Papers
3
Total Citations
12
H-Index
2
About
Shigang Peng is a robotics researcher advancing the safety and intelligence of robotic systems in complex, unstructured environments. His work centers on three key areas: teleoperation safety, bioinspired tactile sensing, and reinforcement learning for robotic control. Peng’s most cited paper (2023, 7 citations) introduces a collision risk assessment and operation assistant strategy for teleoperation systems—critical for applications like in-orbit assembly where human-guided robots must navigate high-risk scenarios without autonomous fallbacks. He further contributes to physical human-robot interaction through a bioinspired tactile sensing system (2024, 3 citations) that uses self-sensing soft pneumatic actuators to recognize objects, enabling robots to modulate contact forces and prevent damage during manipulation tasks. In parallel, Peng explores autonomous mobility with a velocity control framework for a multi-motion mode spherical probe robot (2023, 2 citations), leveraging reinforcement learning to enhance adaptability in harsh, unknown terrains for deep space exploration. His research bridges the gap between human teleoperation and autonomous capability, with a clear trajectory toward safer, more perceptive robots. Peng’s work is particularly notable for its practical focus on collision avoidance and tactile intelligence, laying groundwork for next-generation robots in space and industrial settings.
Research Focus
Key Achievements
Top Papers
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