University of Colorado Boulder · Department of Computer Science
We build robots that perceive, navigate, and act in complex real-world environments. Our work spans perception, SLAM, field robotics, and vision-language-action models.
We develop diffusion-based generative models that synthesize 3D occupancy and semantic geometry from partial observations, enabling robots to predict and plan through unseen space.
Project page → GitHub →From the SUN-Spot dataset to Spatial-LLaVA, we advance how robots understand spatial language, ground referring expressions in visual scenes, and navigate from natural language instructions.
Project page →Building datasets and algorithms for multi-robot data association and collaborative perception in heterogeneous robot teams.
Project page →Pioneering the use of mmWave RADAR as a primary perception modality for robotics, from datasets to dense mapping in degraded visual conditions.
Project page →
Multi-agent autonomy with RADAR-based localization for exploring underground environments. 3rd place, $500K prize.

Immersive mixed reality interfaces for supervision and telepresence with outdoor field robotic systems.

Determining location, direction, intensity, and color of illuminants using physically-based rendering models.

Terrain-aware model predictive control, game-theoretic lane changing, and high-speed autonomous navigation through challenging terrain.

Autonomous multi-agent systems for targeted seed planting in degraded rangelands.

Low-cost radar sensors for field-based water level monitoring with sub-centimeter accuracy.

Online self-calibration, Bayesian optimization for ICP and Kalman filters, and robust SLAM pipelines.

Autonomous endoscope navigation and disease-robust cardiac MRI segmentation.
We release the data behind our research — radar, lidar, visual-inertial, and RGB-D benchmarks collected in mines, campuses, deserts, and competition courses.

52 sequences of 3D FMCW radar, lidar, and IMU in mines and urban environments.

Improved ground truth and RGB-D extension of ColoRadar.
Visual-inertial odometry with onboard illumination in dark environments.

Multi-robot data association across CU Boulder campus.

Seasonal field robotics data from the Canyonlands region.

Sensor data from the DARPA SubT Finals competition course.

Associate Professor, Department of Computer Science
Research focuses on robotics, computer vision, and machine learning. Leads work on robust perception and navigation for robots operating in challenging real-world environments.





