Honggao Deng

Guilin University of Electronic Technology

Papers

Total Citations

H-Index

About

Honggao Deng is a researcher whose work lies at the intersection of robotics and intelligent path planning, with a particular focus on optimizing mobile robot navigation. His most cited paper, "Implementation of IMRRT Path Planning Algorithm for Mobile Robot" (2022), addresses a critical challenge in the field: the inherent randomness and inefficiency of the classic Rapidly-exploring Random Tree (RRT) algorithm. Deng’s major contribution is the development of the Improved Memory-based RRT (IMRRT) algorithm, which enhances search efficiency and reduces path irregularity by incorporating memory mechanisms into the expansion process. This innovation offers a more reliable and smoother navigation solution for autonomous mobile robots in complex environments. With 4 citations, this work has already garnered attention from peers seeking practical improvements to RRT-based systems. Deng’s research is particularly valuable for students and engineers working on real-world robotic applications, where efficiency and path quality are paramount. His work exemplifies a thoughtful refinement of foundational algorithms, demonstrating how targeted improvements can yield significant practical benefits in autonomous systems.