Publications
Selected journal and conference publications in robotic perception, agricultural robotics, and vision-based navigation.
Journal Articles
Published in IEEE Robotics and Automation Letters, 2025
Semantic enrichment of keypoint descriptors for more reliable matching and localization in outdoor agricultural environments.
Recommended citation: de Silva, R., Swindell, J., Cox, J., Popovic, M., Cadena, C., Stachniss, C., & Polvara, R. (2025). "Keypoint Semantic Integration for Improved Feature Matching in Outdoor Agricultural Environments." IEEE Robotics and Automation Letters, 10(12), 13383-13390.
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Published in Computers and Electronics in Agriculture, 2024
Vision-based navigation in arable fields under challenging conditions such as shadows, weeds, discontinuities, and growth variation.
Recommended citation: de Silva, R., Cielniak, G., & Gao, J. (2024). "Vision based crop row navigation under varying field conditions in arable fields." Computers and Electronics in Agriculture, 217, 108581.
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Published in Journal of Field Robotics, 2023
A deep learning approach to crop-row perception for robust visual navigation in arable fields.
Recommended citation: de Silva, R., Cielniak, G., Wang, G., & Gao, J. (2023). "Deep learning-based crop row detection for infield navigation of agri-robots." Journal of Field Robotics, 41(7), 2299-2321.
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Conference Papers
Published in TIG-IV Workshop at ICRA 2023, 2023
A vision-based method for exiting crop rows and transitioning into the headland area.
Recommended citation: de Silva, R., Cielniak, G., & Gao, J. (2023). "Leaving the Lines Behind: Vision-Based Crop Row Exit for Agricultural Robot Navigation." TIG-IV Workshop at ICRA 2023. Best Paper Award.
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Published in IEEE International Conference on Automation Science and Engineering (CASE), 2022
Using simulated data to reduce labelled real-world data requirements for robust crop-row detection.
Recommended citation: de Silva, R., Cielniak, G., & Gao, J. (2022). "Towards Infield Navigation: leveraging simulated data for crop row detection." IEEE International Conference on Automation Science and Engineering (CASE).
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