Max Robotics — Global Service Robot Directory + US Certification

About

Mingshan Xie is a robotics researcher whose work focuses on the intersection of autonomous navigation, energy-efficient data acquisition, and agricultural robotics. Their major contributions lie in developing intelligent algorithms for mobile robots operating under real-world constraints—such as limited battery life, time-sensitive tasks, and complex environments. Notably, Xie’s most-cited paper, "Energy- and Time-Aware Data Acquisition for Mobile Robots Using Mixed Cognition Particle Swarm Optimization" (2020, 14 citations), formulates data collection as a multiobjective optimization problem, enabling robots to balance energy and time constraints effectively. In agricultural robotics, their work on "Real-Time Recognition and Localization Based on Improved YOLOv5s for Robot’s Picking Clustered Fruits of Chilies" (2023, 11 citations) addresses the challenge of detecting occluded fruits in dense foliage, advancing precision harvesting. Xie also tackles infrastructure challenges, such as path planning for indoor charging piles and multi-robot scheduling for battery towing, ensuring uninterrupted service. Their recent exploration of vision-language models for grasp pose detection (2025) signals a shift toward semantic understanding in manipulation. With over 30 citations across key publications, Xie’s research is shaping the future of autonomous robots in logistics, agriculture, and service industries.