Indoor global path planning based on critical cells using dijkstra algorithm
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| date | 2015-09-28 08:53:32 |
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| id | 12351 |
| institution | UniSZA |
| internalnotes | [1] Kala, R., Shukla, A., & Tiwari, R. (2009, November). Robotic path planning using multi neuron heuristic [2] search. In Proceedings of the 2nd [3] International Conference on Interaction Sciences: Information Technology, Culture and Human (pp. 1318-1323). ACM. [4] Dijkstra, E. W. (1959). A note on two problems in connexion with graphs.Numerische mathematik, 1(1), 269-271. [5] Mansouri, M., Shoorehdeli, M. A., & Teshnehlab, M. (2008, October). Path planning of mobile robot using integer ga with considering terrain conditions. InSystems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on (pp. 208-213). IEEE. [6] Ismail, A. T., Sheta, A., & Al-Weshah, M. (2008). A mobile robot path planning using genetic algorithm in static environment. Journal of Computer Science,4(4), 341. [7] Soofiyani, F. R., Rahmani, A. M., & Mohsenzadeh, M. (2010, July). A Straight Moving Path Planner for Mobile Robots in Static Environments Using Cellular Automata. In Computational Intelligence, Communication Systems and Networks (CICSyN), 2010 Second International Conference on (pp. 67-71). IEEE. [8] Ying-hua, X., & Hong-peng, L. (2010, May). Optimal Path Planning for Service Robot in Indoor Environment. In Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on (Vol. 2, pp. 850-853). IEEE. [9] Ahmed, S. U., Malik, U. A., Iqbal, K. F., Ayaz, Y., & Kunwar, F. (2011, August). Sparsed potential-PCNN for real time path planning and indoor navigation scheme for mobile robots. In Mechatronics and Automation (ICMA), 2011 International Conference on (pp. 1729-1734). IEEE. [10] Jin, X. B. (2013, August). Fusion Estimation Based on UKF for Indoor RFID Tracking. In Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing (pp. 1928-1931). IEEE. [11] Reza, A. W., Geok, T. K., & Dimyati, K. (2011). Tracking via square grid of RFID reader positioning and diffusion algorithm. Wireless Personal Communications, 61(1), 227-250. [12] Hongling, H., & Fenglei, Y. (2010, November). Path Planning of an Indoor Mobile Robot Navigated by Infrared. In E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on (pp. 1-4). IEEE. Hongling, H., & Fenglei, Y. (2010, November). Path Planning of an Indoor Mobile Robot Navigated by Infrared. In E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on (pp. 1-4). IEEE |
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| spelling | 12351 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=12351 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Article Journal UniSZA Unisza unisza image/jpeg inches 96 96 1419 789 1419x789 30 30 2015-09-28 08:53:32 6651-01-FH02-FIK-15-03800.jpg UniSZA Private Access Indoor global path planning based on critical cells using dijkstra algorithm Journal of Theoretical and Applied Information Technology Path planning has been implemented in various robotics systems, and the results checked. This paper proposes global path planning based on grids representation in an indoor environment using Dijkstra algorithm. The algorithm uses floor plan of any environment discretized to some equal-sized square grids. Cells that contained doorways, corner, curve and junction are considered as critical cells. These critical cells are used as the vertices to the Dijkstra algorithm, with distances between two successive cells as edges between them, and the shortest path between a set of predefined points within the terrain can then be calculated. Simulations results show that the proposed algorithm enhances performance and speed compared to the traditional Dijkstra’s algorithm. 79 1 Asian Research Publishing Network Asian Research Publishing Network 115-121 [1] Kala, R., Shukla, A., & Tiwari, R. (2009, November). Robotic path planning using multi neuron heuristic [2] search. In Proceedings of the 2nd [3] International Conference on Interaction Sciences: Information Technology, Culture and Human (pp. 1318-1323). ACM. [4] Dijkstra, E. W. (1959). A note on two problems in connexion with graphs.Numerische mathematik, 1(1), 269-271. [5] Mansouri, M., Shoorehdeli, M. A., & Teshnehlab, M. (2008, October). Path planning of mobile robot using integer ga with considering terrain conditions. InSystems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on (pp. 208-213). IEEE. [6] Ismail, A. T., Sheta, A., & Al-Weshah, M. (2008). A mobile robot path planning using genetic algorithm in static environment. Journal of Computer Science,4(4), 341. [7] Soofiyani, F. R., Rahmani, A. M., & Mohsenzadeh, M. (2010, July). A Straight Moving Path Planner for Mobile Robots in Static Environments Using Cellular Automata. In Computational Intelligence, Communication Systems and Networks (CICSyN), 2010 Second International Conference on (pp. 67-71). IEEE. [8] Ying-hua, X., & Hong-peng, L. (2010, May). Optimal Path Planning for Service Robot in Indoor Environment. In Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on (Vol. 2, pp. 850-853). IEEE. [9] Ahmed, S. U., Malik, U. A., Iqbal, K. F., Ayaz, Y., & Kunwar, F. (2011, August). Sparsed potential-PCNN for real time path planning and indoor navigation scheme for mobile robots. In Mechatronics and Automation (ICMA), 2011 International Conference on (pp. 1729-1734). IEEE. [10] Jin, X. B. (2013, August). Fusion Estimation Based on UKF for Indoor RFID Tracking. In Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing (pp. 1928-1931). IEEE. [11] Reza, A. W., Geok, T. K., & Dimyati, K. (2011). Tracking via square grid of RFID reader positioning and diffusion algorithm. Wireless Personal Communications, 61(1), 227-250. [12] Hongling, H., & Fenglei, Y. (2010, November). Path Planning of an Indoor Mobile Robot Navigated by Infrared. In E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on (pp. 1-4). IEEE. Hongling, H., & Fenglei, Y. (2010, November). Path Planning of an Indoor Mobile Robot Navigated by Infrared. In E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on (pp. 1-4). IEEE |
| spellingShingle | Indoor global path planning based on critical cells using dijkstra algorithm |
| summary | Path planning has been implemented in various robotics systems, and the results checked. This paper proposes global path planning based on grids representation in an indoor environment using Dijkstra algorithm. The algorithm uses floor plan of any environment discretized to some equal-sized square grids. Cells that contained doorways, corner, curve and junction are considered as critical cells. These critical cells are used as the vertices to the Dijkstra algorithm, with distances between two successive cells as edges between them, and the shortest path between a set of predefined points within the terrain can then be calculated. Simulations results show that the proposed algorithm enhances performance and speed compared to the traditional Dijkstra’s algorithm. |
| title | Indoor global path planning based on critical cells using dijkstra algorithm |
| title_full | Indoor global path planning based on critical cells using dijkstra algorithm |
| title_fullStr | Indoor global path planning based on critical cells using dijkstra algorithm |
| title_full_unstemmed | Indoor global path planning based on critical cells using dijkstra algorithm |
| title_short | Indoor global path planning based on critical cells using dijkstra algorithm |
| title_sort | indoor global path planning based on critical cells using dijkstra algorithm |