Sklar, Elizabeth and Sareh, Sina and Secco, Emanuele Lindo and Faragasso, Angela and Althoefer, Kaspar (2016) A non-linear Model for Predicting Tip Position of a Pliable Robot Arm Segment Using Bending Sensor Data. Sensors & Transducers - Special Issue on Soft Bio-sensing Technologies, 199 (4). pp. 52-61. ISSN 2306-8515 (Accepted for Publication)
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Abstract
Using pliable materials for the construction of robot bodies presents new and interesting challenges for
the robotics community. Within the EU project entitled STIFFness controllable Flexible & Learnable manipulator
for surgical Operations (STIFF-FLOP), a bendable, segmented robot arm has been developed. The exterior of the
arm is composed of a soft material (silicone), encasing an internal structure that contains air-chamber actuators
and a variety of sensors for monitoring applied force, position and shape of the arm as it bends. Due to the physical
characteristics of the arm, a proper model of robot kinematics and dynamics is difficult to infer from the sensor
data. Here we propose a non-linear approach to predicting the robot arm posture, by training a feed-forward neural
network with a structured series of pressures values applied to the arm's actuators. The model is developed across
a set of seven different experiments. Because the STIFF-FLOP arm is intended for use in surgical procedures,
traditional methods for position estimation (based on visual information or electromagnetic tracking) will not be
possible to implement. Thus the ability to estimate pose based on data from a custom fiber-optic bending
sensor and accompanying model is a valuable contribution. Results are presented which demonstrate the utility of
our non-linear modelling approach across a range of data collection procedures.
| Item Type: | Article |
|---|---|
| Additional Information and Comments: | Full citation: Elizabeth I. SKLAR, Sina SAREH, Emanuele L. SECCO, et all, 'A Non-linear Model for Predicting Tip Position of a Pliable Robot Arm Segment Using Bending Sensor Data', Sensors & Transducers, Vol. 199, Issue 4, April 2016, pp. 52-61, http://www.sensorsportal.com/HTML/DIGEST/P_2815.htm |
| Faculty / Department: | Faculty of Human and Digital Sciences > Mathematics and Computer Science |
| Depositing User: | Emanuele Secco |
| Date Deposited: | 12 May 2016 10:39 |
| Last Modified: | 01 Dec 2017 14:03 |
| URI: | https://hira.hope.ac.uk/id/eprint/1253 |
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