natural machine motion initiativemech.vub.ac.be/iroswsactuators/workshop_iros14.pdfnikos tsagarakis,...

Natural Machine Motion

Natural Machine Motion Initiative:

A Proposal Manolo Garabini, Giorgio Grioli, Manuel Catalano, Lorenzo Malagia

Yong Tae Giovanni Kim, Antonio Bicchi

Nikos Tsagarakis, Alin Albu-Schaeffer, Bram Vanderborght, Stefano Stramigioli, Etienne Burdet, Sami Haddadin, Alessandro De Luca, …

Istituto Italiano di Tecnologia

University of Pisa Centro di Ricerca “E. Piaggio”

• cooperative manipulation tasks

• domestic applications (domotics) • entertainment

• assistance

• rehabilitation

SARCOS

NASA-JPL

The Lokomat by Hocoma

Robots and Humans

UTAH

• teleoperation

• human augmentation

• haptic exoskeletons

• mixed environments

Berkeley

HAL

Tsukuba

Robots and Humans

Max Speed: 44.7 km/h Average Speed: 20.5 km/h

Highest Standing Jump: 1.62 m Deepest Dive: 53.9 m

On August 17th 2014 Daniele Meucci

won the European Athletics Championship

marathon in 2:11:08

(Daniele is a Ph.D. student in Robotics in Pisa)

How will robots look like in 10 years?

like their stiff and heavy ancestors… …or more like us?

Machine Intelligence

• Yesterday: Puma – Motorola 68K – 8 MHz – 160 Kflops

• Today: smartphones – Snapdragon S4 – 1.5 GHz – 6.4 Gflops = 40,000 X 160 Kflops

Machine Motion

• 1960’s robotics – Unimate Puma – Servomotors

• 2010’s robotics – Servomotors

The problem

How to make robots that are – soft yet strong – simple yet dextrous – intelligent yet practical

good news

Labs are a-changing…

Enabling Technologies

• Additive Manufacturing - Stereolithography (SLA) - Laminated Object Manufacturing (LOM™) - Ink Jet (PolyJet 3D Printing) - Selective Laser Sintering (SLS®) - Fused Deposition Modeling (FDM)

• New OS embedded uControllers (e.g. Arduino)

• New Sensors (e.g. magnetic encoders)

• New HW-in-the-loop tools

• New OS SW & MW (e.g. toolboxes, ROS, Yarp)

In the human body, each joint is actuated by - at least - two muscles

Enabling Science - I

Co-contraction of muscular groups allows for both SOFT and STRONG operations of the arm

Equilibrium-Point Hypothesis

[Latash, Motor Synergies and the Equilibrium-Point Hypothesis, Motor Control. Jul 2010; 14(3): 294–322]

According to the EP hypothesis, central control signals change the threshold of activation of alpha-motoneurons to afferent signals related to muscle length (threshold of the tonic stretch reflex, λ) For each λ (given an external load), there is an instantaneous EP – a combination of muscle length and force that would have been observed if the control process stopped and the system were given time to reach an equilibrium state Control of a simple joint with one kinematic degree of freedom may be viewed as resulting from specifying the control variables for the agonist and antagonist muscles

Natural Muscles: Mechanical Characteristics

[P. L. Gribble, D. J. Ostry, V. Sanguineti, and R. Laboissière, “Are complex control signals required for human arm movement?” Journal of Neurophysiology ]

Muscle Force

Muscle Activation

Muscle Length

Threshold Length

Reflex Delay

Parameter relating to fore-generating capability of the muscle

Form parameter

Antagonist Muscle System Model

[P. L. Gribble, D. J. Ostry, V. Sanguineti, and R. Laboissière, “Are complex control signals required for human arm movement?” Journal of Neurophysiology ]

External Load

Instantaneous Lever Arm

Equilibrium of a system composed of a couple of muscles acting on the same joint (e.g. elbow)

Assuming that R is constant and ρ and δ are the same for both muscles

is the forearm angular position w.r.t. the arm

Antagonist Muscle System Model

Neglecting the reflex delay and considering

the equilibrium position (with no external load) of the joint results from the equation

