Bahram Sadeghi Bigham
Papers
7
Total Citations
43
H-Index
4
About
Bahram Sadeghi Bigham is a leading researcher in robotics and artificial intelligence, with a primary focus on mobile robot localization, navigation, and behavior modeling in complex, dynamic environments. His major contributions include developing novel probabilistic methods for indoor robot localization using artificial landmarks, as demonstrated in his most-cited work (15 citations), which addresses the challenge of accurate pose estimation in cluttered settings. He also introduced the Geometrical Scan Registration (GSR) algorithm (13 citations), a fast and robust technique for robot pose estimation based on laser range data, advancing real-time localization capabilities. In the realm of multi-agent systems, Bigham proposed a learning-based Petri net model for a soccer goalkeeper robot, enabling qualitative and quantitative task analysis. His work extends to computational geometry with a polynomial-time algorithm for the minimum constraint removal problem in big data contexts, and neural network approaches for obstacle avoidance in unknown environments. Bigham’s research has garnered significant attention, with over 40 total citations, and his achievements include advancing practical solutions for autonomous navigation in dynamic settings, making him a notable figure in robotics and AI.
Research Focus
Key Achievements
Top Papers
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- 3A learned soccer goalkeeper Petri net model4 citations · 2017
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- 6Minimum landmarks for robot localization in orthogonal environments2 citations · 2021
- 7Near-pole polar diagram of objects and duality2 citations · 2011