Active Haptic Control for a Biologically Inspired Gripper in

Reconfigurable Assembly Systems

Testing Active Haptic Control through Force Feedback

Christian Ivan Basson and Glen Bright

Discipline of Mechanical Engineering, University of KwaZulu-Natal, King George V Ave, Durban, South Africa

Keywords: Flexibility, Shape Conformity, Adaptability, Active Haptic Control, Force Feedback.

Abstract: Haptic feedback for flexible grippers enhances control over human-machine interaction and object

manipulation. Force feedback control through a haptic sensory system enables gripping sensitivity for the

grasping of fragile components. The development of intelligent gripping systems has the potential to be

implemented in Reconfigurable Assembly Systems, (RAS), for on-demand production lines. Advancements

in object control and successful object handling for assembling systems were investigated. An active haptic

control system was developed to assess the adaptability of gripper appendage grip force through a dynamic

pick and place movement. The aim was to determine the force output from a self-adjusting grasping procedure

using a haptic feedback control sensory system. The force output data was empirically collected and plotted

on a signal verse time graph. The voltage signal representing the actual grasp force throughout a gripping

procedure. The testing was performed on a previously manufactured gripper based on a biologically inspired

phenomenon called the Fin Ray Effect

. Conclusions and recommendations were made in relation to effective

grip force control.

1 INTRODUCTION

Modern assembly systems require superior production

rate capabilities. Reconfigurable Manufacturing

Systems, (RMS), satisfies the requirements for

flexibility and reconfigurability in manufacturing.

Production lines are required to be efficient in terms of

precise part control and placement (Bouchard, 2014).

Reconfigurable Assembly Systems, (RAS) are defined

by (Koren and Shpitalni, 2010) as follows:

“Reconfigurable assembly systems are those that can

rapidly change their capacity (quantities assembled)

and functionality (product type, within a product

family) to adapt to market demand”.

Flexible fixtures in RAS cater for product variety

and changes in part size through adjustable

mechanisms in dynamic response environments for

on-demand production (Padayachee and Bright,

2013). Flexible grippers are therefore applicable in

RAS. The end-effector of a robotic manipulator is

essential for part handling (Reddy and Suresh, 2013).

Flexible grippers are developed for multi-function

and high flexibility in gasping operations for pick and

place procedures and fixturing applications.

Grippers are improved through the means of

flexibility and performance. Flexibility and

performance have an inverse relationship with a one-

another shown in Figure 1. Gripper systems with high

flexibility sacrifice performance and vice-versa.

Grippers possessing adaption to part variety require

haptic feedback to increase the performance of

gripping.

Flexibilit

Performance

Number of tasks it can do

Accuracy and

repeatability

Figure 1: Performance verse flexibility of grippers.

Basson, C. and Bright, G.

Active Haptic Control for a Biologically Inspired Gripper in Reconﬁgurable Assembly Systems - Testing Active Haptic Control through Force Feedback.

DOI: 10.5220/0006840800810090

In Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2018) - Volume 2, pages 81-90

ISBN: 978-989-758-321-6

Product assembly in manufacturing is ineffective

in human-computer integration because assembly

systems consist mainly of geometric constraints and

lack haptic feedback attributes (Xia, 2016). Haptic

systems are divided into three (3) focus areas: Human

haptics, computer haptics and machine haptics.

Human haptics concern the sense of touch between a

human and object. The human “intuition” is described

as the input to a machine for object manipulation. The

algorithms and software utilized in computational and

simulated haptic feedback to describe the properties

of the interacted object are termed computer haptics.

Machine haptic technology is the focus research

of this paper. Machine haptics refers to the haptic

touch interfaces between a machine and an object.

The development and design of the haptic devices

augment and simulate human touch for intelligent

gripping systems.

Part handling employing haptic force sensitive

systems enable the complete control without human

intervention. Surface damage during part grasping is

avoided by utilizing minimum force threshold values.

