Bunyod Suvonov
Papers
1
Total Citations
1
H-Index
1
About
Bunyod Suvonov is a researcher at the forefront of robotics and autonomous navigation, with a primary focus on path planning in complex, interactive environments. His most notable contribution is the development of search-based algorithms for Path Planning Among Movable Obstacles (PAMO), a challenging problem where robots must not only avoid static obstacles but also strategically push movable objects to clear a path to their goal. This work, published in 2025, introduces complete and optimal planners that significantly advance the state of the art in robotic manipulation and navigation. While his research is still early in its impact trajectory, Suvonov’s approach bridges the gap between classical search-based planning and dynamic, real-world environments, offering practical solutions for robots operating in cluttered spaces like warehouses or disaster zones. His work has already garnered attention, with his most-cited paper receiving 1 citation, and it promises to influence future developments in autonomous systems. Suvonov’s contributions are particularly valuable for students and researchers interested in the intersection of motion planning, artificial intelligence, and interactive robotics.
Research Focus
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Top Papers
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