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• Proprioceptive data available:
Position and movement of JOINTS,
BODY ORIENTATION & RATE OF
ORIENTATION CHANGE
• Not much sensory data available
• Maximize self-rightability of fielded
robots
• Improve performance
• MATLAB  C++
• Exhaustive  Terminal
• Increase degrees of freedom handled
• Transition the analysis framework from 2
dimensions to 3 dimensions
• Exhaustive search strategy = big issue.
• We must continue to translate the code
to a platform with more memory, and
expand code to 3D.
• We can use PRMs and RRTs to
simplify the search problem.
• We can use the idea behind White Box
testing and apply it to use the limits of
the program to our advantage.
• These methods can make the problem
smaller by only considering the best of
the random path plans vs. finding all
paths and the best of all the path plans.
Towards Autonomous Self-Righting for Robots in 3D
Barbara Jean Neal
Majoring in Computer Science
Attending Chicago State University
ARL Mentor: Chad Kessens
Directorate/Division: VTD/ASD
Duration of Project: 06/06/16– 08/12/16
Approved for Public Release; Distribution Unlimited
Approved for Public Release;
Distribution Unlimited
Wider ApplicationsArmy Applications
Resting on its rear and
arm
Joint
• Numbers indicate sets of continuously stable states.
• Decimals indicate transition costs.
Node
-15º
Tipping points
Center of
mass
Support
Polygon
Projection onto
horizontal
A. Find side of the hull that the
robot is resting on
B. Project this onto the horizontal
C. Where is the Center of mass,
in the projection?
• Above projection =Stable
• Edge of projection =Tipping
Point
• Not above projection
=Unstable
2D depiction of Self-righting Validation Platform
Objectives
Impact
Past ARL Work and Challenges
Conformation Space Map
(Grows exponentially)
Directed Graph Illustration Structure
(Smaller subspaces)
2D
swing Consider a program:
• Analyzes each joint motion in
one degree increments, each
joint range is100 degrees
• Analyzing each state 1 ms.
• Single DOF system 0.1 s.
• 4 DOF system 100,000 s.
• 6 DOF system 10^9 s, or 31+
years to compute!
Technical Approach
• Both PRM and RRT use a distance function
to measure the effective displacement
between two points in configuration space
• Now consider: Distance from one orientation
to another
• Point 1 = Current
• Point 2 = an orientation Δ toward the goal
• Repeat
Flowchart Flow Graph
If/else
statements
Programming strategy:
• Imagine numbers on
the PRM method at
every point
• The white box testing
method gives a way to
eliminate any extra
information before
testing the entire path.
• If a common number is
met, drop the longer
paths immediately
• This will guarantee the
most optimized
outcome with the
available data.
2
1
3
4
5
0.1 0.2
0.5
0.1
0.1
0.1
0.1
Set stop at 6, Test legs of the code simultaneously,
eliminate all but the lowest cost to 6 right away6
Discussion
&
Conclusions
Path Forward
Grows exponentially as
degree of freedom
increases
1

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NEAL-2016 ARL Symposium Poster

  • 1. • Proprioceptive data available: Position and movement of JOINTS, BODY ORIENTATION & RATE OF ORIENTATION CHANGE • Not much sensory data available • Maximize self-rightability of fielded robots • Improve performance • MATLAB  C++ • Exhaustive  Terminal • Increase degrees of freedom handled • Transition the analysis framework from 2 dimensions to 3 dimensions • Exhaustive search strategy = big issue. • We must continue to translate the code to a platform with more memory, and expand code to 3D. • We can use PRMs and RRTs to simplify the search problem. • We can use the idea behind White Box testing and apply it to use the limits of the program to our advantage. • These methods can make the problem smaller by only considering the best of the random path plans vs. finding all paths and the best of all the path plans. Towards Autonomous Self-Righting for Robots in 3D Barbara Jean Neal Majoring in Computer Science Attending Chicago State University ARL Mentor: Chad Kessens Directorate/Division: VTD/ASD Duration of Project: 06/06/16– 08/12/16 Approved for Public Release; Distribution Unlimited Approved for Public Release; Distribution Unlimited Wider ApplicationsArmy Applications Resting on its rear and arm Joint • Numbers indicate sets of continuously stable states. • Decimals indicate transition costs. Node -15º Tipping points Center of mass Support Polygon Projection onto horizontal A. Find side of the hull that the robot is resting on B. Project this onto the horizontal C. Where is the Center of mass, in the projection? • Above projection =Stable • Edge of projection =Tipping Point • Not above projection =Unstable 2D depiction of Self-righting Validation Platform Objectives Impact Past ARL Work and Challenges Conformation Space Map (Grows exponentially) Directed Graph Illustration Structure (Smaller subspaces) 2D swing Consider a program: • Analyzes each joint motion in one degree increments, each joint range is100 degrees • Analyzing each state 1 ms. • Single DOF system 0.1 s. • 4 DOF system 100,000 s. • 6 DOF system 10^9 s, or 31+ years to compute! Technical Approach • Both PRM and RRT use a distance function to measure the effective displacement between two points in configuration space • Now consider: Distance from one orientation to another • Point 1 = Current • Point 2 = an orientation Δ toward the goal • Repeat Flowchart Flow Graph If/else statements Programming strategy: • Imagine numbers on the PRM method at every point • The white box testing method gives a way to eliminate any extra information before testing the entire path. • If a common number is met, drop the longer paths immediately • This will guarantee the most optimized outcome with the available data. 2 1 3 4 5 0.1 0.2 0.5 0.1 0.1 0.1 0.1 Set stop at 6, Test legs of the code simultaneously, eliminate all but the lowest cost to 6 right away6 Discussion & Conclusions Path Forward Grows exponentially as degree of freedom increases 1

Editor's Notes

  1. Small/medium/large funding/staffing Small <$250K (~1 man year) Medium $250K - $1M Large > $1M Talking Points ARL Contribution In what parts of this research does ARL lead the scientific community? What is ARL’s niche? Identify complementary work occurring in other parts of ARL. Collaborations Discuss internal and external partners, their affiliations, and the contribution of each to this project. Include email addresses of the ARL PIs.