CMU projects.

Quality inspection of complex, custom 3D-printed parts for aviation and manufacturing applications. Coverage planning for a robot arm and turntable so a line-scanner can fully scan an arbitrary object.

Software perception for a suitcase-sized lunar rover designed to autonomously search for evidence of water ice near the lunar pole. Worked on the stereo reconstruction pipeline so failures could be debugged offline.

A functional three-legged robot dog built to study how a tripod's natural gait compares to a trajectory-optimized gait in cost of transport, on the same hardware, with stability actively managed at every step.

Six projects from CMU's graduate computer vision course: spatial pyramid scene classification, augmented reality with planar homographies, Lucas-Kanade tracking, two-view 3D reconstruction, neural networks for character recognition, and photometric stereo.

Grading diabetic retinopathy from retinal photographs with AlexNet, ResNet50 and VGG16. Binary detection reached 98% validation accuracy in our evaluation, while five-class severity grading reached 80%. We also explored a cascade of binary classifiers.

Three searches over three different kinds of space: a grid, where the trick is choosing which goal to aim at; a continuous high-DOF configuration space you can only sample; and a space of logical facts where states are sets of conditions.

Lucas-Kanade tracking is a nonlinear least-squares problem solved once per frame, so which optimizer should solve it? Gradient descent, Newton, Gauss-Newton, BFGS and Levenberg-Marquardt raced against each other, explaining why the 1981 paper chose what it did.

Four takes on the same problem: particle filter localization, EKF-SLAM, SLAM as a sparse least-squares problem, and dense SLAM with point-based fusion. From thousands of samples, to a single Gaussian, to batch linear algebra, to raw geometry.

Setting up ORB-SLAM2, RTAB-Map and Google Cartographer in ROS and benchmarking them against the same TUM data and four driving scenarios we generated in the CARLA simulator. Every system degraded in dynamic environments; the interesting part is how differently.