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Head and leg adjustments help insects and legged robots traverse cluttered, large obstacles Department of Mechanical Engineering, Johns Hopkins University [email protected] https://li.me.jhu.edu Wang, Othayoth, Li, J. Exp. Biol., in prep. 1. Background & Motivation Animals integrate active sensory feedback and passive mechanical feedback to control locomotion Potential energy landscape Physical interaction (energy landscape) plays a major role during obstacle traversal Model system Locomotor transition pathways Transition barrier Othayoth et al. (in press), PNAS Dickinson et al. (2000), Science Saddle Awareness of landscape helps find a lower barrier Hypothesis: Cockroaches actively adjust body and appendages to overcome barrier and make transition 2. Experimental Observations Leg sprawl Head Bending Pushing Leg Height Supporting Leg Height 0 5 10 15 0 5 10 15 0 50 100 Leg sprawl angle (⁰) s.d. of head flexion (⁰) Leg height difference (mm) Difference *** *** *** *** Frequent head flexion Leg sprawl Differential leg use Run Push Roll Beam obstacle traversal can be divided into three phases Cockroaches actively adjust their head and legs to make locomotor transition Beam obstacle layer Cameras (100 fps) 3-D kinematics tracking setup Reduces roll stability Generates roll torque Sense terrain (?) Run Push Roll 0.30s 0.43s 1.06s 1.29s 1.97s 3.13s 3.44s Tags Beads Beads N = 8 animals, n = 64 trials P < 0.05 ANOVA P < 0.05 ANOVA P < 0.05 ANOVA Run Push Roll Run Push Roll Pitch Saddle Body roll (°) ` Body pitch (°) ` >0.54 Energy (mJ) 50 -50 Roll -50 -50 0 0.4 0.52 0.46 2 0 3. Energy Landscape Modeling Energy landscape approach to understand physics of locomotor transitions Proper head adjustment reduces energy barrier on landscape Body pitch (º) −80 −40 0 40 −70 0 70 Body roll (º) 0 25 0 50 Start 1 Start Transition barriers Roll Start 1 Roll Pitch Pitch 3 Energy (mJ) iii ii i Beams Start Pitch Pitch Start Start Roll Vertical vibration 3 −80º 0 40 −70 0 70 3 3 1 Start i ii iii iii’ 17 7 Energy (mJ) 11 8 Energy (mJ) 0 20 2 −80 −40 0 40 −70 0 70 Barrier without head adjustment Pitch Roll Saddle Energy barrier comparison Othayoth et al. (in press), PNAS 0 300 600 −40 −20 0 20 40 Traversal barrier (µJ) x (mm) Roll more favorable K = 11.44 mN·m/rad Roll Pitch Body roll (º) −90 0 90 90 0 −90 Body pitch (º) Potential energy (µJ) 2.5 ×104 2 1.5 1 0.5 With head bending (measured head angle) Representative barrier profile Head adjustment lowers barrier 3-D reconstruction Pitch Saddle Body roll (°) ` Body pitch (°) ` >0.54 Energy (mJ) 50 -50 Roll -50 -50 0 0.4 0.52 0.46 2 0 Without head bending (constant head angle) Body roll (°) 0 20 40 60 80 Barrier with head adjustment Energy (mJ) 0.38 0.5 0.4 0.42 0.44 0.46 0.48 0 0.5 1 1.5 2 2.5 Time (s) 0 0.1 0.2 0.3 0.4 No head bending With head bending Barrier energy (mJ) Start rolling Roll to max Time (s) 0 0.5 1 1.5 2 2.5 0 0.1 0.2 0.3 0.4 0 10 20 30 40 50 60 Trial NO. -0.08 -0.06 -0.04 -0.02 0 0.02 Barrier is smaller with head bending than without (mean change < 0) (P < 0.05, ANOVA) 0.02 0 -0.02 -0.04 -0.06 -0.08 Change in energy barrier (mJ) 0 10 20 30 40 50 60 Trial No. 4. Robophysical Model & Future Work Next steps Beams Retract Left Leg Extend Right Leg Head bending Sprawl inward Gap = 57% Body Width Initial Pitch = 45° Legged robot to systematically control and vary active adjustment of head and legs Head flexion Leg sprawl Differential leg use Legged robot Preliminary result: all the three adjustments help the robot roll into the gap Low cost 3-axis force sensor (designed by J. Krakauer’s group) Y Z X Embedded sensors at the neck Robot with force sensors Force measurements to understand: Relationship between contact forces and potential energy landscape (slope?) Transitions on landscape emerging from local force sensing Acknowledgements: Yuanfeng Han and Qiyuan Fu for help with imaging setup; Yuanfeng Han, Qiyuan Fu, Qihan Xuan and Xiao Yu for discussion; Xiao Yu for help with animal care. 5 trials 5 trials 5 trials 11 Yaqing Wang, Ratan Othayoth, Chen Li

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Page 1: +HDG DQG OHJ DGMXVWPHQWV KHOS LQVHFWV DQG …posa/DynamicWalking2020/678-1004-1-RVP.pdf*ds %rg\ :lgwk,qlwldo 3lwfk /hjjhg urerw wr v\vwhpdwlfdoo\ frqwuro dqg ydu\ dfwlyh dgmxvwphqw

Head and leg adjustments help insects and legged robots traverse cluttered, large obstacles

Department of Mechanical Engineering, Johns Hopkins University [email protected] https://li.me.jhu.edu

Wang, Othayoth, Li, J. Exp. Biol., in prep.

