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About

Tingting Bao is a leading researcher in the field of industrial robotics, specializing in trajectory planning and motion optimization. Her work focuses on developing algorithms that minimize execution time while reducing mechanical vibration and jerk in robotic manipulators, directly enhancing productivity in manufacturing and pick-and-place operations. In her highly cited 2022 paper, Bao introduced a hybrid Whale Optimization Algorithm and Genetic Algorithm (WOA-GA) for time-jerk optimal trajectory planning, achieving smoother motion with reduced joint vibration—a contribution that has garnered 43 citations. She also proposed a novel point-to-point trajectory planning algorithm (PTPA) based on a locally asymmetrical jerk motion profile, which significantly improves motion efficiency and has been cited 30 times. More recently, in 2024, Bao advanced the field with a multi-objective optimal trajectory planning approach for manipulators using a constrained multi-objective student psychology-based optimization (CMOSPBO) algorithm, integrating quintic B-spline curves for smooth joint-space trajectories. Her work is instrumental in bridging the gap between theoretical optimization and practical robotic performance, making her a key figure in modern industrial automation research.