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Robots for Disabilities Leapmotion Testing for
Accuracy as an Input
Method for Robotic Surgery
Anthony Brill
Matthew Moorhead
5/18/15
Robotic Surgery
• Developed to address issues with
traditional surgery techniques
o increase dexterity/precision
o reduce recovery time
o reduce physiologic tremors
• Ability to perform surgery remotely
o battlefield for wounded soldiers
o transcontinental for specialized
surgery reaching more patients
• Limited long-term studies to truly
understand benefits/disadvantages
Robotic Surgery
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Robotic Surgery
5/18/2015 3
Surgical Robots
• Current end effector manipulation
accomplished by use of a joystick-
like controller
• A more intuitive, hands-free method
has potential for ease-of-use
Robotic Surgery
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Project Goals
• Examine the accuracy of position
measurements made by the
Leapmotion sensor
• Control a robotic arm utilizing the
Leapmotion sensor as the input
Robotic Surgery
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Leapmotion
Leap Motion
• Two monochromatic IR
cameras
• Tracks infrared light (850 nm)
projected onto hands
• 8 ft3 of interaction space
• Image processing
• Tracking algorithm infers
hand position and orientation
Leapmotion
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Tool tracking
• Tracks the tip of a “tool”
• A pencil is used in this study
• Data is only used once the z-
component reaches the threshold
• Tool requirements: o longer, thinner, and straighter than
a finger
o Cylindrical
Leapmotion
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Hardware Communication
• Leap Motion data is accessed
through processing
• Robotic Arm o Tip position is sent to the arbotiX-
M Robocontroller through Serial
Com.
• Data Collection o Text-files created are exported for
analysis in excel
Leapmotion
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Robotic Arm
Forward Kinematics
• Diagram
• Transformation matrices
• End effector equation
Inverse Kinematics
Robotic Arm
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L2
q2
L1
q1
n2
n1
a2
a1
b2
b1
O
P
Q
Robotic Arm
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NRA a1 a2
n1 c1 -s1
n2 s1 c1
ARB b1 b2
a1 c2 s2
a2 -s2 c2
NRB = NRA · ARB
NRB b1 b2
n1 c1c2 + s1s2 c1s2 - c2s1
n2 c2s1 - c1s2 s1s2 + c1c2
NRB b1 b2
n1 c1-2 s2-1
n2 s1-2 c12
=
Rotation matrices:
L2
q2
L1
q1
n2
n1
a2
a1
b2
b1
O
P
Q
Robotic Arm
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NRA a1 a2
n1 c1 -s1
n2 s1 c1
x = L1c1 – L2c1-2
y = L1s1 – L2s1-2
NRB b1 b2
n1 c1-2 s2-1
n2 s1-2 c12
L2
q2
L1
q1
n2
n1
a2
a1
b2
b1
O
P
Q End effector:
rQ/O = rP/O + rQ/P = L1a1 – L2b1
= L1c1n1 + L1s1n2 – L2c1-2n1 –
L2s1-2n2
Robotic Arm
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L2
q2
L1
q1
n2
n1
r
β
α
(xc, yc)
Processing Code:
● Acquires tip position
from Leapmotion
● Maps values for
graphical interface
● Sends position
information to Arbotix
Robotic Arm
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Graphical Interface:
● Grey box - motor mount
● Red line - extension
limit of arm
● Colored line - tracked
tip position
Robotic Arm
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Drawing Results
Parameter testing:
Motor Speed: ~2.20rpm
Delay: 10ms
Observation: choppy output
Change: increase motor speed
Robotic Arm Drawing Results
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5 10 15 20 25
5 10 15 20 25 Parameter testing:
Motor Speed: ~8.79rpm
Delay: 10ms
Observation: no noticeable change
Change: reduce delay time
Robotic Arm Drawing Results
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Parameter testing:
Motor Speed: ~4.39rpm
Delay: 5ms
Observation: slightly smoother
lines at higher tip speed
Change: increase path accuracy
between points (future)
Robotic Arm Drawing Results
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5 10 15 20 25
Sensor Results
Leapmotion Sensor Results
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Experimental set up:
•Coordinate resolution • Coordinates are provided in mm’s
•Series of two lines • 25, 20, 15, 10, and 5mm apart
• Mean of x-position
• Standard deviation of x-position
•Comparison • Comparing the measured distance
to average distance from the leap
5 10 15 20 25
Leapmotion Sensor Results
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Distance (mean):
5.26mm
Standard Deviation:
Left: 0.83mm
Right:
0.43mm
Leapmotion Sensor Results
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Distance (mean):
10.80mm
Standard Deviation:
Left: 0.59mm
Right:
0.33mm
Leapmotion Sensor Results
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Distance (mean):
16.11mm
Standard Deviation:
Left: 0.52mm
Right:
0.86mm
Leapmotion Sensor Results
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Distance (mean):
21.99mm
Standard Deviation:
Left: 0.41mm
Right:
0.34mm
Leapmotion Sensor Results
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Distance (mean):
26.60mm
Standard Deviation:
Left: 0.46mm
Right:
1.11mm
Problems
● Robotic Arm
o The path of the end effector between points is random
o Does not provide smooth transition between data points
o Tip position data is not smooth
o Motor resolution provides limited accuracy
● Data Collected
o Standard deviations are fairly large
o Human error introduces significant effects on data
Problems
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Conclusion
● The Leap Motion successfully controls the robotic arm through tool tracking
o Results show a noisy output, implementing a filter would help
o Implementing a dynamic controller (PD,PID..) would improve performance
o Path planning could decrease error between data points
● Data collected from the sensor on average was within 1.5 mm of the actual distance
o Not acceptable for robotic surgery needs
Conclusion
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