Daniel Gonzalez-Adell
Papers
1
Total Citations
33
H-Index
1
About
Daniel Gonzalez-Adell is a robotics researcher specializing in autonomous navigation and motion planning for underwater vehicles. His primary research focuses on developing advanced path planning algorithms that enable autonomous underwater vehicles (AUVs) to operate safely and efficiently in complex, unknown 3D environments. His most cited work, "Online 3-Dimensional Path Planning with Kinematic Constraints in Unknown Environments Using Hybrid A* with Tree Pruning" (2021, 33 citations), presents a significant extension to the hybrid A* planner. This contribution addresses the critical challenge of incorporating kinematic constraints into real-time 3D path planning, allowing AUVs to navigate while accounting for their physical motion limitations. The work's impact is demonstrated through its citation count and its practical relevance to underwater robotics, where safe autonomous operation remains a key challenge. Gonzalez-Adell's research bridges the gap between theoretical path planning and real-world robotic applications, contributing to the broader field of autonomous systems and marine robotics.
Research Focus
Key Achievements
Top Papers
- 1