Papers
13
Total Citations
292
H-Index
10
About
Hepeng Ni is a robotics and automation researcher whose work spans intelligent robotic control, machining optimization, and emerging sensing technologies. His research has made significant contributions to trajectory tracking control for robotic manipulators, developing novel approaches that combine extended state observers with backstepping and computed torque methods to achieve high precision under parameter uncertainties and external disturbances — work that has collectively garnered nearly 90 citations across multiple publications. Ni has made notable advances in robotic machining, addressing critical challenges such as posture optimization under combined spindle weight and cutting forces (71 citations) and real-time chatter detection using adaptive signal decomposition. His 2024 work on digital twin-driven virtual commissioning, enhanced by machine learning, reflects his forward-looking integration of emerging technologies into manufacturing systems. Beyond manipulation and machining, his research extends to dynamic parameter identification for industrial robots, S-shaped trajectory planning for sorting systems, and mobile robot localization. A particularly distinctive contribution is his work on in-sensor visual perception and inference (31 citations), bridging robotics with neuromorphic and edge-computing paradigms. With over 270 total citations across his most impactful papers, Ni's interdisciplinary portfolio positions him as a versatile contributor to next-generation intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2In-Sensor Visual Perception and Inference31 citations · 2023
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