TARDEC Robotics Update to the Joint Robotics Program

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TARDEC Robotics Updateto the Joint Robotics
Program
Curt Adams [phone] Associate
Director Vetronics Technology Area U.S. Army
Tank-Automotive RDE Center (TARDEC) Vetronics
Technology Area (AMSTA-TR-R, Mailstop
264) Warren, MI 48397-5000
8 November 2001
UNCLASSIFIED
Tank-automotive Armaments COMmand
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Outline

• Vetronics Technology Integration (VTI) Contract
• Crew integration Automation Testbed (CAT) ATD
• Robotic Follower ATD
• RDEC Federation CalEx Experiment
• Intelligent Mobility Omni-Direction Inspection
  System

Vetronics Technology Area Mission To conduct
research in the Vetronics technology areas of
crew stations, electronics architecture, embedded
simulation and robotics while leveraging advanced
automotive technology to provide our soldiers
with the worlds most advanced ground vehicle
systems and logistics support equipment.
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Vetronics Technologies
General Shinseki and MG (P) Caldwell Visit
Embedded Simulation
Crew Stations

• Cognitive Aids
• Route Planning
• Auto Driving
• 3-D Audio
• Speech Recognition
• Indirect Vision Driving

• Mission Planning
• Mission Training
• Battlefield Visualization

Robotics
Electronics Architecture

• Semiautonomous Perception
• Soldier-Robot Interface
• Intelligent Situational Behavior
• Leader-Follower Technology

Vetronics Technology Area Intelligent Systems
for the Objective Force
Improved hardware and software reusability
Reconfigurable component based Software Ref Arch

• Unmanned Systems
• Warfighter Interfaces
• Warfighter Decision Aids

Open Interface based Sys Ref Arch
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Vetronics Technology Integration Objectives

• Advance ground vehicle cockpit and robotic
  follower technology state-of-the-art
• Develop, integrate and test CAT and RF ATD
  programs
• Provide technology risk mitigation to FCS
• Provide technology readiness to FCS Milestone B
  and Block Upgrade Schedule (Feb03 and Feb06)

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VTI Contractor Team

• Team Member Focus Areas
• General Dynamics Land Systems -Program
  Management, Systems Integration, CAT
  Lead
• General Dynamics Robotic Systems -Technology
  Insertion, RF Lead,
• Field Experiments
• Applied Systems Intelligence -Intelligent Control
  Architectures, Decision Aids
• Micro Analysis and Design -Human Performance
  Modeling
• Carnegie Mellon University -Geometric Planning,
  Map Registration, Road Following
• Oasis Advanced Engineering -Embedded Training
  Systems, SMI, Modeling and Simulation
• General Motors Defense -CAT and RF Platforms
  (IAV
• Infantry Carrier)

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Vetronics Technology Testbed Crewstation
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CAT TECHNICAL APPROACHLEVERAGES CURRENT PROGRAMS

• VTT
• Crew Station Design and SMI
• Speech Recognition
• Indirect Vision
• ARLs Demo III
• Hardware Architecture
• Software Architecture
• Autonomous Mobility
• Symbolic Planning and Agent Based Associate - ASI
• Geometric Based Planning and Map Registration -
  CMU
• Obstacle Avoidance
• Communication and Navigation

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INDIRECT DRIVING AID

• Two Ways To Improve Indirect Driving
• Driver Cued
• Tele-reflexive

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Robotic Follower ATD (STO III.GC.2000.04 )
Pacing Technologies
Semiautonomous Perception
Soldier-Robot Interface
Intelligent Situational Behavior
Leader-Follower Technology

• Affordability Metrics
• Total Sensor Cost lt370k
• Technology Protection Plan
• Completed April 2001.
• Modeling and Simulation
• April 2003 MS Demonstration of end ATD Exit
  Criteria
• Integrates mobility, sensor and terrain models

• Solution Approach
• Manned leader proofs path to reduce perception
  intelligence requirements
• Rapidly mature integrate perception technology
  to enable higher speed enhanced decision making
  capabilities
• Successively demonstrate maturing capability for
  FCS

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Robotic Follower Systems Solution

• H/W S/W (obstacle avoidance algorithms and AM
  sensors) design based on Demo III
• A separate LADAR at the rear for safe back-up
  maneuvers.
• In addition to sending back GPS waypoints,
  leader will use its onboard sensors to
• collect and send back higher resolution terrain
  data (1 meter or less) to RF.
• Sensor terrain data will be registered to
  coarser onboard DTED map (4-10 meters) using
• advanced map registration techniques.

