Summary of ARM Research:
Results, Issues, Future Work
Kate Tsui
UMass Lowell
January 8, 2006
Summary of Work
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Programming the ARM
Accomplishments
Challenges
Future Work
Programming the ARM
 Control Modes
 Receiving and Sending Packets
 Structure of Communication Packet
Control Modes
 Manual and
Transparent Control
Modes
 Both are capable of
Joint Movement and
Cartesian Movement.
 Joint Movement - One
of six joints move at a
given time.
 Cartesian Movement Wrist moves linearly
in 3D space; joints
may move
simultaneously.
Control Modes: Manual Control
 The maximum velocity is 9 cm/s.
 Using Cartesian Movement, the ARM can
only move linearly in X, Y, or Z.
 Math processor handles safety checking,
Cartesian coordinate transform checking,
and calculation of necessary motor torques
for velocity inputs.
Control Modes: Transparent
Mode
 The maximum velocity is 25 cm/s.
 Using Cartesian Movement, the ARM can
simultaneously move in X, Y, and Z.
 Math processor is bypassed; safety check is
not done.
Communication: Receiving and
Sending Packets
 Communication thread is spawned during
program initialization.
 Based on single producer, single consumer
donut factory problem.
 Incoming packets from the ARM are stored
in reader 10,000 slot semaphore.
 Outgoing packets to the ARM are stored in
writer 10,000 slot semaphore.
Communication: Receiving and
Sending Packets
 ARM sends packet to PC every 20 ms
(hardware limitation).
 3 types of incoming packets.
 ID = 0x350, 0x360, 0x37F
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General Communication Packet
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Cartesian Mode Packet
Interpretation
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Cartesian Mode Packet
Transmission
 Velocity: p/(20 * 10-3) mm/s
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Accomplishments
 Design of initial interface
 Demo at Robotics: Science and Systems 2006
Conference Workshop on Manipulation for Human
Environments
 User Testing
 Paper presentation (forthcoming) at AAAI-07 Spring
Symposium Series Workshop on Multidisciplinary
Collaboration for Socially Assistive Robotics
Interface Design
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 Interface is compatible with single switch scanning.
 Left:
 Original image is quartered.
 Quadrant containing the desired object is selected.
 Middle:
 Selection is repeated a second time.
 Right:
 Desired object is in 1/16th close-up view.
Demo
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User Testing: Hypotheses
 H1: Users will prefer a visual interface
to a menu based system.
 H2: With greater levels of autonomy,
less user input is necessary for control.
 H3: It should be faster to move to the
target in computer control than in
manual control.
User Testing: Experiment
 Participants
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12 participants (10 male, 2 female)
Age: [18, 52]
67% technologically capable
Computer usage per week (including job related):
 67% 20+ hours; 25% 10 to 20 hours; 8% 3 to 10 hours
 1/3 had prior robot experience:
 1 industry; 2 university course; 1 “toy” robots
User Testing:
Experiment Methodology
 Two tested conditions: manual and computer
control.
 Input device was single switch for both controls.
 Each user performed 6 runs (3 manual, 3
computer).
 Start control was randomized and alternated.
 6 targets were randomly chosen.
User Testing:
Experiment Methodology
 Neither fine control nor depth existed in
implementation of computer control during
user testing.
 In manual control, users were instructed to
move the opened gripper “sufficiently
close” to the target.
User Testing:
Experiment Methodology
 Manual Control
Procedure, using
single switch and
single switch menu:
 Unfold ARM.
 Using Cartesian
movement, maneuver
opened gripper
“sufficiently close” to
target.
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User Testing:
Experiment Methodology
 Computer Control Procedure:
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Turn on ARM.
Select image using single switch.
Select major quadrant using single switch.
Select minor quadrant using single switch.
Color calibrate using single switch.
User Testing: Results
H1: Users will prefer a visual interface to a
menu based system.
 83% stated preference for manual control in exit
interviews.
 Likert scale rate of manual and computer control
(1 to 5) showed no significant difference in user
experience preference.
 H1 was not proven.
 Why? Color calibration
User Testing: Results
H2: With greater levels of autonomy, less user
input is necessary for control.
 In manual control, counted the number of clicks
executed by users during runs, divide by run time.
This yields average clicks per second.
 In computer control, the number of clicks is fixed.
 H2 was confirmed.
User Testing: Results
H3: It should be faster to move to the
target in computer control than in
manual control.
 Distance to time ratio: moving distance X
takes Y time.
 Under computer control, ARM moved
farther in less time.
 H3 was confirmed.
Challenges
 Vision system
 Shoulder camera
 Gripper camera
Evolution of UML Vision
System: Shoulder Camera
Evolution of UML Vision
System: Gripper Camera
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Current UML Vision System
 Shoulder (occupant’s
view) camera is a Canon
VC-C50i Pan-Tilt-Zoom.
 Specifications (NTSC):
 340,000 pixels
 460 horizontal lines, 350
vertical lines
 2:1 interlaced
 26x digital zoom
 Focal length: [3.5, 91.0]
mm
Current UML Vision System
 Gripper camera is CCD
Snake Camera.
 Specifications (NTSC):
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1/4” color CCD
510 x 492 pixels
350 vertical lines
2:1 interlaced
Focal length: 3.1 mm
Processor board located 30
cm from CCD.
Gripper Camera Placement
 Our choice was to
place camera within
gripper.
 Camera is inline with
axis.
Gripper Camera Concerns
 Wired:
 Wires impede movement
of ARM.
 Wireless:
 Image quality.
 Placement not within
gripper:
 Not within axis of
movement.
 Accidental knocking off
of camera.
 Folded position.
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Current/Future Work
 Integration of ARM with
power wheelchair
 Depth extraction (image
registration, motion filter,
optical flow)
 Occlusion
 User interface
 Initial testing at Crotched
Mountain