Daniel Drake

Papers

Total Citations

H-Index

About

Daniel Drake is a leading researcher in mobile robotics, with a focus on path planning for dynamic environments. His work addresses the critical challenge of enabling autonomous systems—such as unmanned aerial and underwater vehicles—to pursue moving targets in real time. Drake’s most-cited paper, “Mobile Robot Path Planning With a Moving Goal” (2018, 31 citations), introduces an incremental path planning algorithm that reuses previous planning data to efficiently adapt to a moving goal. This contribution is foundational for applications in surveillance, search-and-rescue, and autonomous navigation. By reducing computational overhead while maintaining robust performance, Drake’s algorithm has influenced subsequent work in dynamic path planning and multi-agent coordination. His research bridges theory and practice, offering scalable solutions for robots operating in unpredictable environments. With a growing citation record and a reputation for tackling hard, real-world problems, Drake is a rising voice in the robotics community. For students and researchers, his work exemplifies how clever algorithmic design can unlock new capabilities in autonomous systems.