Obstacle avoidance for a robotic navigation aid using Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA)
Robotic Navigation Aids (RNAs) assist visually impaired individuals in independent navigation. However, existing research overlooks diverse obstacles and assumes equal responsibility for collision avoidance among intelligent entities. To address this, we propose Fuzzy Logic Controller-Optimal Recipr...
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ftiislamicuniv:oai:generic.eprints.org:106206 2023-12-03T10:28:36+01:00 Obstacle avoidance for a robotic navigation aid using Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA) Mohd Romlay, Muhammad Rabani Mohd Ibrahim, Azhar Toha, Siti Fauziah De Wilde, Philippe Venkat, Ibrahim Ahmad, Muhammad Syahmi 2023-08-10 application/pdf http://irep.iium.edu.my/106206/ http://irep.iium.edu.my/106206/1/106206_Obstacle%20avoidance%20for%20a%20robotic%20navigation.pdf http://irep.iium.edu.my/106206/13/106206_Obstacle%20avoidance%20for%20a%20robotic%20navigation_Scopus.pdf https://link.springer.com/article/10.1007/s00521-023-08856-8 en eng Springer Nature http://irep.iium.edu.my/106206/1/106206_Obstacle%20avoidance%20for%20a%20robotic%20navigation.pdf http://irep.iium.edu.my/106206/13/106206_Obstacle%20avoidance%20for%20a%20robotic%20navigation_Scopus.pdf Mohd Romlay, Muhammad Rabani and Mohd Ibrahim, Azhar and Toha, Siti Fauziah and De Wilde, Philippe and Venkat, Ibrahim and Ahmad, Muhammad Syahmi (2023) Obstacle avoidance for a robotic navigation aid using Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA). Neural Computing and Applications, 35 (30). pp. 22405-22429. ISSN 0941-0643 E-ISSN 1433-3058 T Technology (General) Article PeerReviewed 2023 ftiislamicuniv 2023-11-07T18:48:45Z Robotic Navigation Aids (RNAs) assist visually impaired individuals in independent navigation. However, existing research overlooks diverse obstacles and assumes equal responsibility for collision avoidance among intelligent entities. To address this, we propose Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA). Our FLC-ORCA method assigns responsibility for collision avoidance and predicts the velocity of obstacles using a LiDAR-based mobile robot. We conduct experiments in the presence of static, dynamic, and intelligent entities, recording navigation paths, time taken, angle changes, and rerouting occurrences. The results demonstrate that the proposed FLC-ORCA successfully avoids collisions among objects with different collision avoidance protocols and varying liabilities in circumventing obstacles. Comparative analysis reveals that FLC-ORCA outperforms other state-of-the-art methods such as Improved A* and Directional Optimal Reciprocal Collision Avoidance (DORCA). It reduces the overall time taken to complete navigation by 16% and achieves the shortest completion time of 1 min and 38 s, with minimal rerouting (1 occurrence) and the smallest angle change (12). Our proposed FLC-ORCA challenges assumptions of equal responsibility and enables collision avoidance without pairwise manoeuvres. This approach significantly enhances obstacle avoidance, ensuring safer and more efficient robotic navigation for visually impaired individuals. Article in Journal/Newspaper Orca IIUM Repository (IRep - International Islamic University Malaysia) |
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T Technology (General) Mohd Romlay, Muhammad Rabani Mohd Ibrahim, Azhar Toha, Siti Fauziah De Wilde, Philippe Venkat, Ibrahim Ahmad, Muhammad Syahmi Obstacle avoidance for a robotic navigation aid using Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA) |
topic_facet |
T Technology (General) |
description |
Robotic Navigation Aids (RNAs) assist visually impaired individuals in independent navigation. However, existing research overlooks diverse obstacles and assumes equal responsibility for collision avoidance among intelligent entities. To address this, we propose Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA). Our FLC-ORCA method assigns responsibility for collision avoidance and predicts the velocity of obstacles using a LiDAR-based mobile robot. We conduct experiments in the presence of static, dynamic, and intelligent entities, recording navigation paths, time taken, angle changes, and rerouting occurrences. The results demonstrate that the proposed FLC-ORCA successfully avoids collisions among objects with different collision avoidance protocols and varying liabilities in circumventing obstacles. Comparative analysis reveals that FLC-ORCA outperforms other state-of-the-art methods such as Improved A* and Directional Optimal Reciprocal Collision Avoidance (DORCA). It reduces the overall time taken to complete navigation by 16% and achieves the shortest completion time of 1 min and 38 s, with minimal rerouting (1 occurrence) and the smallest angle change (12). Our proposed FLC-ORCA challenges assumptions of equal responsibility and enables collision avoidance without pairwise manoeuvres. This approach significantly enhances obstacle avoidance, ensuring safer and more efficient robotic navigation for visually impaired individuals. |
format |
Article in Journal/Newspaper |
author |
Mohd Romlay, Muhammad Rabani Mohd Ibrahim, Azhar Toha, Siti Fauziah De Wilde, Philippe Venkat, Ibrahim Ahmad, Muhammad Syahmi |
author_facet |
Mohd Romlay, Muhammad Rabani Mohd Ibrahim, Azhar Toha, Siti Fauziah De Wilde, Philippe Venkat, Ibrahim Ahmad, Muhammad Syahmi |
author_sort |
Mohd Romlay, Muhammad Rabani |
title |
Obstacle avoidance for a robotic navigation aid using Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA) |
title_short |
Obstacle avoidance for a robotic navigation aid using Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA) |
title_full |
Obstacle avoidance for a robotic navigation aid using Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA) |
title_fullStr |
Obstacle avoidance for a robotic navigation aid using Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA) |
title_full_unstemmed |
Obstacle avoidance for a robotic navigation aid using Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA) |
title_sort |
obstacle avoidance for a robotic navigation aid using fuzzy logic controller-optimal reciprocal collision avoidance (flc-orca) |
publisher |
Springer Nature |
publishDate |
2023 |
url |
http://irep.iium.edu.my/106206/ http://irep.iium.edu.my/106206/1/106206_Obstacle%20avoidance%20for%20a%20robotic%20navigation.pdf http://irep.iium.edu.my/106206/13/106206_Obstacle%20avoidance%20for%20a%20robotic%20navigation_Scopus.pdf https://link.springer.com/article/10.1007/s00521-023-08856-8 |
genre |
Orca |
genre_facet |
Orca |
op_relation |
http://irep.iium.edu.my/106206/1/106206_Obstacle%20avoidance%20for%20a%20robotic%20navigation.pdf http://irep.iium.edu.my/106206/13/106206_Obstacle%20avoidance%20for%20a%20robotic%20navigation_Scopus.pdf Mohd Romlay, Muhammad Rabani and Mohd Ibrahim, Azhar and Toha, Siti Fauziah and De Wilde, Philippe and Venkat, Ibrahim and Ahmad, Muhammad Syahmi (2023) Obstacle avoidance for a robotic navigation aid using Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA). Neural Computing and Applications, 35 (30). pp. 22405-22429. ISSN 0941-0643 E-ISSN 1433-3058 |
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1784253360135733248 |