116 citations · 1.1k across the 96 of their papers we have counts for
6 papers · 1 filter
Quantifying VIO Uncertainty
Stephanie Tsuei, Stefano Soatto
We compute the uncertainty of XIVO, a monocular visual-inertial odometry system based on the Extended Kalman Filter, in the presence of Gaussian noise, drift, and attribution error…
Learned Uncertainty Calibration for Visual Inertial Localization
Stephanie Tsuei, Stefano Soatto, Paulo Tabuada +1
The widely-used Extended Kalman Filter (EKF) provides a straightforward recipe to estimate the mean and covariance of the state given all past measurements in a causal and recursiv…
SABER: Data-Driven Motion Planner for Autonomously Navigating Heterogeneous Robots
Alexander Schperberg, Stephanie Tsuei, Stefano Soatto +1
We present an end-to-end online motion planning framework that uses a data-driven approach to navigate a heterogeneous robot team towards a global goal while avoiding obstacles in…
Risk-Averse MPC via Visual-Inertial Input and Recurrent Networks for Online Collision Avoidance
Alexander Schperberg, Kenny Chen, Stephanie Tsuei +5
In this paper, we propose an online path planning architecture that extends the model predictive control (MPC) formulation to consider future location uncertainties for safer navig…
Robust Inference for Visual-Inertial Sensor Fusion
Konstantine Tsotsos, Alessandro Chiuso, Stefano Soatto
Inference of three-dimensional motion from the fusion of inertial and visual sensory data has to contend with the preponderance of outliers in the latter. Robust filtering deals wi…
Observability, Identifiability and Sensitivity of Vision-Aided Navigation
Joshua Hernandez, Konstantine Tsotsos, Stefano Soatto
We analyze the observability of motion estimates from the fusion of visual and inertial sensors. Because the model contains unknown parameters, such as sensor biases, the problem i…