Papers
7
Total Citations
83
H-Index
5
About
Suman Raj Bista is a leading researcher in robotic vision and autonomous navigation, whose work has fundamentally advanced how mobile robots perceive and move through indoor environments. His core research focuses on appearance-based navigation, where he pioneered methods that allow robots to navigate using only 2D image information—eliminating the need for complex 3D reconstructions. Bista’s most influential contribution, the 2016 paper “Appearance-Based Indoor Navigation by IBVS Using Line Segments” (31 citations), introduced a novel approach using line segments as landmarks for image-based visual servoing (IBVS). He later expanded this framework by combining line segments with feature points (18 citations), creating more robust navigation systems. His impact extends beyond theory; Bista co-developed BenchBot, a software suite that bridges the gap between photorealistic simulation and real-world robotics, enabling standardized benchmarking of active scene understanding research. His work on topological navigation with collision avoidance (12 citations) addresses the practical challenges of resource-constrained mobile robots. Through these contributions, Bista has established himself as a key figure in creating vision-based systems that are both computationally efficient and practically deployable, making indoor robotic navigation more accessible and reliable for real-world applications.
Research Focus
Key Achievements
Top Papers
- 1Appearance-Based Indoor Navigation by IBVS Using Line Segments31 citations · 2016
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- 6The Robotic Vision Scene Understanding Challenge4 citations · 2020
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