Max Robotics — Global Service Robot Directory + US Certification

About

He Du is an emerging researcher specializing in mobile robotics, path planning, and reinforcement learning-based navigation systems. His work focuses on developing intelligent algorithms that enable robots to operate autonomously and efficiently in complex, unknown environments — a critical challenge in modern robotics research. Du's most significant contributions lie in advancing Q-learning methodologies for robotic path planning. His 2022 papers introduced the Potential and Dynamic Q-Learning (PDQL) approach and the "short and safe Q-learning" method, each garnering over a dozen citations and addressing fundamental trade-offs between path efficiency and obstacle avoidance. These works demonstrate his consistent effort to bridge classical artificial potential field techniques with adaptive reinforcement learning frameworks. Beyond theoretical contributions, Du has applied his expertise to practical industrial problems. His 2021 work on automatic recharging path planning for cleaning robots — utilizing an improved Maklink graph structure — earned 12 citations and showcases his ability to translate algorithmic innovation into real-world robotic applications. More recently, his 2023 fusion of the Flower Pollination Algorithm with Q-learning for search-and-rescue robots highlights his growing interest in bio-inspired computation. With a focused and rapidly developing publication record, Du represents a promising voice in intelligent robotics and autonomous systems research.