Qianlai Sun

Taiyuan University of Science and Technology

Papers

Total Citations

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About

Qianlai Sun is a leading researcher in the field of robotics trajectory planning, with a specific focus on heavy machinery such as hydraulic excavators. His work centers on optimizing the motion of robotic systems to achieve superior performance in terms of speed, energy efficiency, and operational smoothness. Sun’s major contributions include the development of novel algorithms that overcome the limitations of traditional intelligent methods like Particle Swarm Optimization (PSO) and Differential Evolution (DE), which often get trapped in local optima. He pioneered the use of Sequential Quadratic Programming (SQP) for time-jerk optimal trajectory planning, a method that has garnered 48 citations. Further advancing the field, he introduced an Improved Simplified Particle Swarm Optimization (ISPSO) algorithm for time-optimal planning, cited 18 times, and a multi-objective approach for time-energy consumption optimization under path constraints. His work is critical for enhancing the productivity and sustainability of large-scale construction equipment. With a growing citation impact, Sun’s research is shaping the next generation of intelligent, efficient, and autonomous heavy machinery, making him a key figure in applied robotics and industrial automation.