Slippages are reduced through force control. Haptic

feedback systems allow for enhanced part machine

interactions. Haptic feedback systems can be

classified as active and passive.

Passive haptic feedback systems are implemented

into the monitoring of gipping systems without

energy inputs into the actuation of the grippers.

Active haptic feedbacks systems possess either partial

or full control of force application of gripping device

onto the object or computer-generated simulations

(Martin, et al., 2013). An active haptic feedback

system was investigated and introduced in the design

of a force-feedback control system. The active force

feedback additionally enables monitoring of force.

Active haptic control is necessary for orientation

and input acknowledgement. Haptic systems provide

improved mobility for robots in the form of touch

sense. Haptic control minimizes human interaction in

complex machine mechanisms and movement.

Physiological presence is improved through the

means of enhancing machines with intelligent control

systems using touch.

2 FLEXIBLE GRIPPERS IN

LITERATURE

Flexible grippers and fixtures are investigated to

substitute dedicated assembly stations that are

composed of devoted grasping and fixturing

mechanisms. The reduction of time loss per station

change in an assembly or disassembly of components

decreases overall production time. Modular and/or

flexible gripping methods have been recognized to

minimize time consumption in assembly station

overlay (Molfino, et al., 1999).

A six (6) degree of freedom design of a gripping

system for Flexible Fixtureless Assembly, (FFA), was

developed by (Yeung and Mills, 2004). The gripper

system designed provides functions for both a conven-

tional fixture and reconfigure-able gripper. The gripper

is able to change the gripping configurations to suit the

assembly procedure and part variety. A drawback to

the system was the position of grasp points on the

object to be manipulated has to be known. The

flexibility in terms of self-adjustment can potentially

be compromised.

A reconfigurable gripper design was investigated

by (Molfino, et al., 2006), using modular fixture units

to assemble and disassemble a washing machine. The

gripper mechanism consisted of rigid links and

hinges. The modular fixture device incorporates a

fuzzy controller to implement force control to identify

extrusions on the part surface. An anthropomorphic

modular reconfigurable gripper purposed by (Staretu,

2015), using exchangeable finger orientations. The

modularity of gripper appendages increases grip

variation for size and shape of objects.

A gripping mechanism consisting of Fin Ray

Effect

based appendages are described by (Tharayil,

et al., 2017). Self-conformity was investigated in the

Fin Ray structure and implemented in a self-

adjustment gripper system. The Fin Ray Effect

described by the deformation of a V-shaped rib

structure through an applied force P (Pfaff, et al.,

2011), illustrated in Figure 2. The undeformed rib

structure is shown in A and the deformed rib structure

is shown in B.

Figure 2: The working principle of the Fish Fin Effect

(Pfaff, et al., 2011).

Potential flexible grippers can be categorised as:

multi-fingered grippers, enveloping grippers and

malleable grippers. The design criteria comparison is

shown in Tables 1, 2 and 3, according to the

advantages, disadvantages and significant application.

ICINCO 2018 - 15th International Conference on Informatics in Control, Automation and Robotics

A design should be suitable for an applicable gripping

function.

Table 1: Advantages of flexible grippers.

Design Advantages

Multi-fingered

grippers

Flexibility gripping for different object

shapes, gripping wit force feedback

Enveloping

grippers

Adaptability to mould around the

object

Malleable

grippers

Adaptable to different shapes, reliable

gripping

Table 2: Drawbacks of flexible grippers.

Design Drawbacks

Multi-fingered

grippers

Control complexity

Enveloping

grippers

Low force control capability

Malleable

grippers

Low gripping dexterity

Table 3: Significant application of flexible grippers.

Design Significant Application

Multi-fingered

grippers

Grasping all shaped objects with force

control

Enveloping

grippers

Grasping oddly shaped and unknown

objects

Malleable

grippers

Grasping unknown and specially

deformed objects

3 HAPTIC CONTROL FOR

GRIPPERS IN LITERATURE

Haptic feedback is utilized in gripper systems enabling

force feedback control. The grasping sensitivity is

attained through haptic feedback. Force management

reduces the unintended damage of handled part and

gripper mechanisms. The force control decreases the

probability of unwanted slippage and increases self-

adjustability.

