Tan GZ
Papers
1
Total Citations
17
H-Index
1
About
Tan GZ is a leading researcher in industrial robotics, with a primary focus on time-optimal trajectory planning and control. Their most influential work, a 2003 study with 17 citations, introduces a novel method that minimizes robot travel time along a prescribed Cartesian path while respecting joint displacement, velocity, acceleration, and jerk constraints. By representing joint trajectories as quadratic polynomials combined with cosine functions, Tan’s approach ensures continuous second-order acceleration, thereby enhancing both operational efficiency and mechanical longevity. Validated through computer simulations and experiments on a PUMA 560 robot, this research provides a robust solution to nonlinear kinematic optimization problems. Tan’s contributions are pivotal for advancing high-speed, precision automation, directly impacting manufacturing productivity and robot lifespan. Their work remains a cornerstone for engineers and researchers tackling constrained motion planning in industrial settings.
Research Focus
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Top Papers
- 1