Publications (14)
Online Estimation and Manipulation of Articulated Objects
Russell Buchanan, Adrian Röfer, João Moura +2
From refrigerators to kitchen drawers, humans interact with articulated objects effortlessly every day while completing household chores. For automating these tasks, service robots…
3D Freehand Ultrasound using Visual Inertial and Deep Inertial Odometry for Measuring Patellar Tracking
Russell Buchanan, S. Jack Tu, Marco Camurri +2
Patellofemoral joint (PFJ) issues affect one in four people, with 20% experiencing chronic knee pain despite treatment. Poor outcomes and pain after knee replacement surgery are of…
BayesContact: Uncertain Pose Estimation via Visuo-Tactile Proposals and Simulation-based Inference
Aditya Kamireddypalli, Matias Mattamala, Joao Moura +3
Contact-rich manipulation requires pose estimates that are often more accurate than what depth-only sensing provides. Existing methods, relying on vision and contact, employ costly…
iMHS: An Incremental Multi-Hypothesis Smoother
Fan Jiang, Varun Agrawal, Russell Buchanan +2
State estimation of multi-modal hybrid systems is an important problem with many applications in the field robotics. However, incorporating discrete modes in the estimation process…
Online Estimation of Articulated Objects with Factor Graphs using Vision and Proprioceptive Sensing
Russell Buchanan, Adrian Röfer, João Moura +2
From dishwashers to cabinets, humans interact with articulated objects every day, and for a robot to assist in common manipulation tasks, it must learn a representation of articula…
Deep IMU Bias Inference for Robust Visual-Inertial Odometry with Factor Graphs
Russell Buchanan, Varun Agrawal, Marco Camurri +2
Visual Inertial Odometry (VIO) is one of the most established state estimation methods for mobile platforms. However, when visual tracking fails, VIO algorithms quickly diverge due…