The equilibrium joint position is proportional to the semi-sum of the threshold lengths of the muscles

Reciprocal

Command

Muscle Model: Joint Stiffness

The stiffness at the equilibrium position (with no external load) can be evaluated by computing the derivative of the external torque w.r.t. the link position

The stiffness around the equilibrium position depends on the semi-difference of the threshold lengths of the muscles

Coactivation

Command

Evolution of actuation • Rigid actuation (e.g.: servomotors)

• Series Elastic Actuation • Variable Stiffness and

Variable Impedance Actuation

VSA, or muscles for robots

• From Position Control

• To Torque Control

• to Reference Point

AND Stiffness Control

Variable Stiffness Actuators @ Pisa

VSA I: 2003

VSA II: 2008

VSA HD: 2010

TODAY:

VSA-cubes

Soft Arm: 2000

Agonist-Antagonist VSA

VSA Antagonist Model: Nonlinear springs

Mechanical characteristic of the nonlinear springs

Where α, β, and η are the parameters that determine the mechanical characteristic of the spring; θm,I are positions of the motors and q is the link position

VSA Antagonist Model: Equilibrium Position

Considering zero velocity and no external load

the reference position of the joint is

The equilibrium joint position is proportional to the semi-sum of the motor positions

Position Reference

VSA Antagonist Model: Stiffness

The stiffness at the equilibrium position (with no external load) can be evaluated by computing the derivative of the external torque w.r.t. the link position

The stiffness around the equilibrium position depends on the semi-difference of the motor positions

Stiffness Preset

Natural and Robot Muscles

Muscle VSA A-A Relationship

Reciprocal Command (Reference) Coactivation Command

(Stiffness Preset) Stiffness

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5.7 From V SA -Cube t o B iologic M uscles

where k =θm,2 − θm,1

2.

In [140] an experimental device implement ing an antagonist ic VSAwith two exponent ial springs act ing on the same joint is used. Theexponent ial force-length characterist ic of each spring is obtained bysuitable designing the geometric profile where a linear spring slides(see Fig. 5.17).

Figure 5.17: The experimental setup consists of an antagonist VSAsystem with exponent ial springs, realised using a linear spring forcedto move on a suitable cam profile. Force sensors (strain gauges) aremounted on the tendons connect ing the springs to the link. Posit ionsensors (encoders) aremounted on the link and on two tendon pulleyscoupled with the input levers

The VSA-CubeBot described in [A4] has a completely differentdesign, even if based on the same principle. However, Fig. 5.18 showsthree different force-length characterist ics obtained by experimenta-t ions and their approximations (black line) given by (5.11), sett ing allparameters therein.

Concluding, for both musclesand agonist ic-antagonist ic VSAs, the

249

V SA -CUBE: Design of a Servo V SA

where α, β and η are parameters which determine the shape of theforce-length characterist ic and θm,i is the posit ion of the motor act ingon the link throughout the nonlinear spring.

The equilibrium posit ion of this type of VSA is such that

τ + τm,1 + τm,2 = 0 (5.12)

where τ represents the external load (see figure 5.16). τ1 and τ2 arethe torques that each motor applies to the link, given by

τ1 = αeβ(q− θm ,1 ) − µτ2 = − αeβ(− q+ θm ,2 ) + µ .

(5.13)

Figure 5.16: Scheme of a VSA with agonist and antagonist configu-rat ion.

The equilibrium posit ion q̄ of the VSA can be determined by im-posing τ = 0 and q̇ = 0 in (5.12), obtaining

0 = τm,1 + τm,2 = αeβ(q̄− θm ,1 ) − αeβ(− q̄+ θm ,2 ) (5.14)

which implies

q̄ =θm,1 + θm,2

2= qℓ (5.15)

The st iffness σ can be obtained as a funct ion of θm,1 and θm,2by determining the derivat ive of the external torque w.r.t . the linkposit ion q and evaluat ing it in q̄, i.e.

