Junjie Lu

Papers

Total Citations

H-Index

About

Junjie Lu is a rising researcher in robotics, specializing in multi-robot systems, coverage path planning, and 2D LiDAR-based simultaneous localization and mapping (SLAM). His most influential work, "TMSTC*: A Path Planning Algorithm for Minimizing Turns in Multi-Robot Coverage" (2023, 52 citations), introduces a novel spanning-tree coverage algorithm that significantly reduces the number of turns required for multi-robot area coverage—a critical factor for energy efficiency and mission time in real-world applications like cleaning, inspection, and agriculture. In parallel, his paper "2DLIW-SLAM: 2D LiDAR-inertial-wheel odometry with real-time loop closure" (2024, 14 citations) addresses a persistent challenge in indoor navigation: motion degeneracy in geometrically feature-poor environments. By tightly fusing 2D LiDAR, inertial, and wheel odometry data with real-time loop closure, Lu’s approach achieves robust and accurate localization on cost-effective hardware. His contributions are already shaping practical, deployable solutions for autonomous mobile robots, bridging the gap between theoretical algorithms and real-world constraints.