A force feedback control system through a

miniature load cell for a rigid 3d-printed 2-finger

gripper is proposed by (Lipina, et al., 2011). Object

manipulation was required in the circumstance of a

power failure during the extension of a robot arm. The

force of the gripper was influenced through the

changing the input current (Ampere) and the force was

measured through a miniature load cell.

A haptic control system utilizing Shape Memory

Alloys, (SMA) as a gripper actuator, is presented by

(Yan, et al., 2012). The haptic control is performed by

means of potential difference (Voltage) across micro-

deformations from Polyvinylidene Fluoride Films

PVDF), due to their piezoelectric properties. The

PVDF sensors are embedded as tactile sensors.

A tele-manipulation (master-slave operation) for a

gripper system was presented by (Park, et al., 2016) to

replace human presence at task site. The telepresence

extends human touch to the environment remotely. The

haptic sense interface utilizes Force Sensitive Resistors

(FSR) and laser distance sensors inserted in the slave

device (the gripper). The master device (remote

controller) manipulates the force feedback by means of

magnetorheological (MR) glove acting as force-

control, increasing and decreasing force commands.

4 PREVIOUS DESIGN OF

A 4-FINGER GRIPPER

4.1 Mechanical Design of Gripper

The study was conducted on a previously designed

Fin Ray Effect

based gripper that was developed by

(Basson, et al., 2017). The 4-finger gripper was

designed and based on the Fin Ray Effect

, shown in

Figure 3. The design was inspired by the FESTO

Multi Choice Gripper (FESTO, 2014). The gripper

appendage design was based on conformity studies

investigated in the design of the TIHRA gripper

(Crooks, et al., 2016).

The design was manufactured from Acrylonitrile

Butadiene Styrene, (ABS), plastic and by means of

3D printing. The mechanical properties of ABS allow

for flexibility and strength to sustain deformation

without failure. The Elastic Modulus (E) of ABS

plastic is 2 GPa, the Poisson’s Ratio (υ) is 0.4 and the

Yield Stress (σ

) is 45 MPa.

Figure 3: 4-Finger proposed gripper design (Basson, et al.,

2017).

Active Haptic Control for a Biologically Inspired Gripper in Reconﬁgurable Assembly Systems - Testing Active Haptic Control through

Force Feedback

4.2 Design and Simulation of the

Selected Appendage

The rib design for the appendage was selected from

four (4) geometries and was described by (Basson, et

al., 2017), shown in Figure 4. Geometry 1 utilized the

traditional Fin Ray Effect

concept with parallel ribs.

Geometry 2 was designed with a slanted rib structure.

Geometry 3 comprised of concentric curved ribs.

Geometry 4 possessed the rib structures of Geometry

3 and Geometry having curved and slop structures. A

Finite Element Analysis, (FEA), was performed on

the various rib structures and the conformity was

examined in relation to the Fin Ray Effect

. The

design appendages demonstrated self-conformity

with respect to rib deflection.

Figure 4: Rib structure design for appendages (Basson, et

al., 2017).

A non-linear static analysis was performed and

Geometry 4 was found to be the best-suited rib

structure, illustrated in Figure 5. A force of 10 N was

applied against the gripping face of the appendage.

The stress and deflection results from the simulation

yielded 19.84 MPa and 2.28 mm respectively. The

deflection was 29.3% larger than that of Geometry 1.

Figure 5: Deflection shape of Geometry 4 (Basson, et al.,

2017).

