Lanjun Liang

Shanghai Institute of Technology, Tsinghua University

Papers

Total Citations

H-Index

About

Lanjun Liang is a pioneering researcher in embodied AI and service robotics, specializing in long-term autonomy and human-robot interaction. His work centers on enabling robots to intelligently search for and track dynamic objects in complex indoor environments—a critical challenge for household and service robots. Liang’s most cited paper, “Long-term object search using incremental scene graph updating” (2022, 16 citations), introduces a novel framework that allows robots to persistently update their environmental knowledge, effectively locating movable objects like cups even as they change position over time. This contribution addresses a fundamental limitation in traditional static mapping. Building on this, his 2023 paper “Extracting Dynamic Navigation Goal from Natural Language Dialogue” (10 citations) advances natural language understanding in robotics, enabling robots to interpret conversational cues to track moving targets such as humans. Liang’s research bridges perception, reasoning, and dialogue, significantly improving robots’ ability to operate in dynamic, human-centric spaces. His work has garnered attention for its practical applications in assistive robotics, and he continues to shape the future of autonomous systems that can adapt to real-world unpredictability.