Richard Bucknall

University College London

Papers

4

Total Citations

60

H-Index

3

About

Dr. Richard Bucknall is a leading researcher in autonomous maritime and multi-robot systems, with a focus on unmanned surface vehicles (USVs) and intelligent task allocation. His work bridges the gap between theoretical motion planning and real-world deployment, particularly in challenging environments. His most impactful contribution, "A Fully-Autonomous Framework of Unmanned Surface Vehicles in Maritime Environments Using Gaussian Process Motion Planning" (2022, 25 citations), provides a robust framework for USV autonomy in complex maritime settings. He further advances the field with "An End-to-End Deep Reinforcement Learning Based Modular Task Allocation Framework for Autonomous Mobile Systems" (2024, 24 citations), which addresses the critical challenge of coordinating multiple robots for industrial applications like warehouse inspection and hydrographic surveying. Notably, his earlier work, "Design and implementation of an USV for large bodies of fresh waters at the highlands of Peru" (2017, 9 citations), demonstrates a commitment to applied, socially-relevant robotics, developing a USV for water quality monitoring in the Peruvian highlands. With a growing citation record and recent innovations like the RRT-GPMP2 motion planner (2025), Bucknall is shaping the future of autonomous navigation and multi-agent collaboration.

Research Focus

Key Achievements

3
H-Index
4
Papers
60
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
A Fully-Autonomous Framework of Unmanned Surface Vehicles in Maritime Environments Using Gaussian Process Motion Planning
25 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: University College London

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago