Research

AI that perceives, reasons about and acts in physical space

RESEARCH DIRECTION

Structured Spatial World Models

Drones and robots sense the world, build accurate 3D world models, and use those models to predict, decide and act. What they learn from acting flows back to update the model.

Structured Spatial World Models Flagship direction: Autonomous mapping agents
  1. Sensing · Autonomy See the world now
    • Image–LiDAR co-serialization
    • Resident space object (RSO) tiny-object detection
    • Pedestrian trajectory sensing
    • Quality-aware drone mapping
  2. 3D World Model Know what the world looks like
    • LoD1 to LoD2 building reconstruction
    • Semantic-first BIM/IFC digital twins
    • Single-view 3D reconstruction with diffusion priors (GeoPriorPC)
    • Diffusion models for RSO imagery
    • Gaussian splatting for 3D city models
  3. Prediction · Action Predict what happens before acting
    • Spatial graph + LLM agents
    • Pedestrian and CFD simulation
    • Vision-language models for railways
    • Autonomous mapping agents
    • 3D-grounded vision-language-action models

Results of action feed back into sensing, closing the loop.

  • Infrastructure · Digital twinsMaps, BIM, power lines and rail
  • Mobility · Public healthDelivery robots, pedestrian flow, disease modelling
  • SpaceSpace situational awareness (K-SSA)
NSERC Discovery: Embodied Spatial IntelligenceThe program that supports all of the lab's research
Q-Drone UWB positioning system and test sites

SEE THE WORLD NOW

Sensing · Autonomy

Drones, mobile mappers and satellites collect LiDAR, imagery and orbital observations. We fuse these sensors and detect what matters in them, from tiny objects in orbit to people on a sidewalk.

TOPICS

Image–LiDAR co-serialization
OCI C2C · Aethon Jacob Yoo, Youssef Korny
Resident space object (RSO) tiny-object detection
K-SSA, with Prof. Regina Lee's lab Youssef Beshir
Pedestrian trajectory sensing
OCI C2C, with Hanyang University Mohammadjavad Ghorbanalivakili
Quality-aware drone mapping Looking for students

KEY PAPERS

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3D building models from airborne LiDAR

KNOW WHAT THE WORLD LOOKS LIKE

3D World Model

We turn sensor data into accurate, structured 3D models of cities and infrastructure, from building geometry to semantic BIM, so machines can reason about space.

TOPICS

LoD1 to LoD2 building reconstruction Mohammad Moein Sheikholeslami
Semantic-first BIM/IFC digital twins
with Yonsei University Md. Ehsan Shahmi Chowdhury
Single-view 3D reconstruction with diffusion priors (GeoPriorPC)
NSERC Discovery Youssef Korny
Diffusion models for RSO imagery
K-SSA, with Prof. Regina Lee's lab Merna Tamer Youssef
Gaussian splatting for 3D city models Looking for students

KEY PAPERS

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Simulating a sidewalk delivery robot in a campus digital twin

PREDICT WHAT HAPPENS BEFORE ACTING

Prediction · Action

With a world model in hand, agents can plan, simulate and act. We build agents that map on their own, connect spatial graphs to language models, and simulate how people and vehicles move.

TOPICS

Spatial graph + LLM agents
ORF-RE Md. Ehsan Shahmi Chowdhury
Pedestrian and CFD simulation
ORF-RE · NSERC CREATE SMART Mohammadjavad Ghorbanalivakili
Vision-language models for railways Mohammadjavad Ghorbanalivakili, Ashley Varghese
Autonomous mapping agents Looking for students
3D-grounded vision-language-action models Looking for students

KEY PAPERS

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Projects

Funded projects, current and past

3DMMAI 3DMMAI 3D Mobile Mapping Artificial Intelligence (3DMMAI), is supported by the NSERC (Natural Sciences and Engineering Research Council of Canada) Collaborative Research Development (CRD) program and Teledyne Optech in… Layout SLAM Layout SLAM In this project, we study the role of high-level geometric topological cues such as 3D primitive representation of indoor corridors to improve the performance of simultaneous localization and modelling (SLAM) using a… OnTRAC OnTRAC Ontario Train Autonomy Collaboration (OnTRAC) Project (April 2019 – March 2021) is to develop and demonstrate a prototype system of a high-performance Obstacle Detection, Classification and Tracking (ODCT) solution to… Progressive 3D City Modelling Progressive 3D City Modelling Dr. Jaewoo Jung published his research work on 3D building modeling methods in the ISPRS Journal ( doi.org/10.1016/j.isprsjprs.2019.01.003) . This journal suggests an innovative method for automatically updating an… Q-Drone Q-Drone Q-Drone is a research-oriented unmanned aerial vehicle (UAV), which provides objective path planning to meet the requirements of critical infrastructure mapping such as the complete and homogeneous quality of…

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Research Collaborators

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