σ =∂τ∂q

q= q̄

= 2αβeβk , (5.16)

248

Fig. 1. Agonist and antagonist muscles acting on the elbow joint in the human arm.

(a) l 1 = 1 and l 2 = 5 or, simi-

larly, r = 3 and c = 2.

(b) l 1 = 2 and l 2 = 6, hence

changing joint position. Indeed,

r = 4 and c = 2.

(c) l 1 = 2 and l 2 = 4, hence

changing joint stiffness. Indeed,

r = 3 and c = 1.

Fig. 2. Force–length characteristics.

hence obtaining

q̄ =l 1 + l 2

2R=

rR

, (6)

where r := l 1+ l 22 .

The stiffness s can be evaluated in the equilibrium position as a function of l 1 and l 2 by

computing the derivative of the external torque w.r.t. the link position:

s =∂t∂q

q= q̄

= 2r dR2edc , (7)

where c :=l 1 − l 2

2.

Natural Muscles - Experimental External Load – Link Position Characteristics of elbow flexors and extensors measured through unloading the arm

[Reza Shadmehr and Michael A. Arbib, A mathematical analysis of the force-stiffness characteristics of muscles in control of a single joint system, Biological Cybernetics, 1992], redrawn from Feldman 1980.

VSA Cube - Experimental data

External Load – Link Position Characteristics of the VSAcube for different stiffness presets V SA -CU BE: Design of a Servo V SA

−0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8−1.5

−1

−0.5

0

0.5

1

1.5

qL [rad]

t L [N

m]

(a) Case 1.

−0.4 −0.3 −0.2 −0.1 0 0.1 0.2 0.3 0.4−1.5

−1

−0.5

0

0.5

1

1.5

qL [rad]

t L [N

m]

(b) Case 2.

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6−1.5

−1

−0.5

0

0.5

1

1.5

qL [rad]

t L [N

m]

(c) Case 3.

Figure 5.18: Force–length characterist ics.

st iffness σ can be described by a funct ion of type σ = AeγS (seeTable 5.2). Moreover, the equilibrium posit ion is q̄ = λ1+ λ22R(t) =

rR(t) for

muscles and q̄ = θm ,1+ θm ,22 = qℓ for VSAs.

St iffness model: σ = Aeγ S

Parameters Muscle VSA

A 2ρδR2(t) 2αβ

γ δ β

S c = λ2− λ12R(t) k =θm ,2− θm ,1

2

Table 5.2: Muscle force model and agonist ic-antagonist ic VSA model.

The role of λ i in the EP-H has hence a robot ic counterpart that,in our framework, is represented by motor posit ions θm,i .

250

τ Ext

erna

l Lo

ad

q Link Position

V SA -CU BE: Design of a Servo V SA

−0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8−1.5

−1

−0.5

0

0.5

1

1.5

qL [rad]

t L [N

m]

(a) Case 1.

−0.4 −0.3 −0.2 −0.1 0 0.1 0.2 0.3 0.4−1.5

−1

−0.5

0

0.5

1

1.5

qL [rad]

t L [N

m]

(b) Case 2.

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6−1.5

−1

−0.5

0

0.5

1

1.5

qL [rad]

t L [N

m]

(c) Case 3.

Figure 5.18: Force–length characterist ics.

st iffness σ can be described by a funct ion of type σ = AeγS (seeTable 5.2). Moreover, the equilibrium posit ion is q̄ = λ1+ λ22R(t) =

rR(t) for

muscles and q̄ = θm ,1+ θm ,22 = qℓ for VSAs.

St iffness model: σ = Aeγ S

Parameters Muscle VSA

A 2ρδR2(t) 2αβ

γ δ β

S c = λ2− λ12R(t) k =θm ,2− θm ,1

2

Table 5.2: Muscle force model and agonist ic-antagonist ic VSA model.

The role of λ i in the EP-H has hence a robot ic counterpart that,in our framework, is represented by motor posit ions θm,i .

