Tingbin Chen

Dalian Neusoft University of Information

Papers

Total Citations

H-Index

About

Tingbin Chen’s research focuses on the foundational challenges of mobile robotics, particularly in motion planning and multi-robot coordination. His most cited work, “Robot motion planning based on improved artificial potential field” (2013, 21 citations), addresses a core problem in intelligent robotics: enabling robots to navigate complex environments efficiently. By refining the artificial potential field method, Chen’s approach enhances path planning, a critical technology for autonomous systems. This work has been cited over 20 times, reflecting its relevance to researchers tackling real-world navigation issues. Chen also explores multi-robot systems, notably in “Research on multi-robot capturing strategy based on finite-state machine” (2013, 2 citations), where he investigates cooperative strategies for tasks like formation patrol and environmental investigation. Although less cited, this study contributes to the challenging domain of multi-robot capture operations, integrating finite-state machines to coordinate team behaviors. Chen’s contributions bridge theoretical path planning with practical multi-robot applications, offering insights that support advancements in autonomous navigation and swarm robotics. His work serves as a stepping stone for students and researchers interested in the intersection of algorithm design and robotic teamwork.