1. Sensor Placement Agile Robotics Program Review August 8, 2008
Matthew Walter, Michael Boulet, Luke Fletcher, Matthew Antone, Nick Roy, Seth Teller

2. Outline Perception requirements Sensor types
Candidate sensor placements
Perception simulations
Data collection
Summary

3. Perception Tasks Several roles expected of forklift sensors
Situational Awareness: supervisor “bot’s-eye” view
Navigation: path planning, terrain mapping, obstacle avoidance
Object Detection: finding and recognizing trucks, pallets, slots; estimating pose
Object Manipulation: pallet geometry estimation, tine insertion, load balancing
Safety: Shouted command recognition, seeing beyond load, detecting proximity of humans
Requires array of sensor types and placements

4. Perception Constraints
System complexity
Simplify hardware and perception algorithms
Physical constraints
Maximize visibility, protect sensors
Practical considerations
Subject to acceptable limits on size, weight, power, cost

5. Sensor Types Exteroceptive (perceiving the world)
Array Microphone
FOV: 180 deg
Color Digital Camera
FOV: 90 deg
Res: 752x480 pix
Rate: 60 Hz
Proprioceptive (self movement)
GPS/IMU
Odometry
Mast and tine states
Wheel encoders
Interoceptive (internal state)
Motor, brake status
Strain gauges
SICK Laser Range Scanner Range: up to 80m
FOV: 180 deg
Res: 1 deg
Rate: 75 Hz
Hokuyo Laser Range Scanner Range: up to 4m
FOV: 240 deg
Res: 0.36 deg
Rate: 10 Hz

6. Cameras provide 360o situational awareness
Camera Placement
Cameras provide 360o situational awareness
Right
Front
Rear
Left

7. Supervisor Camera Views
Left
Front
Right

8. Skirt Laser Placement
Long-range skirt lasers assist in navigation and obstacle avoidance
Scan in plane approximately parallel to the ground

9. Pushbroom Laser Placement
Long-range pushbroom lasers assist in navigation and terrain mapping
Rear: 10-20m out
Front Top: 10-20m out
Front Bottom:
Close range, beneath load

10. Temporal Scan Persistence
Single scan sees only narrow “slice” of world
Each scan placed in local 3D coordinate frame
Requires knowledge of forklift, mast, and tine pose
Allows aggregation of multiple scans over time
Drive forward
Raise mast

11. Lasers for Navigation

12. Skirt lasers (“virtual tines”)
Pallet Sensor Layout
Short-range lasers move with mast and tines to perceive pallets and slots
Pushbroom (2-5m out)
Skirt lasers (“virtual tines”)

13. Pallet Sensing Simulations
Goal: study effects of sensor placement on pallet and slot perception
Use system infrastructure for simulation
Virtual 3D environment containing objects of interest
Simulated returns from lasers in various configurations
Data acquisition with different pallet types, pallet poses, ranges, approach maneuvers

14. Pallet Sensing Simulations

15. Simulated Data: Ground Pallet
No mast or tine motion
Approaching Pallet on ground
Tilt mast
Raise/lower mast

16. Simulated Data: Truck Pallet
Far-field, ~18m
Approaching Pallet on truck
Near-field, ~2m
Mid-field, ~4m

17. Real Data Collection Goal: acquire representative sensor data
Pallet approach and slot detection
Mast and tine movement to ‘scan’ objects
Realistic non-level, non-smooth surfaces

18. Data Collection Sensor Layout
Camera
Pushbroom
Vertical
Skirt

19. Short Range Laser Scans

20. Longer Range Laser Scans

21. Summary Sensor types determined to meet operational needs
Support situational awareness, navigation, object detection, object manipulation, safety tasks
Studies performed using simulated and real data sets
3D perception simulator with different configurations
Data collected from real forklift on realistic terrain
Objects ‘scanned’ using mast motion
Additional studies to be performed in coming weeks

22. Timeline (Year 1) start of year 1 end of year 1 today sep 08 nov 08
perception simulator
preliminary placement studies
sep 08
navigation sensors on forklift
experimental configurations
nov 08
all sensors on forklift
final sensor configuration
jan 09
precise body/mast calibration
experimental validation
mar 09
additional simulation
investigation of year 2 sensors
apr 08