250

q Link Position

τ Ext

erna

l Lo

ad

Suitable non-linear springs can closely replicate the human muscle behaviour

Human Hands

Robot Hands

• Extensive neuroscientific evidence for the existence

of sensorimotor synergies and constraints Babinski (1914!), Bernstein, Latash, Bizzi, Arbib, Jeannerod, Wolpert, Flanagan, Soechting, Sperry, …

• Quantitative work on hand postural synergies dates back ~15 years

• Santello, Flanders and Soechting (1998, J. Neuroscience) collected and analyzed the statistics of a large database of human grasps

Enabling Science - II Synergies in the Hand Motor System

(3-rd synergy)

The Shape of Synergies Glossary: “Postural Synergies” = Principal Components of Grasp Covariance Matrix First two synergies explain ~84%, first three ~90% of the covariance. First synergy alone more than 50%

(1-st synergy) (2-nd synergy)

The problem

How to make and use hands that are

• soft yet strong • simple yet dexterous • intelligent yet practical

Our Approach - Soft Robotics Technology - Theory of Human Synergies

• Ashtray

Soft Synergies

The PISA/IIT Soft Hand

Articular Joints and Soft Ligaments

for Robustness & Safety

Innovative Design

Safety & Robustness By Design

The Pisa-IIT Soft Hand

Grasping mugs & embodied intelligence

• Same hand • Same object • Same on/off control

• Two different grasps

depending on affordance

Pisa-IIT SoftHand with EMG teleimpedance control :

Strong but Delicate

Push the hand against the environment to shape it - strongly

but also softly (from the same ream…)

Applications of VSA & VIA

d

?


• We suspect there is a much wider range of applications than few researchers alone can explore

• Idea: crowdsource the exploration of the new territory


Take the Initiative

Main issues

• Cost • Time • Know-how • Diffusion

Solutions • Lower cost • Modularity • Public access,

easy utilization • Open discussion

Full Open

Platform

SW

Electronics HW

Mechanical HW

… fostering the diffusion of soft actuation for robots that move like you…

Natural Machine Motion Initiative

www.

.com

machine

open paradigm BSD & Creative Commons licensing leads to the fast diffusion of the technology best choice for developers create a community to get support and feedback examples: Linux, I-Cub, Arduino

natural machine motion initiative

Take the Initiative

Main issues

• Cost

• Time

• Know-how

• Diffusion

Solutions

• Lower cost

• Modularity

• Public access, easy utilization

• Open discussion

Full Open Platform • SW • Electronics HW • Mechanical HW

website

3 main sections

• Explore – devices, tools, projects

• Join – events, how to contriubute

• Docs – Q&A, Forums, Papers


Explore

• Devices Drawings, schematics, instructions for making soft robotic components: • Actuators (SEA, VSA,

…) • Accessories • Systems • …

• Tools Accessories to evaluate, chose and run your soft robot: • Datasheet • Simulators • Libraries • …

Explore

Explore • Projects Implementation of ideas that exploit the full potential of soft robot: • Bimanual Grasping and handover • Qbmove maker - Arduino interface • …

Docs

• FAQ • Forum

• Papers – a list of selected publications on Soft

Robotics, e.g.: - “Variable Impedance Actuators: a Review”

[Vanderborght et al.] - Datasheet Template [Grioli et al., IJRR 2014]


VSA - Datasheet

Join

• Events

• NMMI winter school (20-25 February, 2015)

• IROS 14 Workshop • …

• Contribute • share your projects • Take your turn in running

the Initiative


a variable stiffness servo actuator qb move

The natural motion actuator you can download and build yourself

spin-off of:

Università di Pisa and IIT

Fully Open Sources contributed to NMMI by

SAPHARI “Summer” School Rome, February 20-25, 2015

Friday, Feb. 20th : School Saturday, Feb. 21st : School Sunday, Feb. 22nd: OFF Monday, Feb. 23rd: School Tuesday, Feb. 24th: School

Wednesday, Feb 25th: Workshop

Wednesday, Feb. 25th: Competition

Look forward to seeing you soon at

naturalmachinemotion.com

natural machine motion initiativemech.vub.ac.be/iroswsactuators/workshop_iros14.pdfnikos tsagarakis,...

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