Papers
7
Total Citations
15
H-Index
2
About
Jiliang Zhao is a researcher at the forefront of robotics, with key contributions spanning parallel robots, soft robotics, and minimally invasive surgical systems. His work is distinguished by a focus on precision, adaptability, and intelligent design. Zhao’s most cited paper, "Vision-based method of kinematic calibration and image tracking of position and posture for 3-RPS parallel robot" (2017, 4 citations), introduces a novel calibration method that addresses critical manufacturing and assembly errors, enhancing the practical deployment of parallel robots. In soft robotics, his recent "A Morphological Transfer-Based Multi-Fidelity Evolutionary Algorithm for Soft Robot Design" (2024, 3 citations) and "Cross-Task Collaborative Optimization Based on Knowledge Transfer for Soft Robot Design" (2025, 1 citation) pioneer efficient design paradigms that integrate morphology evolution and control learning, significantly reducing computational time. Zhao has also made notable strides in medical robotics, with multiple papers on trajectory planning, clamping dexterity, and dynamic modeling for minimally invasive surgical robot manipulators (2009–2017, 2 citations each). His research on the 3-DOF coordinate measuring robot (2017, 1 citation) further demonstrates his versatility in precision measurement. With a cumulative impact of over 15 citations, Zhao’s work is shaping the future of intelligent, adaptive robotic systems for both industrial and medical applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6Error analysis and research on 3-DOF coordinate measuring robot1 citations · 2017
- 7