Papers
18
Total Citations
237
H-Index
8
About
Lavindra de Silva is a robotics and artificial intelligence researcher whose work spans autonomous systems, task planning, formal verification, and, more recently, highway infrastructure digitization. He is perhaps best known for his contributions to hierarchical task network (HTN) planning for robotics, most notably through the development of HATP (Hierarchical Agent-Based Task Planner), which has become a significant reference in the field with over 40 citations. His research addresses how robots can intelligently plan and execute complex, real-world tasks by combining high-level symbolic reasoning with geometric planning — a challenging integration he has explored across multiple influential papers, including work on symbolic-geometric backtracking that has attracted nearly 30 citations. De Silva has also made notable contributions to the formal, correct-by-construction design of robot software, advocating rigorous component-based methods to ensure safety and reliability in autonomous systems — a critical concern as robots increasingly operate in high-stakes environments. More recently, his research has expanded into smart infrastructure, including digital twin-enabled highway maintenance and mobile mapping datasets for UK road networks. Collectively, his publications reflect a career dedicated to making autonomous systems both practically deployable and theoretically sound.
Research Focus
Key Achievements
Top Papers
- 1HATP: An HTN Planner for Robotics41 citations · 2014
- 2Rigorous design of robot software: A formal component-based approach33 citations · 2012
- 3An interface for interleaved symbolic-geometric planning and backtracking29 citations · 2013
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- 8Process Plan Controllers for Non-Deterministic Manufacturing Systems10 citations · 2017
- 9CAMHighways: The Cambridge Highways dataset8 citations · 2024
- 10Highway digital twin-enabled Autonomous Maintenance Plant: a perspective7 citations · 2024