Felipe Inostroza
Papers
9
Total Citations
135
H-Index
6
About
Felipe Inostroza is a leading researcher in mobile robotics, specializing in Simultaneous Localization and Mapping (SLAM) and random finite set (RFS) theory. His work addresses critical challenges in autonomous navigation, particularly in harsh environments like underground mines. Inostroza’s major contributions include pioneering RFS-based SLAM methods that eliminate heuristic data association and integrate detection statistics, leading to more robust and accurate map and trajectory estimates. His 2017 paper on the Chilean underground mine dataset (40 citations) provides a unique, real-world benchmark from the world’s largest underground copper mine, enabling researchers to test algorithms under realistic conditions. He also developed the δ-Generalized Labeled Multi-Bernoulli SLAM with optimal kernel-based particle filtering (26 citations) and introduced the COLA metric (8 citations) for evaluating multi-object error in mapping. With over 135 total citations, Inostroza’s work bridges theory and practice, offering principled solutions for autonomous systems operating in complex, unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1Chilean underground mine dataset40 citations · 2017
- 2
- 3Metrics for Evaluating Feature-Based Mapping Performance25 citations · 2016
- 4
- 5Generalizing random-vector SLAM with random finite sets10 citations · 2015
- 6
- 7
- 8
- 9