without feedback (θ = 0) With hand-tuned parameter θ

Simulation Experiments |

| Par arameter Optimization

• In the original work, θ was manually tuned for each motion
• In this work, θ is optimized to handle gait variations
• Evaluated with simulation of normal gait & 60° crouch gait
• 10s duration, with push in the middle
• Enough to deal with a wide variety of gait variations reliably

penalizes early falling favors better tracking penalizes excessive parameters

Simulation Experiments |

| Push sh Experiments

• Gait variations with random variables
• Level of crouch, stride length, walking speed, the

magnitude and timing of push

• Multivariate normal distributions
• Using motion displacement mapping and timewarping
• Fed into the optimized controller as reference

motion

• Simulated biped is pushed while walking

Result |

| Le Level l of f Cr Crouch

Group 2 Group 1

Result |

| Energy Exp xpendit iture of Sim Simula lated Walk lkin ing

• Cost of Transport :

required energy to move unit distance

• Humans : 1.05m/s ~ 1.4

m/s

• Normal gait simulation:

1 m/s

• Crouch 30 simulation :

0.76 m/s

Result |

| St Stri ride Length & St Stri ride Frequency

• Additional analysis - the gait detours less if
• Stride Length

Shorter stride length

• Stride Frequency

Higher frequency

• Opposite to the results of previous studies
• [Bauby and Kuo 2000; Bruijn et al. 2009] [England and Granata 2007]
• Reason - Different stability estimates
• Prevs’ - Kinematic variation (Lyapunov exponents)
• Ours - Resilience against impulsive perturbation

Discussion |

| Su Summary ry

• Significant factors affecting push-recovery response
• Level of crouch, walking speed, push force and push

timing

• Simulated biped is affect by same factors of human
• Quantitatively, human participants performed better

than simulation.

Discussion | Im

Impli licatio ion

• How much are existing biped controllers human-

like?

• Existing biped controllers behave quite similar to

humans qualitatively

Discussion | Im

Impli licatio ion

• About evaluating robustness of biped controllers
• Normalization for push-recovery test of biped

controllers

Acknowledgements

• Thanks to
• All members of SNU Movement Research Laboratory
• Seung Yeol Lee and Mi Seon Yoo from Seoul National

University Bundang Hospital

• Funding
• National Research Foundation of Korea (NRF) No.2011-

0018340 , No. 2007-0056094.

Push-Recovery Stability of f Bip iped Lo Locomotion

Yoonsang Lee1 Kyungho Lee2 Soon-Sun Kwon3 Jiwon Jeong1 Carol O’Sullivan4 Moon Seok Park5 Jehee Lee2

1Samsung Electronics Co., Ltd. 2 Seoul National University 3Ajou University 4Disney Research 5Seoul National University Bundang Hospital