Computational Design Synthesis and Optimization of...

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Prof. Kristina Shea

Computational Design Synthesis and Optimization

of Robots

Challenges of Mechanical and Mechatronic Design Synthesis

Multi-disciplinary: mechanical,

electronic and software

components

A large number of different

functional and behavioral

elements

Strong dependencies between

geometry, behavior and function

Complex 3D geometry parts and

assemblies

Complex geometric constraints

Strong dependency between

design and fabrication

Prof. Dr. Kristina Shea Engineering Design + Computing Laboratory 2

Computational Design Synthesis and Optimization

Prof. Dr. Kristina Shea Engineering Design + Computing Laboratory 3

Specify Task

Represent

Generate + Optimize

Explore

Fabricate + Test

Automated

Robot

Synthesis and

Optimization

Fused Deposition Modeling

sourc

e: m

imed, T

UM

4Prof. Dr. Kristina Shea

Robotic Systems

Passive Robotic Systems No actuators and control

No energy source necessary

Potential to save energy

Engineering Design + Computing Laboratory

Passive dynamic walking, Mcgeer, T., 1990, International

Journal of Robotics Research

Active Robotic Systems Actuators and feedback control

High task flexibility possible

Responsive to environment

High robustness

http://www.adrl.ethz.ch/doku.php/adrl:robots

5Prof. Dr. Kristina Shea

Prototyping of Passive Walking Robots using FDM (1)

A modular designDesign of different bearings

Design variables can be adjusted

after printing

Engineering Design + Computing Laboratory

6Prof. Dr. Kristina Shea

Prototyping of Passive Walking Robots using FDM (2)

Engineering Design + Computing Laboratory

“Designing Passive Dynamic Walking

Robots for Additive Manufacture”,

Stöckli, Modica and Shea.

Rapid Prototyping Journal, 22(5): 842-

847, Bradford: Emerald, 2016.

DOI: 10.1108/RPJ-11-2015-0170

7Prof. Dr. Kristina Shea

More Complex Solutions Can require less space

Can provide visual interest

Computational Design Synthesis of Passive Dynamic Robots

Engineering Design + Computing Laboratory

Single Pendulum Simplest possible solution

“Automated Synthesis of Passive Dynamic Brachiating Robots Using a Simulation-Driven Graph Grammar Method”,

Stöckli and Shea, Journal of Mechanical Design, 139(9), pp. 092301, New York, NY: American Society of

Mechanical Engineers, 2017.

DOI: 10.1115/1.4037245

8Prof. Dr. Kristina Shea

Robotic Taskwww.mc.maricopa.edu/dept/d10/asb/origins/primates/gibbons.htmConfiguration

Design

Multibody System

Computational Design Synthesis of Brachiating Robots

Engineering Design + Computing Laboratory

Embodiment

Part Shape

Fabrication

Physical Robot

9Prof. Dr. Kristina Shea

Results – Design Space

Engineering Design + Computing Laboratory

Space requirement

of single pendulum

Ideal cyclic locomotion

Number of bodiesEvaluation Plot

Final populations of eight different topologies

All do three successful swings

Three Objectives:

10Prof. Dr. Kristina Shea

Results

Engineering Design + Computing Laboratory

11Prof. Dr. Kristina Shea

Results

Engineering Design + Computing Laboratory

Less space required

Less space required

Less space required

CAD-Based Generative Design

An interactive environment for parametric spatial grammar rule definition,

generative design and search space exploration.

Prof. Dr. Kristina Shea Engineering Design + Computing Laboratory 12

https://sourceforge.net/projects/spapper/

Hoisl, F. and Shea, K. (2011) “An Interactive, Visual Approach to Developing

and Applying Parametric Three-Dimensional Spatial Grammars”, Artificial

Intelligence for Engineering Design, Analysis and Manufacturing, 25 (4): 333 –

356.

Spatial (and Graph) Grammars

Design Language

Grammar Rules

Vocabulary

45

-45

1 2

1 2

0

1 2

… … … … … … … …

Prof. Dr. Kristina Shea Engineering Design + Computing Laboratory 13

Spatial Grammars

C’ = C - t(A) + t(B)C’ = C - t(A) + t(B)C’ = C - t(A) + t(B)C’ = C - t(A) + t(B)C’ = C - t(A) + t(B)Rule R: A → B

C’ = C - t(A) + t(B)

Rule (R) Object (A)Matching

Condition (t)

Shape Grammar G = (S, L, R, I)

S finite set of shapes

L finite set of labels

R finite set of rules

I the initial shape where I

(S,L)0 (vocabulary)

Prof. Dr. Kristina Shea Engineering Design + Computing Laboratory 14

Robot Arm Concepts – 3D Labels

Engineering Design + Computing Laboratory 15Prof. Dr. Kristina Shea

Robot Arm Components – 3D Labels

r default

default

default finishhole

default

Engineering Design + Computing Laboratory 16Prof. Dr. Kristina Shea

Generated Components

Engineering Design + Computing Laboratory 17Prof. Dr. Kristina Shea

Generated Robot Arm Concepts

parameterized primitives

parametric rules

- shape complexity- constraints 3D labels

- constraints- shape complexity

Boolean operations,

sweeping

collision detection

- part collision avoidance- design space restriction

Engineering Design + Computing Laboratory 18Prof. Dr. Kristina Shea

Computational Design Synthesis of Virtual

Locomotive Soft Robots

Spatial grammar uses bending actuators

as building blocks

An actuator has a predefined, cyclic

activation pattern

Target gaits: walking, crawling, hopping

Engineering Design + Computing Laboratory 19

Spatial Grammar Simulation

Simulated Annealing

Prof. Dr. Kristina Shea

“A Spatial Grammar Method for the Computational

Design Synthesis of Virtual Soft Robots”, van Diepen

and Shea, ASME DETC conference 2018.

Results

Engineering Design + Computing Laboratory 20Prof. Dr. Kristina Shea

21Prof. Dr. Kristina Shea

Results in Action

Engineering Design + Computing Laboratory

HoppingCrawling

WalkingWalking

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