Haptic Manipulation of Microspheres Using

1
Haptic Manipulation of Microspheres Using
Optical Tweezers (Graphics replaced to keep file
size small)
ICON
Ibrahim Bukusoglu, Cagatay Basdogan, Alper Kiraz,
Adnan Kurt Koc University, Istanbul, Turkey
We report the manipulation of glass micro spheres
having a diameter of 3-10 µm using optical
tweezers and with haptic feedback. We detect the
position of a micro sphere manipulated in a fluid
bed using a CCD camera and calculate the forces
acting on it due to the optical trap and viscous
drag. We estimate the optical forces between the
laser beam and the manipulated particle using a
mass-spring-damper model. For this purpose, we
calibrated the optical trap and calculated the
coefficients of the mass-spring-damper model
using image processing and curve fitting
techniques. The drag force is calculated using
the velocity of the sphere and the viscous
damping coefficient of the fluid. We also use a
potential field approach to generate a
collision-free path for the manipulated micro
sphere and display the optical trapping and drag
forces and the forces due the artificial
potential field to the user through the haptic
device for achieving better results in
manipulation and control.

• Optical trapping is a non-contact manipulation
  method.
• Object sizes ranging from single atoms to
  microscopic particles can be manipulated.
• Forces range from pN to nN.

Modeling
Set-up
Set-up
Characterization
We calculated the coefficients b, m, and spring
constant of laser potential. We applied a
sinusoidal displacement input to the scanner at a
frequency of 1 Hz and captured the motion of a
trapped microsphere using a video imaging system
at 25 Hz. We then calculated its position from
the captured video frames using the Image
Processing Toolbox of Matlab. We fitted
sinusoidal waves to the recorded scanner and
sphere positions to compute the velocity of the
scanner as well as the velocity and acceleration
of the trapped particle. The position, velocity,
and accelaration data were then inserted into the
dynamical equation and the unknown coefficients
were calculated using the least squares curve
fitting technique.
Haptic Feedback
We have implemented a path planning algorithm
based on a potential field approach to compute
the collision-free path of a trapped particle. In
this approach, obstacles (other particles) and
the goal are represented by repulsive and
attractive potential fields respectively. The
negative gradient of the potential function gives
the attractive force applied on the particle.
Manipulation Experiments

• Modes of manipulation
• WF without haptic feedback
• DF drag force as haptic feedback
• DPF drag force and force due to potential
  field as haptic feedback