Qihang Chen
Papers
2
Total Citations
18
H-Index
2
About
Qihang Chen is a pioneering researcher in the field of deep-sea robotics and autonomous underwater vehicle control, with a specialized focus on intelligent path planning and navigation systems for extreme marine environments. His groundbreaking work addresses the critical challenges of operating deep-sea mining vehicles (DSMVs) in complex, unstructured underwater terrains. Chen's most influential contribution, "Three-Dimensional Path Planning of Deep-Sea Mining Vehicle Based on Improved Particle Swarm Optimization" (2023, 16 citations), revolutionized obstacle avoidance strategies by developing a novel algorithm that overcomes the traditional particle swarm optimization's tendency to converge on local optima, significantly enhancing both convergence speed and path decision-making accuracy. Building on this foundation, his latest work (2025) introduces an optimized deep reinforcement learning framework for dual-task control, simultaneously managing path following and obstacle avoidance—a breakthrough that addresses the fundamental limitations of conventional training strategies in underwater robotics. Chen's research directly impacts the future of autonomous deep-sea resource extraction, providing the computational intelligence necessary for safe and efficient mining operations in one of Earth's most challenging environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2