Papers
5
Total Citations
43
H-Index
3
About
Yachao Cao is a robotics researcher whose work focuses on the design, control, and calibration of parallel mechanisms and autonomous mobile robots. His primary research areas include parallel robot kinematics, trajectory tracking control, and precision calibration techniques. Cao’s most significant contributions involve the development of parallel mechanisms with constant Jacobian matrices—a breakthrough that simplifies robot analysis and control by eliminating the pose-dependent variability typical of such systems. His work on the 3-CRU translational parallel robot is particularly notable, where he has advanced linear kinematics equations, robust PD+ control strategies, and efficient calibration methods that reduce the complexity of error measurement. With over 40 citations across his top papers, Cao’s research has practical implications for industries like packaging and medicine, where rapid, repetitive handling tasks demand high precision. He has also extended his expertise to agricultural robotics, developing cascaded model predictive control and anti-slip drive control for orchard mowing robots operating in challenging terrain. Cao’s achievements include advancing the theoretical foundations of parallel mechanism synthesis while simultaneously addressing real-world challenges in robot accuracy and autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Type Synthesis of Parallel Mechanisms With a Constant Jacobian Matrix12 citations · 2018
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