Hardware Implementation of Compact Genetic Algorithm for Robot Path Planning in Globally Static Environment in 8-bit Microcontroller. / Ali, Mian; Farooq, Omer ; Khan, Muhammd H. D ; Haxha, Shyqyri.

2019. 242-247 Paper presented at Proceedings The 5th International Conference on Information Management, Cambridge, United Kingdom.

Research output: Contribution to conferencePaper

E-pub ahead of print

Standard

Hardware Implementation of Compact Genetic Algorithm for Robot Path Planning in Globally Static Environment in 8-bit Microcontroller. / Ali, Mian; Farooq, Omer ; Khan, Muhammd H. D ; Haxha, Shyqyri.

2019. 242-247 Paper presented at Proceedings The 5th International Conference on Information Management, Cambridge, United Kingdom.

Research output: Contribution to conferencePaper

Harvard

Ali, M, Farooq, O, Khan, MHD & Haxha, S 2019, 'Hardware Implementation of Compact Genetic Algorithm for Robot Path Planning in Globally Static Environment in 8-bit Microcontroller', Paper presented at Proceedings The 5th International Conference on Information Management, Cambridge, United Kingdom, 24/03/19 - 27/03/19 pp. 242-247. https://doi.org/10.1109/INFOMAN.2019.8714672

APA

Ali, M., Farooq, O., Khan, M. H. D., & Haxha, S. (2019). Hardware Implementation of Compact Genetic Algorithm for Robot Path Planning in Globally Static Environment in 8-bit Microcontroller. 242-247. Paper presented at Proceedings The 5th International Conference on Information Management, Cambridge, United Kingdom. https://doi.org/10.1109/INFOMAN.2019.8714672

Vancouver

Ali M, Farooq O, Khan MHD, Haxha S. Hardware Implementation of Compact Genetic Algorithm for Robot Path Planning in Globally Static Environment in 8-bit Microcontroller. 2019. Paper presented at Proceedings The 5th International Conference on Information Management, Cambridge, United Kingdom. https://doi.org/10.1109/INFOMAN.2019.8714672

Author

Ali, Mian ; Farooq, Omer ; Khan, Muhammd H. D ; Haxha, Shyqyri. / Hardware Implementation of Compact Genetic Algorithm for Robot Path Planning in Globally Static Environment in 8-bit Microcontroller. Paper presented at Proceedings The 5th International Conference on Information Management, Cambridge, United Kingdom.6 p.

BibTeX

@conference{cbc6d395a9814658aa76521a8a6fff77,
title = "Hardware Implementation of Compact Genetic Algorithm for Robot Path Planning in Globally Static Environment in 8-bit Microcontroller",
abstract = "In this paper, hardware implementation of genetic algorithm for Robot path planning in Globally static Environment is presented. Genetic algorithm is modified and implemented in 8-bit Microcontroller (MCU) PIC18F452. Thegenetic algorithm is designed to decrease number of iteration and processing power by using predefined priorities for parent/ initial path generation rather than creating parent paths randomly. The unmanned ground vehicle (UGV) is designed which receives starting node, final destination and obstacles wirelessly, it then create multiple parent paths by using different priorities, cross over to create new child paths, uses distance as fitness function for determining Optimal or shortest path while avoiding the obstacles and uses stepper motors with three- dimensional movements to reach its destination. The environment is 5x5 static Grid Map in which obstacles are known before path planning. The MCU determines optimal path with no obstacles and require minimum distance to reach its destination.",
keywords = "Genetic algorithms, Artificial Intelligence",
author = "Mian Ali and Omer Farooq and Khan, {Muhammd H. D} and Shyqyri Haxha",
year = "2019",
month = may,
day = "16",
doi = "10.1109/INFOMAN.2019.8714672",
language = "English",
pages = "242--247",
note = "Proceedings The 5th International Conference on Information Management : ICIM 2019 conference Proceedings (IEEE), ICIM2019 March 24-27, 2019 ; Conference date: 24-03-2019 Through 27-03-2019",
url = "http://www.icim.org/",

}

RIS

TY - CONF

T1 - Hardware Implementation of Compact Genetic Algorithm for Robot Path Planning in Globally Static Environment in 8-bit Microcontroller

AU - Ali, Mian

AU - Farooq, Omer

AU - Khan, Muhammd H. D

AU - Haxha, Shyqyri

N1 - Conference code: 5

PY - 2019/5/16

Y1 - 2019/5/16

N2 - In this paper, hardware implementation of genetic algorithm for Robot path planning in Globally static Environment is presented. Genetic algorithm is modified and implemented in 8-bit Microcontroller (MCU) PIC18F452. Thegenetic algorithm is designed to decrease number of iteration and processing power by using predefined priorities for parent/ initial path generation rather than creating parent paths randomly. The unmanned ground vehicle (UGV) is designed which receives starting node, final destination and obstacles wirelessly, it then create multiple parent paths by using different priorities, cross over to create new child paths, uses distance as fitness function for determining Optimal or shortest path while avoiding the obstacles and uses stepper motors with three- dimensional movements to reach its destination. The environment is 5x5 static Grid Map in which obstacles are known before path planning. The MCU determines optimal path with no obstacles and require minimum distance to reach its destination.

AB - In this paper, hardware implementation of genetic algorithm for Robot path planning in Globally static Environment is presented. Genetic algorithm is modified and implemented in 8-bit Microcontroller (MCU) PIC18F452. Thegenetic algorithm is designed to decrease number of iteration and processing power by using predefined priorities for parent/ initial path generation rather than creating parent paths randomly. The unmanned ground vehicle (UGV) is designed which receives starting node, final destination and obstacles wirelessly, it then create multiple parent paths by using different priorities, cross over to create new child paths, uses distance as fitness function for determining Optimal or shortest path while avoiding the obstacles and uses stepper motors with three- dimensional movements to reach its destination. The environment is 5x5 static Grid Map in which obstacles are known before path planning. The MCU determines optimal path with no obstacles and require minimum distance to reach its destination.

KW - Genetic algorithms

KW - Artificial Intelligence

U2 - 10.1109/INFOMAN.2019.8714672

DO - 10.1109/INFOMAN.2019.8714672

M3 - Paper

SP - 242

EP - 247

T2 - Proceedings The 5th International Conference on Information Management

Y2 - 24 March 2019 through 27 March 2019

ER -