Hector Samuel Monjardin Hernandez

Papers

1

Total Citations

4

H-Index

1

About

Hector Samuel Monjardin Hernandez is a robotics researcher specializing in autonomous navigation and motion planning for mobile robots operating in uncertain environments. His most cited work, "Autonomous navigation for a holonomic drive robot in an unknown environment using a depth camera" (2020), introduces a practical implementation of the RRT* path planning algorithm integrated with depth sensor data. This system enables an omnidirectional robot to dynamically plan and replan trajectories from a starting point to a goal, even when the environment is only partially known or entirely unknown. By combining real-time perception with efficient sampling-based planning, Hernandez’s research addresses a critical challenge in field robotics: safe and adaptive navigation without pre-mapped surroundings. His contributions have garnered attention in the robotics community, with his flagship paper accumulating 4 citations—a meaningful impact for a focused, application-driven study. Hernandez’s work is particularly relevant for autonomous systems in disaster response, exploration, and service robotics, where adaptability and sensor-driven decision-making are essential. His approach demonstrates how accessible hardware, such as depth cameras, can be paired with advanced algorithms to achieve robust autonomy in real-world conditions.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Autonomous navigation for a holonomic drive robot in an unknown environment using a depth camera
4 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 3

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago