Shunan Qi

Papers

Total Citations

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About

Shunan Qi is a robotics researcher whose work centers on the motion planning and control of bio-inspired and industrial robotic systems. Their major contributions lie in optimizing the energy efficiency and autonomous operation of robots, particularly through advanced computational methods. Qi’s most cited paper, “Motion Planning of an Inchworm Robot Based on Improved Adaptive PSO” (2022, 6 citations), introduces a novel approach to minimize motion energy consumption in a self-developed inchworm robot’s peristaltic gait. By combining cubic polynomial programming in Cartesian space with seventh polynomial programming in joint space, and leveraging an improved adaptive particle swarm optimization (PSO) algorithm, Qi achieves precise “error tracking” for smoother, more efficient locomotion. This work is notable for its direct application to real-world robotic systems, addressing a critical challenge in soft robotics. In a second influential study (2023, 5 citations), Qi focuses on industrial robot dynamics, proposing a step-by-step identification method for dynamic model parameters and a force-free control strategy for intuitive robot teaching. This research enhances human-robot collaboration by enabling safer, more responsive interactions. With a growing citation footprint, Shunan Qi is establishing a reputation for bridging theoretical optimization with practical robotic applications, making their work essential reading for students and researchers in robotics, control systems, and bio-inspired engineering.