4.3 Gripper and Robotic Arm

Integration

The gripper system was installed onto the end-

effector attachment of a FANUC M-10iA robotic

arm. The gripper system consisted of the actuated

gripper and the force feedback sensory system. The

actuator employed was a NEMA 17 stepper motor

and was connected to stepper motor controller. Force

Sensitive Resistors, (FSR), were utilised as haptic

feedback for the gripper, shown in Figure 6. The

stepper motor controller and the sensors were linked

to an Arduino Mega 2560 microcontroller. The

gripper system was connected through a wire system

to the respective electronic components illustrated in

Figure 7.

Figure 6: Installed sensory system.

Figure 7: Frontal view of robot gripper and gripper system.

ot teac

Pendant

ontro

Board

ttac

Gripper

c arm

ICINCO 2018 - 15th International Conference on Informatics in Control, Automation and Robotics

The solution was proposed as an alternative for

traditional grippers. Flexibility is increased by selecting and

designing appendages to mimic human-like fingers in a

grasping motion. The intention of the design was to test and

manufacture a lightweight and flexible gripper for the ease

of instalment. The haptic system was implemented for

operational environments where product structural integrity

through handling would not be compromised. The gripper

actuation method using motor actuation was changed in

comparison to FESTO’s MultiChoiceGripper

, which used

pneumatic actuation. The rib structure was modified

therefore improving grasping properties from the traditional

rib design.

5 ACTIVE HAPTIC CONTROL

5.1 Pseudocode and Flow Diagram for

the Mechatronic Control

The pseudocode described the procedural layout of

the mounted gripper system and included haptic

control, shown in Figure 8. The program was initiated

and started the operation procedure. The system

located the grasping location of the object by means

of a written input code. The object was grasped with

aid of push-button control, which resembled a written

code that initiated the closing of appendages to grasp

the object. The system was verified for an accepted

grasp. The system reinitiated the grasping procedure

when the grasp was unacceptable.

Acceptable grasps resumed enclosing the gripper

appendage and exceeded a lower force threshold (A).

The lower force threshold initiated automatic closing

of the gripper until a high force threshold (B) was

attained. The gripper was programmed to open

automatically until a force threshold (C) was met. The

force threshold (C) value was located at a fraction

value below threshold (B). The variation between (B)

and (C) existed for self-adjustment just below the

force magnitude required to damage the grasped

object. The grip intensity self-regulated when

unintended grip force interferes were present in the

required force grip when experiencing dynamic

motion.

The program identified the release location. A

push button or over-riding code was programmed to

disengage self-regulating loop for the release of the

object. The program ended and started a new

operation cycle.

START

Locate Object

Grasp Object

Locate Release

Location

Push Button

For Releasing

RETURN

Low Force

Threshold (A)

High Force

Threshold (B)

Push Button

For Grasping

Force

Threshold (C)

Gripper

opening

Gripper

closing

Gripper

closing

Figure 8: Operational pseudocode for the gripping system.

The mechatronic system architecture of the

gripper system consisted of a software architecture

and a mechanical architecture, shown in Figure 9. The

gripping sequence was initiated by means of push-

button input through human involvement. The haptic

input signal from the FSR sensors was converted and

relayed to the system controller. The system

controller transmitted the signal to the stepper motor

controller and manipulated the stepper motor. The

manipulation of the actuation influenced the grip

movement direction on the gripper.

Figure 9: Logic flow diagram of haptic gripper system

architecture.

FSR Sensory

Input

Force

Threshold

Detectio n

Force Signal

Conversion

System

Contro ller

Push Buttons

Human Input

5 V Power

Supply

Stepper

Motor

Contro ller

24 V Power

Supply

Stepper

Motor

Fin Ray

Gripper

Mechatronic Archite cture

Active Haptic Control for a Biologically Inspired Gripper in Reconﬁgurable Assembly Systems - Testing Active Haptic Control through

Force Feedback

5.2 Force Feedback Control Loop

The force feedback control loop is illustrated for the

haptic control of the gripper system. Initial force input

is recorded through a push-button resembling an input

voltage. The threshold values are the required values

for the control system to regulate between the

opening and closing the gripper fingers around the

object. A constant input voltage signal was supplied

through the micro-controller and motor-controller, by

means of an external power source. The signal

required was transmitted to the actuator in the Fin Ray

gripper. The signal value was retrieved from an FSR

and relayed to be compared to the input signal. The

force output was corrected with the condition that the

output signal value was incorrect in comparison with

the input signal value. The corrected voltage value

was applied to the directional motion of the actuator.

