Drug Delivery Based on Swarm Microrobots
Journal article
Authors/Editors
Strategic Research Themes
No matching items found.
Publication Details
Author list: Banharnsakun A., Achalakul T., Batra R.C.
Publisher: World Scientific Publishing
Publication year: 2016
Journal: International Journal of Computational Intelligence and Applications (1469-0268)
Volume number: 15
Issue number: 2
ISSN: 1469-0268
eISSN: 1757-5885
Languages: English-Great Britain (EN-GB)
View in Web of Science | View on publisher site | View citing articles in Web of Science
Abstract
Advances in the development of technology have led to microrobots applications in medical fields. Drug delivery is one of these applications in which microrobots deliver a pharmaceutical compound to targeted cells. Chemotherapy and its side effects can then be minimized by this method. Two major constraints, however, must be considered: the robot's onboard energy supply and the time needed for drug delivery. Furthermore, a microrobot must avoid biological restricted areas which we treat as obstacles in the path. The main objectives of this work were to find optimal paths to targeted cells and avoid collision with obstacles in the paths under a dynamic environment. In this study, we controlled motion of microrobots based on the concept of swarm intelligence. Artificial Bee Colony (ABC), the Best-so-far ABC, and the Particle Swarm Optimization (PSO) methods were employed to implement the collision detection and the boundary distance detection modules. Forces that drove or resisted blood flow as well as pressure in blood vessels were considered to approximate the effects of the environment on the microrobots. Numerical experiments were conducted using various obstacle environments. The results confirm that the proposed approaches were successful in avoiding obstacles and optimizing the energy consumption used to reach the target. ฉ 2016 World Scientific Publishing Europe Ltd.
Keywords
Best-so-far ABC, Micro robots, Target Finding and Obstacle Avoiding
Contact Information