Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Control of biped locomotion inspired fromwalking in monkeys

Charles-Henry Houdemer

BiorobEcole polytechnique fédérale de Lausanne

LSROÉcole polytechnique fédérale de Lausanne

18 June 2010 / Final Presentation

Supervisors : Sarah Dégallier, Jesse Van den Kieboom, Solaiman Shokur, Auke Jan Ijspeert

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Outline

1 IntroductionInsights on BMIsPrevious workGoal of the projectChallengesLong term goals

2 ResultsWebots modelNumerical testsCPG modelResults

3 Future improvements

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Insights on BMIs

Three different forms :InvasivePartially-invasiveNon-invasive

Two types :Motor BMISensory BMI

Transform data either from or to the brain by predictingand interpreting correct behaviour

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Insights on BMIs

Three different forms :InvasivePartially-invasiveNon-invasive

Two types :Motor BMISensory BMI

Transform data either from or to the brain by predictingand interpreting correct behaviour

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Insights on BMIs

Three different forms :InvasivePartially-invasiveNon-invasive

Two types :Motor BMISensory BMI

Transform data either from or to the brain by predictingand interpreting correct behaviour

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Insights on BMIs

Three different forms :InvasivePartially-invasiveNon-invasive

Two types :Motor BMISensory BMI

Transform data either from or to the brain by predictingand interpreting correct behaviour

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Insights on BMIs

Three different forms :InvasivePartially-invasiveNon-invasive

Two types :Motor BMISensory BMI

Transform data either from or to the brain by predictingand interpreting correct behaviour

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Previous work

Fitzsimmons’ work on monkeys1 :Model try to predict the position of each jointQuality of predictions is good for one direction butdegrades for two directionsMust switch between two models for forward andbackward

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Experimental setup

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Achievements

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Goal of the project

Build a CPG with the data from Nicolelis Lab in DukeUniversityData consists in Cartesian positions of hip, knee andankle positions, speed of walking and indication if thefoot is on the groundReproduce the walking gait of a rhesus monkey withthis CPG recieving basic inputs from a BMIGeneralize it if possible to :

Different sessions;Different speeds;Different monkeys;Both directions.

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Goal of the project

Build a CPG with the data from Nicolelis Lab in DukeUniversityData consists in Cartesian positions of hip, knee andankle positions, speed of walking and indication if thefoot is on the groundReproduce the walking gait of a rhesus monkey withthis CPG recieving basic inputs from a BMIGeneralize it if possible to :

Different sessions;Different speeds;Different monkeys;Both directions.

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Goal of the project

Build a CPG with the data from Nicolelis Lab in DukeUniversityData consists in Cartesian positions of hip, knee andankle positions, speed of walking and indication if thefoot is on the groundReproduce the walking gait of a rhesus monkey withthis CPG recieving basic inputs from a BMIGeneralize it if possible to :

Different sessions;Different speeds;Different monkeys;Both directions.

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Goal of the project

Build a CPG with the data from Nicolelis Lab in DukeUniversityData consists in Cartesian positions of hip, knee andankle positions, speed of walking and indication if thefoot is on the groundReproduce the walking gait of a rhesus monkey withthis CPG recieving basic inputs from a BMIGeneralize it if possible to :

Different sessions;Different speeds;Different monkeys;Both directions.

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Challenges

Monkeys are not naturally bipedalMonkeys’ behaviour is not always predictable

Play with holding barMake feet slide on the groundVideoCauses variability in measurements

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Typical variations in the hip angles

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Long term goals

Allow paraplegics to regain the control of their legsAllow for more robust predictions

Less informations are neededLess neurons are neededMay lose more neurons before losing efficency

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Long term goals

Allow paraplegics to regain the control of their legsAllow for more robust predictions

Less informations are neededLess neurons are neededMay lose more neurons before losing efficency

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Long term goals

Allow paraplegics to regain the control of their legsAllow for more robust predictions

Less informations are neededLess neurons are neededMay lose more neurons before losing efficency

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Creation

Built from the webots human model of Jesse van denKieboom

Only hand size and total weight were knownSize and masse extrapolated with data from Hamada2

Main differences :Tail added;Head lighter than with normal division to reflect that amonkey head is lighter than a human one.

