Papers
3
Total Citations
28
H-Index
3
About
Jintao Ma is a robotics researcher whose work focuses on the design and optimization of hybrid and parallel robots for industrial assembly, particularly in constrained environments like aircraft cabins. His major contributions center on developing lightweight, high-payload robots that balance structural efficiency with load capacity. His most cited paper, "Optimal design of a parallel assembling robot with large payload-to-mass ratio" (2022, 14 citations), introduces a novel approach to achieving high strength-to-weight ratios, critical for aerospace applications. Building on this, his 2023 work on a five-degree-of-freedom hybrid robot (9 citations) combines a 1T2R parallel module with a 2T serial module, demonstrating through experiments how such designs can reduce mass while maintaining payload capabilities. Earlier, Ma explored multi-sensor augmented reality tracking for robot hand-eye calibration (2012, 5 citations), showing his versatility in integrating perception and control. With a cumulative citation count reflecting growing influence in manufacturing robotics, Ma’s research is shaping next-generation assembly systems that are both agile and robust, offering practical solutions for industries requiring precise, heavy-duty automation in tight spaces.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3