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Mobile Haptic Interface Progress From the Last Year and Future Plan. Presenter: In Lee HVR Lab Summer Workshop 2010.08.04. Mobile Haptic Interface. Issues on MHI. - Precise and smooth MP tracking. - Reduction of force induced by MP motion. Haptic Interface (HI). Local pose of HI.

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Mobile haptic interface progress from the last year and future plan

Mobile Haptic InterfaceProgress From the Last Year and Future Plan

Presenter: In Lee

HVR Lab Summer Workshop

2010.08.04


Mobile haptic interface

Mobile Haptic Interface


Issues on mhi

Issues on MHI

- Precise and smooth MP tracking

- Reduction of force induced by MP motion

Haptic Interface (HI)

Local pose of HI

Force feedback

+ Force from MP

Mobile Platform (MP)

World pose of MP

MP motion

+ Tracking error


Mp tracking error

MP Tracking Error

  • IS-900 has poor tracking ability for dynamic objects in contrast with its quite good performance for static ones.

IS-900

Pose Info. (at 200 Hz)

MHI Control PC

Tracker Server PC

X

Y

Z

Tracking error along X and Z-axis(about ±20 mm in maximum)

Position (mm)

Trajectory of a tracker that israndomly moved along Y-axisby a linear lift.

Time (ms)


Filter selection

Filter Selection

  • Low-pass filter: Noise freq. overlaps with that of signal.

  • Kalman filter: Difficult to choose the parameter values.

  • Moving Average: Filtering delay may affect the stability.

  • Moving average with variable window size: -> May reduce the noise effectively with small delay.


Adaptive moving average

Adaptive Moving Average

  • Proposed by Perry Kaufman (1998).

  • Exponential Moving Average (EMA).

    • yn = αxn + (1-α)yn-1= yn-1 + α(xn-yn-1),where, x: original signal, y: filtered signal, α: smoothing factor.

    • α = 2 / (w+1),where, w is window size.


Adaptive moving average1

Adaptive Moving Average

  • AMA adjusts α within a certain range, αmax and αmin, using following equations:

    • ERn = |xn – xn-t| / Σ|xi – xi-1|,where, t: test window size.

    • αn = ERn(αmax - αmin) + αmin.

  • Typically, AMA uses α2 instead of α to obtain more robust result against the noise.

n

n-t+1


Ama result

AMA Result

  • High frequency error is well removed.

  • Low frequency error is somewhat reduced but still exist.

  • Sensor fusion will be the key for further improvement.

Y-Axis

Original

Filtered

Position (mm)

X-Axis

Time (ms)


Closed loop control

Closed-loop Control

  • In the previous research, we used the closed-loop force control to reduce the force from the MP dynamics.

  • In the closed-loop control, PID gain setting is crucial and search for the optimal values requires hard work.

  • If the starting point (i.e., near optimum) for the gains can be known, the labor may greatly reduced.

  • Ziegler and Nichols proposed an empirical method for the near-optimum gains values.

  • The method requires the maximum P-gain, ku, which drives the system stably oscillate, and the period of the oscillation, pu.


Relay feedback auto tuning

Relay Feedback Auto Tuning

  • Autonomous method to find kuand pu.

  • Induces the limit cycle oscillation using a relay feedback.

  • Relay feedback:

  • ku =

r(e) = h, if e < 0,

-h, otherwise.

r(e) = h, if e < 0,

-h, otherwise.


Problems of current mp

Problems of Current MP

  • Soft suspension: complex dynamics

  • Mecanum wheel: vibration, slip

  • Heavy weight: dull response

  • Complex dynamics can severely degrade the quality of force control.


New mp design under work

New MP Design (under work)

  • High rigidity: no moving parts

  • Smooth motion: advanced wheel

  • Light weight: simple structure

  • Low center-of-mass: thin base


New mp design under work1

New MP Design (under work)

  • Omni-Ball, designed by K. Tadakuma and R. Tadakuma, is adopted for more smooth motion.


Other changes

Other Changes

  • Side-by-side stereoscopic rendering

  • Additional distant cue using transparent sphere

  • (optional) Command vs. actual force graph for online evaluation.

  • stylus-type, 3-dof end effector with a button


Conclusion

Conclusion

  • Adaptive moving average

  • Auto PID gain tuning

  • Design of new MP & end effector

  • Visual enhancements

Thank you!


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