The haptic control layout is shown in Figure 10.

Arduino

Micro-

Controller

Motor

Controller

Fin Ray

Gripper

FSR

Sensor

Force

Signal

Conversion

Measured

Force

Value

Controlled

Force

Output

Dynamic

Interference

Power

Supply

Push

Button

Input

Figure 10: Force feedback control loop.

The interference forces were produced from the

robot arm’s rotational and translational movement.

The object experiences force components which were

described by inertia forces a, centripetal forces b,

gravitational forces g and Coriolis forces c (Yang, et

al., 2016). The force vector was described by the

Lagrangian formula in Equation 1.



(



)







+

(



)









+

(



)







+

(



)

=

(1)

Where:

q: Vector of joint angles.

a(q): Symmetric, bounded, positive definite

inertia matrix.

c(q): Coriolis forces.

b(q): Centripetal forces.

g(q): Gravitational force

τ: Vector of actuator torques.

Object manipulation required control of the force

input magnitudes of the maximum grip. A control

system was conceptualized utilizing a gripper based

on the Fin Ray Effect

. The system integration

worked collectively to coincide with self-adjustment

requirements.

6 TESTING OF ACTIVE HAPTIC

CONTROL

6.1 Previous Static Testing Overview

A static mass holding test was performed on the

gripper system. The 3-finger and 4-finger gripper

configuration were tested according to gripping

repeatability. An object was grasped and the mass

was gradually increased until a maximum load of

2435 g was reached. Geometry 4 proved to be the

most effective. The system was 97.3% repeatable in

grasping the maximum object mass. The experiment

was repeated fifteen (15) times for each configuration

and rib structure to maintain empirical accuracy

(Basson, et al., 2017).

A dynamic and static qualitative gripping test was

performed on the gripper system. The 4-finger and 3-

finger gripper system was evaluated by gripping

various objects to determine effective conformity in

gripping various shapes, shown in Figure 11. The

following shapes were gripped: A sphere (A), a cube

(B), a triangular prism (C), cylindrical extrusion

screw (D) and a crazy cube with various shaped sides

(E). The 4-finger gripper performed the most

satisfactory with no slippages occurring, and the 3-

finger gripper slipping when handling 4-sided prisms.

The experiment was repeated five (5) times for each

configuration and rib structure to maintain empirical

accuracy (Basson, et al., 2017).

ICINCO 2018 - 15th International Conference on Informatics in Control, Automation and Robotics

Figure 11: Dynamic test for 4-finger gripper holding a

concentric sphere shape: A) Geometry 1, B) Geometry 2,

C) Geometry 3, and D) Geometry 4.

6.2 Dynamic Testing Preparation

A path plan program is described for the robotic arm

input. The path plan is visually described in Figure

12. The path plan describes a dynamic motion that the

end-effector follows in simulating a pick and place

procedure. The dynamic motion simulates a

controlled experimental environment and the

experiment was repeated multiple times for the same

motion.

Figure 12: Graphical representation of the robotic arm path

plan.

Signal feedback values were received from the

FSR sensors. The voltage and mass loading on the

sensor experienced a non-linear relationship, due to

the shearing of the sensor material, illustrated in

Figure 13. The calibration was conducted for all four

(4) sensors. The voltage output values varied from

one sensor to the other, as a result of the sensitivity in

shear mechanics and material thickness that varied in

each sensor.

Figure 13: Mass verse voltage calibration.

The output value program was calibrated

accordingly to produce a potential value in millivolts.