Interim Armored Vehicle (IAV) LAV III infantry
carrier for RF platform.
Demo III world model generated from LADAR sensor.
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AUTONOMOUS MOBILITY SENSORS
The Digital 14-bit output of the Indigo Phoenix
Imager will greatly increase the performance and
robustness of the stereo imaging process
GDRSs 77GHz Radar Scans 90 degrees 10 times/sec
in 1 degree steps
GDRS LADAR Generates High Fidelity 3-D Terrain
Elevation Information at 30 Frames/sec
The Sony DXC-390 camera, with a 640x480 pixel
array
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MAP INTEGRATION FOR PLANNINGON CAT AND RF
The geometric planner receives information from
multiple sources including the vehicles onboard
sensors and external map data. All the data must
be registered to ensure integrity of the internal
representation
Digital map
Local elevation map from on-board sensors
DTED
Obstacle map from on-board sensors
Features from on-board sensors
Geometric Planner
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MAP REGISTRATION AND INTEGRATION
?

• Terrain Elevation Data
• Terrain Features
• Landmarks

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3-D REGISTRATION
Example of registration of map using elevation
information A low-resolution DTED (upper right)
is registered with a local, high-resolution,
elevation map from on-board range sensing (upper
left) to produce an updated map
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ROAD DETECTION
Typical result of road tracking on unimproved
road. Edges are tracked by looking for
transitions from road to non-road terrain type.
Typical result of road detection on highways.
The algorithms can cycle at frame rate on
conventional hardware
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ON-COMING VEHICLE TRACKING
Field of Interest is Used to Minimize
Processing Requirements and Maximize Visual
Servoloop Rate
Feature Classifier Locates Lead Vehicle Within
the Scene
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Data Collection Playback
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Robotic System Simulation
High Fidelity Terrain Database
Imagery
Autonomous Mobility Algorithms
Physics-Based Sensor Models
Mobility Commands
Vehicle Mobility Information
Vehicle Mobility Model
Line Level Equivalence to Real Sensors
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ATD Exit Criteria
Affordability Metric Specific efforts to reduce
sensor cost are not part of this ATD. While
reduction in cost for computing capabilities is
expected, additional computing capabilities will
be required to meet goals. This ATD will strive
to keep the total cost of the autonomous mobility
suite at or lower than the current Demo III cost
of 370k.
1 Difference between achieved performance in 2003
and End ATD will be demonstrated via modeling
simulation. 2 Parameters for obstacle detection
Positive obstacles Height above ground plane
Negative obstacles Depth, Width, and Span in
direction of travel (expressed as DxWxS)
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TRL Milestone Chart Accelerated Robotic Follower
ATD
FY01 FY02 FY03
FY04 FY05
Semi- autonomous Perception
Soldier- Robot Interface
Intelligent Situational Behavior
Leader- Follower Technology
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Description of CalEx Simulation

• The Vehicle Dynamics Mobility Server (VDMS) is a
  high resolution model that using the High Level
  Architecture (HLA) to communicate, can portray
  robotics vehicles. This allows for
  soldier-in-the-loop experimentation using a
  Robotics Operator Control Unit (OCU).
• Such variables as payload and tire pressure can
  be modified and changed to help determine the
  optimum design.
• This tool can be used to evaluate contractors
  concepts against one another in military
  significant exercises in the support of FCSS.

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RDEC Federation CalEx Data Results

• The RDEC Federation ran a road march scenario
  with nine robotics vehicles with varying payloads
  and tire pressures on a Bosnia database. The
  following was determined
• Payloads An increase in payload caused the
  vehicles to slow down as expected.
• Tire Pressures An increase in tire pressure did
  not represent an increase in speed. TARDEC
  vehicle dynamics engineers concluded that the
  higher pressures caused larger vibrations and
  deviations from the ideal course. This in turn
  may cause the vehicle to be a little tougher to
  control and it may actually travel a larger
  distance overall.
• Recommendation for this vehicle on this type of
  terrain would be to use 30 lbs. of tire pressure.
  

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Omni-Directional Inspection System (ODIS)
Funded by the JRP Man-Packable Robotic
Systems (MPRS) program
AUVSI Demonstration
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Under vehicle Inspection using the ODIS RobotPOC
Grant Gerhart/TARDEC

• ODIS Robot Current Technology
• Low profile platform fits under vehicles
  man-packable, weighs less than 50lbs.
• Replaces mirror on a stick inspection
• 2-3 hour run time with hot-swappable batteries
  4 mph top speed
• Tele-operated video inspection with active LED
  lighting
• Com link transmits real time video data to base
  station operator
• Uses omni-directional drive technology for high
  mobility/maneuverability
• Inspects vehicle underbodies for bombs,
  contraband, etc.
• Demonstrated and tested at AUVSI, Ft. Leonard
  Wood and TARDEC
• Three ODIS robots available for User testing in
  January 2002

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Under vehicle Inspection using the ODIS RobotPOC
Grant Gerhart/TARDEC

• ODIS Robot Future Technology
• Advanced sensor suite including video, thermal,
  acoustic and chem/bio sensors
• OCU will feature fully autonomous and
  tele-operational behavior
• OCU will use wearable or hand held computers for
  imaging navigation
• Operate on military law enforcement
  communication frequencies
• Marsupial deployment and improved endurance
• Image enhancement and object recognition
  license plate reading
• Extensive testing at the 2002 Winter Olympics and
  Hill AFB

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Under vehicle Inspection using the ODIS RobotPOC
Grant Gerhart/TARDEC