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Table 1. Distance coverage and duration from point to point
Distance Time start Time finish Duration
(m) Move-base RRT Move-base RRT Move-base RRT
Origin to Point 1 13.3 1 m 44 sec 0.00 2 m 50 sec 56 sec 1 m 6 sec 56 sec
Point 1 to Point 2 4.5 2 m 51 sec 56 sec 3 m 40 sec 1 min 27 sec 49 sec 30 sec
Point 2 to Point 3 7.9 3 m 41 sec 1 min 28 sec 4 m 20 sec 4 min 22 sec 39 sec 2 min 54 sec
Point 3 to Point 4 5.0 4 m 21 sec 4 min 23 sec 5 m 6 min 57 sec 39 sec 2 min 34 sec
Point 4 to Point 5 10.3 5 m 01 sec 6 min 58 sec 5 m 42 sec 8 min 6 sec 41 sec 2 min 8 sec
Point 5 to Point 6 7.2 5 m 43 sec 8 min 7 sec 6 min 16 sec 8 min 30 sec 33 sec 23 ec
4. Conclusion
This project highlights the capability of a path planning algorithm to navigate in a duct environment
successfully. The proposed algorithm is evaluated based on a duct environment using the Rviz simulator.
Further improvement on the distance and duration using other algorithms is planned.
Acknowledgments
The authors want to acknowledge the Ministry of Higher Education Malaysia and University Kebangsaan
Malaysia for funding and supporting this project using grant code FRGS/1/2020/ICT02/UKM/02/7.
References
Bircher, A., Kamel, M., Alexis, K., Oleynikova, H., & Siegwart, R. (2016, May). Receding horizon" nextbest-
view" planner for 3d exploration. In 2016 IEEE international conference on robotics and automation (ICRA)
(pp. 1462-1468). IEEE.
Chataigner F. et al., “ARSI: An Aerial Robot for Sewer Inspection,” Springer Tracts in Advanced Robotics,
vol. 132, pp. 249–274, 2020, doi: 10.1007/978-3-030-22327-4_12.
Grisetti, G., Stachniss, C., & Burgard, W. (2007). Improved techniques for grid mapping with
raoblackwellized particle filters. IEEE transactions on Robotics, 23(1), 34-46.
Zhang, H., Wang, Y., Zheng, J., & Yu, J. (2018). Path planning of industrial robot based on improved RRT
algorithm in complex environments. IEEE Access, 6, 53296-53306.
Koledoye M. A., D. De Martini, M. Carvani, and T. Facchinetti, “Design of a mobile robot for air ducts
exploration,” Robotics, vol. 6, no. 4, p. 26, 2017, doi: 10.3390/robotics6040026.
Senarathne, P. G. C. N., Wang, D., Wang, Z., & Chen, Q. (2013, May). Efficient frontier detection and
management for robot exploration. In 2013 IEEE International Conference on Cyber Technology in
Automation, Control and Intelligent Systems (pp. 114-119). IEEE.
Varnell, P., Mukhopadhyay, S., & Zhang, F. (2016, December). Discretized boundary methods for computing
smallest forward invariant sets. In 2016 IEEE 55th Conference on Decision and Control (CDC) (pp.
65186524). IEEE.
Wang, Y., Liang, A., & Guan, H. (2011, April). Frontier-based multi-robot map exploration using particle
swarm optimization. In 2011 IEEE symposium on Swarm intelligence (pp. 1-6). IEEE.
E- Proceedings of The 5th International Multi-Conference on Artificial Intelligence Technology (MCAIT 2021) [229]
Artificial Intelligence in the 4th Industrial Revolution