The following Equation 2 was used to calibrate the

output values:



 = ( ∗ 

)/1024 ∗ 1000

(2)

Where:

V_out: Output voltage (mV)

val: Value reading output (-)

V_in: Input voltage (5 V)

The relative error for the sensors has been

calculated for 45 readings representing 4.5 seconds

using Equation 3. The object was grasped constantly

to determine the average relative error for the Force

Sensitive Resistors incorporated into the haptic

feedback system for the gripper, shown in Figure 14.

The average relative error was determined for the

mass loading for each sensor and the expected sensor

performance is shown in Table 4.

 = 100 × (



−



)/



(3)

Where:

err: Relative error

Val

act

: Value reading

Val

exp

: Expected reading

1000

2000

3000

4000

0 500 1000

POTENTIAL DIFFERENCE (mV)

MASS (g)

Sensor Calibration: Mass vs Voltage

Mass verse Voltage

Poly. (Mass verse Voltage)

Active Haptic Control for a Biologically Inspired Gripper in Reconﬁgurable Assembly Systems - Testing Active Haptic Control through

Force Feedback

Figure 14: Relative error verse time for FSR sensor 1, 2, 3

and 4.

Table 4: Average relative error for sensor values.

Expected

mass

value (g)

Expected

Voltage

(mV)e

Average

relative error

(%)

Sensor 1

552.25 3378 -0.0003

Sensor 2

429.02 3534 -0.0043

Sensor 3

483.01 3527 -0.0020

Sensor 4

296.08 3173 0.0027

6.3 Dynamic Testing without Feedback

Control

Dynamic testing was performed to determine the

force throughout a dynamic movement without a

feedback control at a low robot speed of 250 mm/s.

The spherical specimen was used as the test piece to

maintain conformity and simultaneous contact of all

four (4) sensors. The object was gripped and cycled

through the movement described in Section 6.2. The

intended movement was described in three (3) time

lapses: A ten (10) second pause, a ten (10) second

dynamic motion and a ten (10) second pause. The

experiment was repeated five (5) times for each

configuration and rib structure to maintain empirical

accuracy.

The data values retrieved to illustrate self-

conformity of the Fin-Ray Effect

while grasping

through dynamic motion. Increased voltage

variations display the external force interference due

to the dynamic force components described in Section

3.3. The voltage verse time graph, illustrated in

Figure 15, depicted increased voltage values during

and following the dynamic motion.

An average grip force in grams was calculated to

determine a minimum holding strength. The mass of

the specimen was 320 g and the average holding force

required was 1146 g (286.5 g per appendage).

A disadvantage from the self-conformity

characteristics and high loading variations due to

force interferences is that fragile and brittle

components i.e. lightbulbs have the potential to fail

under varying force and shock loadings. A dynamic

experiment for active haptic feedback control is

required to control the force variation. The control

response is of importance as force changes occur very

rapidly.

Figure 15: Voltage verse time for 4-finger gripper:

Geometry 4 with 250 mm/s speed.

6.4 Dynamic Testing of Active Haptic

Feedback Control

Dynamic testing was performed to determine the

force throughout a dynamic movement utilizing an

active haptic control at a high robot speed of 2000

mm/s. The spherical specimen was used as the test

piece to maintain conformity and simultaneous

contact od fall four (4) sensors. Identical path

planning, estimated time lapses and test runs were

employed that were used in the experiment.

The data values illustrated force control for high-

speed applications, shown in Figure 16. The force

interference was minimized and force increased, due

to self-conformity, was reduced. High signal spikes

were still present as result of noise from the

environment, voltage imbalances from ineffective

material shearing and impaired actuation response.