Uses a grannywalker to prevent it from falling on its side

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Monkey and human models

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Curves were normalized for testingCPGs can be easily scaled but not change shape

For each cycle :Amplitude was normalizedy = (y − y)/(ymax − ymin)Frequency was normalized by scaling each time intervalto a reference one

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Duty factor

Duty factorDecreases with speedRight leg different than left oneVariance lower with high speeds

Equation of the form (for one cycle) :stancetimetotaltime

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Duty factor

Duty factorDecreases with speedRight leg different than left oneVariance lower with high speeds

Equation of the form (for one cycle) :stancetimetotaltime

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Duty factor

Duty factorDecreases with speedRight leg different than left oneVariance lower with high speeds

Equation of the form (for one cycle) :stancetimetotaltime

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Duty factor

Duty factorDecreases with speedRight leg different than left oneVariance lower with high speeds

Equation of the form (for one cycle) :stancetimetotaltime

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Square errors

Square errorsSteady stepMean error lowVariance relatively low

Equation of the form (for one cycle) :∑ni=1(yiknown − yipredicted )2

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Square errors

Square errorsSteady stepMean error lowVariance relatively low

Equation of the form (for one cycle) :∑ni=1(yiknown − yipredicted )2

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Square errors

Square errorsSteady stepMean error lowVariance relatively low

Equation of the form (for one cycle) :∑ni=1(yiknown − yipredicted )2

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Square errors

Square errorsSteady stepMean error lowVariance relatively low

Equation of the form (for one cycle) :∑ni=1(yiknown − yipredicted )2

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Square errors of Nectarine - Hip

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Square errors of Nectarine - Knee

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Design of the CPGs

Data were in Cartesian form and contained thepositions of the knee, hip and ankleCPG is of the form :

xi = γi (fi (θi ) − xi ) + dfidθi

· θi + Ki

Phase coupling is of the form :p = sin(from.p ∗ 2 ∗ π − to.p ∗ 2 ∗ π − bias)

A cycle was arbitrarily chosen for the building of theCPG

AverageStarts and ends approximatively at the same height

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Design of the CPG

Joint angle cycle was cut in three parts for interpolationParts were interpolated with third degree polynomialsPolynomials were used with cpgstudioTesting on webots was done with the cpg file obtainedthrough cpgstudio and the libcpg, both from Jesse vanden KieboomThe necessary data for building a CPG for the ankleand adapting the foot were obtained by trackingpositions on a video with the help of KostasKarakasiliotis. The implementation of the CPG wasabandoned in order not to add more complexity to analready well performing model.

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

CPG output

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Real and interpolated curves - Hip

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Real and interpolated curves - Knee

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Visual tests

Can walk forward and backwardHandles different speeds

Limited by ground adherence

Video

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

Future improvements

Implement flexible feet for more efficient foot contactModify the polynomials to reduce the error ininterpolation further in order to obtain a interpolatedcurve even more close to a real one

Control ofbiped

locomotioninspired from

walking inmonkeys

Charles-HenryHoudemer

IntroductionInsights on BMIs

Previous work

Goal of the project

Challenges

Long term goals

ResultsWebots model

Numerical tests

CPG model

Results

Futureimprovements

References

References

1 Nathan A. Fitzsimmons, Mikhail A. Lebedev, Ian D. Peikon,andMiguel A. L. Nicolelis. Extracting kinematic parameters for monkeybipedal walking from cortical neuronal ensemble activity.

2 Yuzuru Hamada, Nontakorn Urasopon, Islamul Hadi, and SuchindaMalaivijitnond. Body Size and Proportions and Pelage Color ofFree-Ranging Macaca mulatta from a Zone of Hybridization inNortheastern Thailand.