Heng Deng

Southwest Petroleum University, Beijing University of Technology

Papers

Total Citations

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About

Heng Deng is a robotics and control systems researcher whose work sits at the intersection of intelligent optimization, multi-robot coordination, and motion planning. His research addresses fundamental challenges in making robotic systems more capable, practical, and deployable in real-world environments. Among his most notable contributions is his 2021 work on an improved particle swarm optimization algorithm for solving inverse kinematics in multi-degree-of-freedom serial robotic manipulators — a notoriously complex problem in robotics that directly impacts the precision and efficiency of robotic arms. This paper has garnered 51 citations, reflecting its significance to the field and its adoption by fellow researchers tackling similar computational challenges. Deng has also advanced the field of multi-robot systems through his research on leader-follower formation control for mobile robots. This work tackles the practical challenge of coordinating robot teams under real-world velocity constraints, developing strategies for both trajectory tracking in leader robots and formation maintenance in follower robots — critical capabilities for applications ranging from warehouse automation to autonomous vehicle convoys. Taken together, Deng's contributions demonstrate a consistent focus on bridging theoretical optimization methods with practical robotic implementation challenges.