-3,0

-2,0

-1,0

0,0

1,0

2,0

02040

Realtive error (%)

Deci-seconds (0.1 s)

Relative Error vs Time

Sensor 1 Sensor 2 Sensor 3 Sensor 4

2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

0 100 200 300

Potential Difference (mV)

Deci-seconds (0.1 s)

Voltage vs Time

Sensor 1 Sensor 2 Sensor 3 Sensor 4

ICINCO 2018 - 15th International Conference on Informatics in Control, Automation and Robotics

Figure 16: Voltage verse time for 4-finger gripper:

Geometry 4 with 2000 mm/s speed.

The threshold values for the force control are as

follows: Low threshold value (A) was at 977 mV, the

high threshold value (B) was at 3418 (mV) and the

threshold value (C) was at 3345 (mV). The high value

indicated the critical damage value for fragile objects.

The input signal for value (B) is influenced according

to the type of delicate objects that are gripped. The

experiment was repeated five (5) times. Results

illustrated actuation response to force input values to

sensors. Signal values overcoming threshold values

were countered through the opening of the gripper

fingers to reduce high force loading on contact

surfaces.

7 CONCLUSIONS

The paper analysed a haptic feedback control for a

biologically inspired gripper. The gripper was

designed and developed based on the Fin Ray Effect

The study reviewed conformity characteristic

regarding stress and deflection performed through an

FEA simulation. A haptic feedback control flow

diagram describes the force regulation through

actuation of the gripper. Repeatability of the gripper

was determined through static testing that was

performed in previous studies. The gripper was tested

to verify conformity for grasping of different shapes

in prior investigations. The 4-finger gripper utilizing

Geometry 4 was established to be the preferred

combination.

A dynamic test was performed on the gripper

utilizing force feedback with and without active

haptic control. Testing without active feedback was

performed in prior studies and illustrated force

variation and self-conformity due to dynamic

interferences. High force impulses can potentially

damage fragile components and as a result, an active

haptic feedback control system was required. The

system was tested at lower operational speeds to

emphasise that force fluctuations have involved that

exhibit the potential to damage handled components.

The system was tested employing an active haptic

feedback control and high operational speeds were

exercised in the experiment. The results showed the

force before and after the dynamic motion was

stabilized, but high force impulses were visible

during the movement due to force interferences.

A dynamic test was performed on the gripper

utilizing force feedback with and without active

haptic control. Testing without active feedback was

performed in prior studies and illustrated force

variation and self-conformity due to dynamic

interferences. High force impulses can potentially

damage fragile components and as a result, an active

haptic feedback control system was required. The

system was tested at lower operational speeds to

emphasise that force fluctuations have involved that

exhibit the potential to damage handled components.

The system requires a faster response to force

variation. Force impulses can be minimized by

increased motor speed for opening and closing and

reducing signal noise. The type of sensor used also

affect the sensitivity of the results and higher ranged

force sensors should be used with higher accuracies.

The biologically inspired gripper system with

active haptic control has the potential to be

implemented in production application where

handling of fragile objects is performed. Typical

objects that could be gripped and manipulated in this

investigation are glass components i.e. light bulbs,

fragile foods i.e. eggs, etc.

Haptic feedback control possesses drawbacks

pertaining to environment interaction. Actuator

response to environment requires to be rapid when an

impact occurs. High force impact loading was

observed and as a result affects the control of the

gripper system negatively.

ACKNOWLEDGEMENTS

The authors wish to thank the “Blue Sky Research

Grant” under the grant number 91339.

2700

2900

3100

3300

3500

3700

3900

0 100 200 300

Potential Difference (mV)

Deci-seconds (0.1 s)

Voltage vs Time

Sensor 1 Sensor 2 Sensor 3 Sensor 4

Active Haptic Control for a Biologically Inspired Gripper in Reconﬁgurable Assembly Systems - Testing Active Haptic Control through

Force Feedback

In addition, acknowledgement is given to the

National Research Foundation (NRF) towards this

research.

Opinions expressed and conclusions arrived at,

are those of the authors and not necessarily to be

attributed to the NRF.

The authors’ special thanks are extended to the

staff of UKZN for the opportunity to present their

work.

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