Lanbo She

About

Lanbo She is a researcher whose work sits at the intersection of human-robot interaction, natural language processing, and grounded language learning. Her research focuses primarily on enabling robots to understand and respond to natural language instructions within shared physical environments — a challenge that demands bridging the gap between symbolic linguistic representations and a robot's continuous, sensor-driven perception of the world. She's perhaps best known for her contributions to situated human-robot dialogue, particularly her development of frameworks that allow robots to learn new actions through conversational instruction rather than traditional programming. Her 2014 paper on learning new actions in a blocks world setting (82 citations) introduced a three-tier action knowledge representation that became foundational to subsequent work in the field. Complementary papers on collaborative language grounding and common ground establishment — each exceeding 50 citations — demonstrate her sustained focus on resolving the perceptual mismatches that inevitably arise when humans and robots co-inhabit shared environments. Her 2017 work on interactive learning of grounded verb semantics extended these contributions into richer semantic territory, showing how robots can acquire verb meaning through ongoing human collaboration. Collectively, with hundreds of citations across her core publications, She's research has meaningfully advanced the vision of robots as intuitive, language-responsive partners in real-world tasks.

Research Focus

Key Achievements

Top Papers

1. 1
   Back to the Blocks World: Learning New Actions through Situated Human-Robot Dialogue

   82 citations · 2014
2. 2
   Teaching Robots New Actions through Natural Language Instructions

   77 citations · 2014
3. 3
   Collaborative effort towards common ground in situated human-robot dialogue

   75 citations · 2014
4. 4
   Collaborative Language Grounding Toward Situated Human‐Robot Dialogue

   67 citations · 2016
5. 5
   Interactive Learning of Grounded Verb Semantics towards Human-Robot Communication

   51 citations · 2017
6. 6
   Probabilistic Labeling for Efficient Referential Grounding based on Collaborative Discourse

   16 citations · 2014
7. 7
   Program robots manufacturing tasks by natural language instructions

   14 citations · 2016
8. 8
   Perceptive feedback for natural language control of robotic operations

   10 citations · 2014
9. 9
   Modelling and Analysis of Natural Language Controlled Robotic Systems

   7 citations · 2014

Key Collaborators

Contact & Links