Control and Simulation of Complex Robotic Systems

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13 Νοε 2013 (πριν από 4 χρόνια και 11 μήνες)

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Control and Simulation of
Complex Robotic Systems
Energid Technologies
www.energid.com
James D. English
RoboBusiness June 20, 2006 Pittsburgh
June 2006 Pittsburgh, Pennsylvania slide 2
Robots Will Change the World
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What is Holding Us Back?

Capability needs to be expanded

Cost needs to be reduced
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Algorithms and Software for Control
and Vision

High-Fidelity Validating Simulations
Energid’s Contribution

Focus: Complex Systems
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Control

Vision

Simulation
This Talk
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XML-Based Robot Description

There is a lot to describe about a robot

Energid has created, and is using in practice, an
XML-based language, MCML
“Metal-1”
“red”
“green”
“blue”
“frictionK”
0.5
0.5
0.75
0.2
“Metal-1”
Polygons
Surface Properties
String-Float Map
Shapes
Base Link
Link 0
Link 1
Link 2
Link 3
Universal
System
Static Base
Dynamic Base
Environment
System
State
Proximal
Frame
Distal
Frame
Joint Kinematics
Link
Actuator Properties
Sensor Properties
Mass Properties
Kinematic Structure
Reference Frame
s
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Any number and type of joint

Any number of branches

Any number and type of end effector

Configurable optimization, such as collision
avoidance
Robotic Control
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Joints and Degrees of Freedom
Energid’s focus is on complex systems with many
degrees of freedom
PA-10
7 DOF
LEMUR
30 DOF
Robonaut
40+ DOF
Branchin
g
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Cooperation, Branching, and Mobility

What approach best suits the problem?
Cooperating
Serial Arms
Multiple Levels
of Branching
Branching with
Mobility
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End Effectors and Constraints

What do you
really
want the robot to do?

2D Point Placement

3D Point Placement

3D Orientation

3D Pose

Linear Constraint

Center of Mass

Spatial Momentum

Other?
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Extra Degrees of Freedom

When constraints are satisfied, what is left?

Optimize everything else.
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Energid’s software uses a patented
combination of a unique algorithm with XML
configuration

Collision avoidance

Joint limit avoidance

Strength optimization

Accuracy optimization

Error recovery

Soft end effectors

Others
Configurable Optimization
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DEMO
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Simulation-Based Control

Our simulation is
modular

This allows it to be
embedded in the
controller
Simulation
Manipulators
Controllers
S
Embedded
Simulation

Digital simulation is fast. What can be done
with all that speed?
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DEMO
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Force Control

Force control uses Energid’s position and velocity
control framework
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Control

Vision

Simulation
This Talk
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Energid provides advanced algorithms to
handle critical robot-vision tasks

2D algorithms

3D object recognition

3D tracking
Vision
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Original B737 ImageFiltered aircraft image
Detected
door location
Robotic Aircraft Door Detection
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Object Tracking and Recognition

The system is able to identify objects using only
CAD models

Object models can articulate
CAD Models
Camera Image
Image
Segmentation
Initial Type, Pose,
and Geometry
Refined Type, Pose,
and Geometry
Spatial Stage ISpatial Stage IISpatial Stage III
A Priori
Knowledge
ID
and
Tracks
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Gestures for Robot Control

Human-body tracking
uses vision to determine
body movement

The system recognizes
gestures to guide robotic
systems

Examples: left, right,
stop
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Control

Vision

Simulation
This Talk
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Energid software for simulation-based
validation of robotic systems

Articulated dynamics

Impact dynamics

Application to validation
Simulation
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Many algorithms exist

Energid selects the best algorithm
automatically based on complexity
Articulation Dynamics
Body i
Body
j
Body
k
How do links interact through the
mechanical structure?
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Impact Dynamics

Energid uses its own
expanding-polytope
algorithm for
general polyhedra

Fast, tailored
methods are used
for special shapes

Detailed surface
properties are used
for modeling
How does physical contact affect the
dynamics?
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Robot Design Validation
Energid’s system includes a plugin for SolidWorks,
giving push-button validation.

Energid is creating an infrastructure for
automatic validation of robot designs

Given the model and a few parameters, a
control system is created and tested
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Monte Carlo Simulation

Multiple simulation runs

Robot parameters are randomized

Sensor and actuator noise is random

Gives high quality predictive results

Requires validation
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Performance Optimization

Variable robot parameters are defined

Monte Carlo analysis is used to optimize
performance
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Fast High-Fidelity Visualization
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DEMO
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Rapid Design Validation for Space
Robots

Robot for Application of High Intensity
Focused Ultrasound

Target Identification

Underwater Robot Control System

Aircraft Door Identification

Networked General-Purpose Robot
Control
Ongoing Application Development
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More complex mechanisms offer new
opportunities

Simulation-based validation can save
money and lead to better systems

Energid’s software can help you achieve
your goals
In Conclusion
Thank You!