About

Rafael Valencia is a robotics researcher whose work centers on simultaneous localization and mapping (SLAM), autonomous navigation, and robotic exploration. He is perhaps best known for his sustained contributions to Pose SLAM, a landmark-free variant of SLAM that estimates robot trajectories directly, making maps immediately actionable for path planning. His 2013 paper "Planning Reliable Paths With Pose SLAM" (76 citations) demonstrated how this framework could support safe, reliable navigation without the overhead of traditional feature-based maps, while his 2011 and 2017 follow-up works extended these ideas into belief-space planning and full exploration pipelines. Beyond SLAM, Valencia has made significant contributions to autonomous exploration, proposing information-driven methods on continuous Gaussian process maps (60 citations) and reaction-diffusion-inspired exploration strategies. His early work on 3D urban mapping and vision-based loop closing laid important groundwork for outdoor service robotics. More recently, he has tackled multi-robot coordination, addressing simultaneous task allocation and collision-free trajectory planning in dynamic environments. With over 290 cumulative citations, Valencia's research spans the full autonomy stack — from perception and mapping to planning and coordination — making his body of work an essential reference for students and practitioners in mobile robotics.

Research Focus

Key Achievements

7
H-Index
11
Papers
297
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
Planning Reliable Paths With Pose SLAM
76 citations · 2013
📈 Most Prolific Year: 2017 (3 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Institut de Robòtica i Informàtica Industrial, Örebro University, Universitat Politècnica de Catalunya, Carnegie Mellon University, FC Barcelona, Consejo Superior de Investigaciones Científicas

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago