Jiting Chen

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About

Jiting Chen is a researcher in robotics and autonomous systems, with a primary focus on simultaneous localization and mapping (SLAM) and autonomous exploration in unknown indoor environments. Their most impactful contribution is the development of an improved Rapidly-exploring Random Tree (RRT) method for robot autonomous exploration and SLAM construction, published in 2020. This work addresses a critical challenge in mobile robotics: enabling robots to efficiently explore partially observable and uncertain environments while simultaneously constructing accurate maps. The proposed method has garnered 13 citations, reflecting its relevance to advancing autonomous navigation capabilities. Chen's research is particularly significant for applications in search-and-rescue, domestic service robots, and industrial automation, where robust exploration in GPS-denied indoor spaces is essential. By tackling the fundamental problem of balancing exploration efficiency with map accuracy under real-world uncertainty, Chen has contributed a practical solution that improves the autonomy and reliability of mobile robots. Their work continues to influence the development of more adaptive and intelligent robotic systems capable of operating in complex, unstructured environments.