Ruitian Pang
Papers
2
Total Citations
6
H-Index
2
About
Ruitian Pang is a robotics researcher specializing in human-robot interaction, with a particular focus on seamless and intuitive handover tasks. Their work bridges the gap between human intention and robotic action by leveraging multimodal perception—integrating visual, tactile, and spatial data to enable robots to anticipate and respond to human movements during object transfer. Pang’s most cited paper, "Human-to-robot handovers based on multimodal perception" (2025, 4 citations), introduces a framework that fuses sensory inputs for robust, real-time coordination, while their earlier study, "6-DoF Grasp Planning on Point Cloud for Human-to-Robot Handover Task" (2023, 2 citations), advances grasp planning by using 3D point cloud data to compute optimal six-degree-of-freedom grasps. Though early in their career, Pang’s contributions are foundational to developing socially aware robots capable of safe and efficient physical collaboration. Their work holds promise for applications in manufacturing, healthcare, and assistive robotics, where fluid human-robot teamwork is essential.
Research Focus
Key Achievements
Top Papers
- 1Human-to-robot handovers based on multimodal perception4 citations · 2025
- 26-DoF Grasp Planning on Point Cloud for Human-to-Robot Handover Task2 citations · 2023