TY  - CONF
KW  - Artificial intelligence; Manufacture; Mobile robots; Motion planning; Robot programming; Robotics; Robots
KW  -  Ant Colony Optimization (ACO); Robot path-planning; Static obstacles
KW  -  Ant colony optimization
TI  - Mobile robot path planning using Ant Colony Optimization
ID  - scholars8845
N1  - cited By 44; Conference of 2nd IEEE International Symposium on Robotics and Manufacturing Automation, ROMA 2016 ; Conference Date: 25 September 2016 Through 27 September 2016; Conference Code:126431
N2  - Ant colony optimization (ACO) technique is proposed to solve the mobile robot path planning (MRPP) problem. In order to demonstrate the effectiveness of ACO in solving the MRPP problem, several maps of varying complexity used by an earlier researcher is used for evaluation. Each map consists of static obstacles in different arrangements. Besides that, each map has a grid representation with an equal number of rows and columns. The performance of the proposed ACO is tested on a given set of maps. Overall, the results demonstrate the effectiveness of the proposed approach for path planning. © 2016 IEEE.
AV  - none
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015962268&doi=10.1109%2fROMA.2016.7847836&partnerID=40&md5=bda25be6f6d2162eb028ffe7718cf325
A1  - Rashid, R.
A1  - Perumal, N.
A1  - Elamvazuthi, I.
A1  - Tageldeen, M.K.
A1  - Khan, M.K.A.A.
A1  - Parasuraman, S.
SN  - 9781509009282
PB  - Institute of Electrical and Electronics Engineers Inc.
Y1  - 2017///
ER  -