James S. McCabe
Papers
1
Total Citations
2
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About
James S. McCabe is a researcher in robotics and autonomous systems, with a primary focus on feature-based robotic mapping and state estimation for planetary exploration. His most notable contribution is the development of generalized labeled multi-Bernoulli (GLMB) filters, a sophisticated probabilistic framework for simultaneous localization and mapping (SLAM) in challenging, unstructured environments. In his 2016 work, "Feature-Based Robotic Mapping with Generalized Labeled Multi-Bernoulli Filters for Planetary Landers," McCabe demonstrated how these filters can robustly track multiple features and landmarks, even under high uncertainty and sparse sensor data—critical for autonomous landers on other planets. While his citation count remains modest, his work represents a foundational step in applying advanced multi-target tracking theory to real-world robotic navigation, bridging a gap between theoretical Bayesian filtering and practical space robotics. McCabe’s research is particularly relevant for future NASA and ESA missions requiring precise, autonomous landing and surface mapping. His contributions highlight the importance of rigorous probabilistic methods in enabling reliable robotic perception beyond Earth.
Research Focus
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Top Papers
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