1. Background & Motivation

Animals integrate active sensory feedback and passive mechanical feedback to control locomotion

Potential energy landscape

Physical interaction (energy landscape) plays a major role during obstacle traversal

Model system Locomotor transition pathways

Transition barrier

Othayoth et al. (in press), PNAS

Dickinson et al. (2000), Science

Saddle

Awareness of landscapehelps find a lower barrier

Hypothesis: Cockroaches actively adjust body and appendages to overcome barrier and make transition

2. Experimental Observations

Leg sprawl

Head Bending

Pushing Leg Height

Supporting Leg Height

0

5

10

15

0

5

10

15

0

50

100

Leg sprawl angle (⁰) s.d. of head flexion (⁰)Leg height difference (mm)

Difference

*** *** ******

Frequent head flexionLeg sprawl Differential leg use

Run Push Roll

Beam obstacle traversal can be divided into three phases

Cockroaches actively adjust their head and legs to make locomotor transition

Beam obstacle layer

Cameras(100 fps)

3-D kinematics tracking setup

Reduces roll stability Generates roll torque Sense terrain (?)

Run Push Roll

0.30s 0.43s 1.06s 1.29s 1.97s 3.13s 3.44s

Tags

Beads

Beads

N = 8 animals, n = 64 trials

P < 0.05 ANOVA

P < 0.05 ANOVA

P < 0.05 ANOVA

Run Push RollRun Push Roll

Pitch

Saddle

Body roll (°)

`Body pitch (°)

`

>0.54

Energy(mJ)

50

-50

Roll

-50

-50

0

0.4

0.52

0.462

0

3. Energy Landscape ModelingEnergy landscape approach to understand physics of locomotor transitions

Proper head adjustment reduces energy barrier on landscape

Body pitch (º)

−80

−40

0

40−70

0

70

Body roll (º)

0

25

0

50Start

1

Start

Transition barriers

Roll

Start

1

Roll

Pitch Pitch

3

Energy (mJ)

iiiiii

Beams

Start

Pitch

Pitch

Start Start

Roll

Vertical vibration

3−80º

0

40−70

0

70

3

3

1

Start

i ii iii iii’

17

7

Energy (mJ)

11

8

Energy (mJ)

0

20

2

−80

−40

0

40−70

0

70

Barrier without head adjustment

Pitch

Roll

Saddle

Energy barrier comparison

Othayoth et al. (in press), PNAS

0

300

600

−40 −20 0 20 40

Traversalbarrier

(µJ)

x (mm)

Roll more favorable

K = 11.44 mN·m/rad

− Roll− Pitch

Body roll (º)

−90

0

9090

0 −90

Body pitch (º)

Potential energy (µJ)2.5

×104

2

1.5

1

0.5

With head bending(measured head angle)

Representative barrier profileHead adjustment lowers barrier

3-D reconstruction

Pitch

Saddle

Body roll (°)

`Body pitch (°)

`

>0.54

Energy(mJ)

50

-50

Roll

-50

-50

0

0.4

0.52

0.462

0

Without head bending(constant head angle)

Body roll (°)0 20 40 60 80

Barrier with head adjustment

Energy(mJ)

0.38

0.5

0.4

0.42

0.44

0.46

0.48

0 0.5 1 1.5 2 2.5Time (s)

0

0.1

0.2

0.3

0.4

No head bendingWith head bending

Barrier energy(mJ)

Start rolling Roll to max

Time (s)0 0.5 1 1.5 2 2.5

0

0.1

0.2

0.3

0.4

0 10 20 30 40 50 60

Trial NO.

-0.08

-0.06

-0.04

-0.02

0

0.02 Barrier is smaller with head bending than without

(mean change < 0)

(P < 0.05, ANOVA)

0.02

0

-0.02

-0.04

-0.06

-0.08

Change in energy barrier(mJ)

0 10 20 30 40 50 60

Trial No.

4. Robophysical Model & Future Work

Next steps

Beams

Retract Left Leg

Extend Right Leg

Head bending

Sprawlinward

Gap = 57% Body WidthInitial Pitch = 45°

Legged robot to systematically control and vary active adjustment of head and legsHead flexionLeg sprawl Differential leg useLegged robot

Preliminary result: all the three adjustments help the robot roll into the gap

Low cost 3-axis force sensor(designed by J. Krakauer’s group)

Y

Z

X

Embedded sensors at the neckRobot with force sensors

Force measurements to understand:• Relationship between contact forces and

potential energy landscape (slope?)• Transitions on landscape emerging from local

force sensing

Acknowledgements:Yuanfeng Han and Qiyuan Fu for help with imaging setup;Yuanfeng Han, Qiyuan Fu, QihanXuan and Xiao Yu for discussion;Xiao Yu for help with animal care.

5 trials5 trials5 trials

11

Yaqing Wang, Ratan Othayoth, Chen Li