Liam Paull

About

Liam Paull is a robotics researcher whose work spans simultaneous localization and mapping (SLAM), multi-robot systems, semantic scene understanding, and autonomous robot perception. His research career traces a compelling arc from foundational contributions to multi-robot SLAM — including decentralized neural network approaches and communication-constrained cooperative mapping for autonomous underwater vehicles — toward increasingly sophisticated representations of robot knowledge and perception. Paull has made significant contributions to graph-based SLAM, developing methods for object-based mapping, active exploration, and computational efficiency through node removal and edge sparsification. His work on ontologies for autonomous robots reflects a broader commitment to principled knowledge representation, contributing to IEEE's Working Group on Robotics and Automation standards. More recently, his research has pushed toward the frontier of deep learning and foundation models in robotics. His work on Deep Active Localization introduced end-to-end differentiable frameworks for pose disambiguation, while ConceptGraphs — his most cited work with 178 citations — demonstrated how large vision-language models can enable open-vocabulary 3D scene understanding for robot planning, representing a landmark contribution to embodied AI. With over 690 citations across his most recognized work, Paull's research consistently bridges theoretical rigor with practical robotic applications.

Research Focus

Key Achievements

Top Papers

1. 1
   ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning

   178 citations · 2024
2. 2
   Communication-constrained multi-AUV cooperative SLAM

   108 citations · 2015
3. 3
   SLAM with objects using a nonparametric pose graph

   82 citations · 2016
4. 4
   Neural Network-Based Multiple Robot Simultaneous Localization and Mapping

   66 citations · 2011
5. 5
   Group Mapping: A Topological Approach to Map Merging for Multiple Robots

   57 citations · 2014
6. 6
   Requirements for building an ontology for autonomous robots

   44 citations · 2016
7. 7
   Information-based Active SLAM via topological feature graphs

   43 citations · 2016
8. 8
   Deep Active Localization

   40 citations · 2019
9. 9
   Decoupled, consistent node removal and edge sparsification for graph-based SLAM

   38 citations · 2016
10. 10
    Towards an Ontology for Autonomous Robots

    38 citations · 2012

Key Collaborators

Contact & Links