Xindong Tang
Papers
2
Total Citations
16
H-Index
2
About
Xindong Tang is a rising leader in safe and autonomous robot navigation, with a focus on enabling robots to move intelligently through complex, cluttered, and unknown spaces. Their core research lies at the intersection of trajectory optimization, control theory, and formal methods, specifically leveraging sums-of-squares (SOS) programming to guarantee safety. In their highly cited 2024 work, "Collision-Free Trajectory Optimization in Cluttered Environments Using Sums-of-Squares Programming" (9 citations), Tang introduced a novel approach that represents a robot’s geometry as a semialgebraic set, allowing for provably collision-free paths for robots of arbitrary shapes. Building on this foundation, their companion paper, "Geometry-Aware Safety-Critical Local Reactive Controller for Robot Navigation in Unknown and Cluttered Environments" (7 citations), formulates trajectory tracking as a constrained polynomial optimization problem, embedding safety constraints directly into the control law. This work provides a robust, real-time reactive controller that does not require a pre-built map. By fusing geometric awareness with formal safety guarantees, Tang is pioneering a new class of controllers that are both theoretically rigorous and practically deployable, making significant strides toward truly autonomous robots in human-centric environments.
Research Focus
Key Achievements
Top Papers
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