Lijun Ma

Zhongnan University of Economics and Law

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Total Citations

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About

Lijun Ma is an emerging researcher specializing in autonomous robotics, with a particular focus on intelligent path planning and obstacle avoidance in complex, high-stakes environments. Ma's work sits at the intersection of deep reinforcement learning and practical robotic navigation, addressing real-world challenges where conventional algorithms fall short. Ma's most recognized contribution is the development of an adaptive obstacle avoidance algorithm combining Deep Deterministic Policy Gradient (DDPG) with the Dynamic Window Approach (DWA), a hybrid framework that has garnered 33 citations since its 2023 publication — a strong indicator of rapid community uptake for such recent work. This research advances how robots dynamically respond to unpredictable environments, a critical capability for deployment in unstructured spaces. Equally noteworthy is Ma's work on full coverage path planning for emergency fire control robots operating in nuclear environments — a domain defined by extreme hazard, irregular spatial geometry, and densely distributed obstacles. By applying reinforcement learning to this uniquely demanding setting, Ma demonstrates a commitment to high-impact, safety-critical applications that push the boundaries of autonomous robotics. With publications concentrated in 2023, Lijun Ma represents a promising voice in next-generation intelligent robotics research.