Motion Planning of Robotic Systems for Applications in Nuclear Facilities Clean Up

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Motion Planning of Robotic Systems for
Applications in Nuclear Facilities Clean Up

• By
• Peter S. March, Chetan Kapoor, and Delbert Tesar
• Robotics Research Group
• The University of Texas at Austin

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Presentation Outline

• Introduction
• Motion Planning (MP) Software
• Reasons for MP Software
• Requirements for MP Software
• Development of MP Software
• Applications of Software
• DD Demo
• DD Plasma Torch Cutting
• Glovebox Automation
• Conclusion

 
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Robotics Research Group (RRG)
To produce modular systems which exhibit
advanced performance at reduced costs whose
architecture matches that of todays computers,
allowing rapid repairs and a reduced threat of
obsolescence

• Two Major Areas of Research
• Intelligent Actuators for Robotics
• System Level Decision Making and Software
• Accomplishments
• 50 M.Sc. and 20 Ph.D. Graduates since 1985
• Currently, 12 M.Sc. and 7 Ph.D. Students
• More than 17M in funding since 1985
• Sponsors have included NASA, DOE, ATP, DARPA

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Introduction

• University Research Program in Robotics (URPR)
• DOE Sponsored Program Conducting Research on
  Robotic Applications for Nuclear Facilities Clean
  Up
• Participating Universities
• University of Florida
• University of Michigan
• University of New Mexico
• University of Tennessee
• University of Texas

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Introduction

• Why Use Robotics?
• Reduce onsite involvement of humans in hazardous
  environments
• Reduce Overall Costs
• Problems with Robotic Use
• Difficult to implement
• Difficult to maintain
• Requires highly skilled operators

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DD Tele-Robotic Task

• Concept
• Move away from pure tele-operation and pure
  automation to perform more complex operations
• Combine tele-operation, sensing, automation,
  motion planning, decision making, etc

• Task Level Planner
• Decision-making
• Trajectory Execution

• Data Input
• Tele-operation
• Vision Systems
• Sensing

• Motion Planner
• Trajectory Generation

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Motion Planning Software

• What is Motion Planning?
• Motion Planning is the generation of smooth
  motion trajectories for robotic systems.
• Types of Motion Planning
• Joint-Space Planning
• End-Effector (Cartesian)
• Space Planning

(xf,yf,?f)
(xi,yi,?i)
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Motion Planning Software

• Trapezoidal Motion Specification
• Define derivative of motion curve to have
  trapezoidal shape
• Derivative that trapezoid is defined in is known
  as the order of the system
• Positions determined through integration

2nd Order Motion System
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Motion Planning Software

• Software Requirements
• Easy to use and reprogram
• Applicable to a variety of robotic systems
• Able to produce trajectories in both Joint Space
  and End-Effector (Cartesian) Space
• Able to produce trajectories with respect to
  defined constraints (max velocity, max
  acceleration, etc.)
• Able to be easily expanded to more complex
  operations

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Motion Planning Software

• Operational Software Components for Advanced
  Robotics (OSCAR)
• Concept
• Generalized to N-DOF Systems
• Criteria Based Decision Making Core
• Open Interfaces via Emerging Technologies
• Real-Time, Simulation, and Design
• PC Based
• Development
• 3 developers for past 5 years
• Online reference manual with tutorials and sample
  code

http//www.robotics.utexas.edu/rrg/downloads/softw
are/oscar/
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Motion Planning Software
OSCAR Implementation Overview
Operator Interface Layer
Machine Interface Layer
Generalized Operational Software Layer

• Forward Kinematics
• Inverse Kinematics
• Performance Analysis
• Obstacle Avoidance
• Dynamic Modeling
• Deflection Modeling
• Motion Planning

• Real-time Event Handling
• Hardware Interfacing
• Simulation Interfacing
• Servo Communication
• Network protocols

• Robot Programming
• Variety of controllers.
• Variety of operator backgrounds.
• Compatible with GUI Programming Objects
• Network protocols

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Motion Planning Software

• Class Hierarchy for MP Software
• MotionPlan
• Contains routines to
• generate trapezoidal
• motion profiles
• OffLineMotionPlanner
• Generates and stores
• trajectories (useful for
• automation)
• OnLineMotionPlanner
• Generates real-time
• trajectories (useful for
• tele-operation)
• MotionParameter
• Stores information on time intervals,initial and
  final configurations, and constraints (max
  acceleration, max velocity, etc)

 
MotionPlan


OffLineMotionPlanner

OnLineMotionPlanner

MotionParameter

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DD Demo

• DD Demo
• Used as validation of software
• Robotics Research Corporation K/B 2017 17 DOF
  dual-arm robot
• Performs a demonstrative DD task (material
  reduction)
• Uses Joint Space and End-Effector Space planning
• Executed with linear interpolation, and 1st and
  2nd order motion planning

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DD Demo

• 5 Motion Curve Criteria
• ymax - maximum velocity of the motion, provides
  a good indicator of the inertial energy
• yrms - root mean square of the acceleration
  curve, high values are an indication of high
  inertial forces
• ?y - peak-to-peak value of the acceleration
  curve, indicates the range of inertial loading.
• ?? - peak-to-peak value of the torque curve,
  indicates the range of torque demands.
• ?max - derivative of the torque curve.

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DD Demo Results

• Easily integrated into existing application
• Visual improvement over linear interpolation
  routines
• Improvement in all
• criteria except
• max velocity
• Improvement
• most dramatic
• with joint space
• planning
• 1st Order planning
• showed more
• improvement than
• 2nd Order planning

Joint Space Planning
End-Effector Space Planning
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DD Demo
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Application DD Plasma Torch Cutting

• Plasma Torch Cutting Simulation
• Schilling Titan 2 with 1-DOF End-Effector
• Tele-Robotic Operation
• Tele-operated to
• determine set points
• Automated task
• performs cut
• Decision-Making
• Determination of Tool configuration
• Optimization of rotation about z-axis of tool

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Application DD Plasma Torch Cutting
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Application Glovebox Operation

• Modular Small Automation Systems
• 1 DOF to 5 DOF Systems
• Manually Reconfigurable Through Glove Port
• Motion Planning for Efficient Paths and
  Automation
• Physical Demonstration
• DOE URPR and LANL Supported Research

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Conclusion

• Software Results
• Easily integrated into existing application (DD
  Demo)
• Extensible to more complex applications (Plasma
  Torch Demo)
• Resulted in visibly smoother motion and improved
  system performance over linear interpolation
• Future Work
• Addition of Online motion planning
• Applications to more complex tele-robotic tasks
• Improved end-effector space planning