1. N I C H O L A S W E T T E L S , A V I N A S H R .
P A R N A N D I , J I - H Y U N M O O N ,
G E R A L D E . L O E B , A N D G A U R A V S .
S U K H A T M E
Grip Control Using Biomimetic
Tactile Sensing Systems
P R E S E N T A T I O N C R E A T E D B Y P U R N I M A S H A R M A
H O C H S C H U L E R H I N E - W A A L U N I V E R S I T Y O F A P P L I E D
S C I E N C E , G E R M A N Y

2. Table of Contents
 Introduction to Grip Control
 Calculation of Minimal Grasp Force
 Previous Approaches and Authors‘ approach
 M2 hand
 The Biotac Sensor
 Kalman Filter
 Algorithms and Constraints
 Conclusion
 References

3. Introduction to Grip Control
 Why do we need grip control?
- Reduction of unnecessary energy usage
- Preventing the damage to the object
 Why do we need tactile sensing?
- Not for inital grasp
- For minimization/optimization of grasp force once object
contact has been done
 Humans adjust grip force on objects relative to normal
and shear forces at the contact surface

4. Calculation of Minimal Grasp Force
The minimal grasp force to hold an object is
determined by ensuring the ratio of normal to
tangential reaction forces multiplied by the static
coefficient of friction (µF) exceeds one.
1 < µF x Fnorm/Ftan
 (assumption of authors µF =0.5)

5. Previous Approaches
 Gunji et al.- To detect slip and adjust grasp Gunji
used proportional force controller.
 Stansfield – To control a pinch grabber Stansfield
used a six-axis strain gauge sensor
 Yussof et al.- To control a pinch grabber Yussof used
a custom tactile sensor based on an optical signal.
 Beccai et al. - implemented a triaxial MEMs force
sensor to resolve slip by analyzing forces and
transitions between static and kinetic coefficients of
friction

6. Authors‘ approach
 Online/real-time (algorithm)
 Biomimetic
 Regardless of point of contact
 Overcoming the limitations of commercially availible
sensors

7. OTTO BOCK MICHELANGELO (M2)

8. Operation of M2 hand
 Thumb and all four fingers simultaneously open and
close to the palm.
 The fingers operate at a maximum speed of 408 mm/s
and maximum force of 60 N.
 The hand operates under fingers proportional–
differential position control and proportional force with a
fixed velocity.
 The hand has a span of about 114 mm when the fingers
are open.

9. The Biotac Sensor
As forces are applied to the elastomeric skin, it
deforms the conductive path for the fluid that
makes up the sensor, increasing the impedance of
electrodes where the path narrows and decreasing
it where the fluid bulges.
 For realistic calculation multiple sensors were
arranged to sense both normal and tangential forces.
For test purposes, the normal force was estimated
from the mean of all normal forces.

10. Visual Respresentation of Forces

11. Kalman Filter for Tangential Force Calculation
 Why do we need Kalman Filter?
To calculate a force from the voltages and for state
estimation (initial state=zero tangential force)
Voltage to force relationship calculation can not be
direct like the normal force case; each of the
relevant electrodes will have a different
sensitivity to a given amount of tangential force.

12. Algorithms and Constraints
 In this case, it is a precision pinch–grasp so the ring finger
and thumb of the M2 hand serve as the primary contact
points.
 The algorithm is started and when the weight of the object is
no longer supported, the algorithm adjusts its grip to
maintain stable grasp .
 Hand position changes in response to tangential to normal
force ratio.
 The controller is set to achieve a safety factor of 1.20 (based
on Johansson’s values).

13. Flow chart of Grip adjustment

14. Conclusion
 It provides proof-of-concept for a force minimizing
and grip adjustment algorithm in a constrained
environment.
 The algorithm uses a KF for its tangential force
estimation, which boosts its robustness to noisy
signals.
 The electrodes designated to interpreted tangential
forces and normal forces will depend on the posture
of the hand.

15. References
 Nicholas Wettels, Avinash R. Parnandi, Ji-Hyun Moon,
Gerald E. Loeb, and Gaurav S. Sukhatme, “Grip
Control Using Biomimetic Tactile Sensing
Systems”, VOL. 14, NO. 6, pp-718-723,DECEMBER
2009.
 NicholasWettels, Veronica J. Santos, Roland S.
Johansson and Gerald E. Loeb, Biomimetic Tactile
Sensor Array, Advanced Robotics 22 (2008) 829–849.
 Martin Buss, Bdeki Hashimoto, and John B. Moore,
Dextrous Hand Grasping Force 0ptimazation, IEEE
TRANSACTIONS ON ROBOTICS AND AUTOMATION,
VOL 12, NO 3, JUNE 1996.