Xiaoteng Wang

Papers

Total Citations

H-Index

About

Xiaoteng Wang is a robotics researcher whose work focuses on advancing autonomous navigation through novel path planning methodologies. His key research areas include robotic motion planning, algorithm design, and bio-inspired computational approaches for autonomous systems. Wang’s most notable contribution is the development of the Ray Tracking & Illumination Algorithm, introduced in his 2022 paper "Robotic Path Planning Algorithm based on Ray Tracking and Diffuseness." This innovative algorithm simulates natural ray propagation and diffuse reflection to search for optimal paths, drawing inspiration from physical light behavior. To enhance path quality, Wang incorporated redundant node removal and Bezier curve smoothing techniques, demonstrating a sophisticated integration of physics-based modeling with computational geometry. While his work is still early in its citation impact trajectory, with 2 citations to date, the conceptual novelty of his approach—applying ray diffuseness principles to robotic navigation—represents a creative departure from traditional graph-based or sampling-based planners. Wang’s research contributes to the growing field of nature-inspired robotics, offering potential applications in complex, obstacle-dense environments where conventional algorithms may struggle. His work is particularly relevant for students and researchers interested in interdisciplinary approaches to autonomous systems.