Abstract
Inefficient navigation capability in dynamic agricultural field limits the application of agricultural robot in the field. Probabilistic roadmap however has the robustness for outdoor navigation. A path planning algorithm was established upon an enhanced probabilistic roadmap and this was implemented in a virtual greenhouse environment. A smoothing algorithm for the robot’s navigation has been proposed to improve the existing algorithm in producing an optimal path. A simulation was conducted using a crop inspection mobile robot and tested with suitable turning trajectories for lane changing. Several trajectories were initiated and compared based on travel time, distance and controller error in order to choose the best trajectories for crop inspection. The proposed smoothing algorithm was able to smooth out the initial paths in order to create an optimal path for the robot with error less than 0.1 m.
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Acknowledgements
The authors are grateful to the Universiti Teknologi Malaysia and the Ministry of Higher Education (MOHE) for their partial financial support through their research fund, Vote no. R.J130000.7823.4F759 entitled ‘A Study on Adaptive Control Strategies for Infiltration Process in Fibrous-capillary System for Precision Water-saving Agriculture’.
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Mahmud, M.S.A., Zainal Abidin, M.S., Mohamed, Z., Abd Rahman, M.K.I., Buyamin, S. (2017). Enhanced Probabilistic Roadmap for Robot Navigation in Virtual Greenhouse Environment. In: Mohamed Ali, M., Wahid, H., Mohd Subha, N., Sahlan, S., Md. Yunus, M., Wahap, A. (eds) Modeling, Design and Simulation of Systems. AsiaSim 2017. Communications in Computer and Information Science, vol 752. Springer, Singapore. https://doi.org/10.1007/978-981-10-6502-6_15
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DOI: https://doi.org/10.1007/978-981-10-6502-6_15
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