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Xiao Ai-ping is a pioneering researcher in robotics and intelligent systems, with a primary focus on spherical robot kinematics, path planning, and deep learning applications. Her seminal work on the "Omnidirectional kinematics analysis on bi-driver spherical robot" (2005, 27 citations) established foundational principles for nonholonomic and underactuated systems, introducing a novel omnidirectional mobile robot design that enhances flexibility across diverse fields. She further advanced this domain through "Movement Trajectory Planning and Control for a Spherical Robot" (2004, 4 citations), developing robust control strategies for complex robotic motion. Xiao's research extends to agricultural automation, as seen in "Path Planning Technology and Its Application in Greenhouse Robot" (2010, 3 citations), where she systematically classified global and local path planning methods. Demonstrating versatility, she integrated gradient estimation theory and Mask R-CNN convolutional networks in "Deep Learning-Based Algorithm for Recognizing Tennis Balls" (2022, 10 citations) to optimize target recognition for tennis-picking robots. Additionally, her work on CAN bus communication systems (2012, 5 citations) highlights expertise in embedded system design. With a career spanning two decades, Xiao's contributions bridge theoretical kinematics and practical AI-driven robotics, impacting both industrial and agricultural applications.