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Found 18 papers, 2 papers with code
On the Quotient Representation for the Essential Manifold
The essential matrix, which encodes the epipolar constraint between points in two projective views, is a cornerstone of modern computer vision.
A Metric Parametrization for Trifocal Tensors With Non-Colinear Pinholes
In this work, we investigate a new parametrization of the trifocal tensor for calibrated cameras with non-colinear pinholes obtained from a quotient Riemannian manifold.
A Factorization Approach to Inertial Affine Structure from Motion
We consider the problem of reconstructing a 3-D scene from a moving camera with high frame rate using the affine projection model.
Fast Multi-Image Matching via Density-Based Clustering
We consider the problem of finding consistent matches across multiple images.
Distributed and Consistent Multi-Image Feature Matching via QuickMatch
The centralized QuickMatch algorithm is compared to other standard matching algorithms, while the Distributed QuickMatch algorithm is compared to the centralized algorithm in terms of preservation of match consistency.
Statistical Outlier Identification in Multi-robot Visual SLAM using Expectation Maximization
This paper introduces a novel and distributed method for detecting inter-map loop closure outliers in simultaneous localization and mapping (SLAM).
Bearing-Based Formation Control with Optimal Motion Trajectory
We form and solve a nonlinear optimization problem with the sum of path lengths of the agent trajectories as the objective and subject to the original equilibria and global convergence conditions for formation control.
Koopman pose predictions for temporally consistent human walking estimations
We tackle the problem of tracking the human lower body as an initial step toward an automatic motion assessment system for clinical mobility evaluation, using a multimodal system that combines Inertial Measurement Unit (IMU) data, RGB images, and point cloud depth measurements.
Learning Signal Temporal Logic through Neural Network for Interpretable Classification
Machine learning techniques using neural networks have achieved promising success for time-series data classification.
Essential Matrix Estimation using Convex Relaxations in Orthogonal Space
We introduce a novel method to estimate the essential matrix for two-view Structure from Motion (SfM).
Control-Based Planning over Probability Mass Function Measurements via Robust Linear Programming
Using the strong duality of linear programs (LPs) and robust optimization, we convert the optimization problem to a linear program that can be efficiently solved offline.
Distance-coupling as an Approach to Position and Formation Control
We apply this method to the homing problem and prove Lyapunov stability with and without anchor placement error; defining bounds on the region of attraction when the anchors are linearly transformed from their desired positions.
Interpretable Generative Adversarial Imitation Learning
Imitation learning methods have demonstrated considerable success in teaching autonomous systems complex tasks through expert demonstrations.
Multi-class Temporal Logic Neural Networks
Time-series data can represent the behaviors of autonomous systems, such as drones and self-driving cars.
Lyapunov Neural Network with Region of Attraction Search
Deep learning methods have been widely used in robotic applications, making learning-enabled control design for complex nonlinear systems a promising direction.
Designing Robust Linear Output Feedback Controller based on CLF-CBF framework via Linear~Programming(LP-CLF-CBF)
We consider the problem of designing output feedback controllers that use measurements from a set of landmarks to navigate through a cell-decomposable environment using duality, Control Lyapunov and Barrier Functions (CLF, CBF), and Linear Programming.
Spline Trajectory Tracking and Obstacle Avoidance for Mobile Agents via Convex Optimization
We propose an output feedback control-based motion planning technique for agents to enable them to converge to a specified polynomial trajectory while imposing a set of safety constraints on our controller to avoid collisions within the free configuration space (polygonal environment).
Rotational Outlier Identification in Pose Graphs Using Dual Decomposition
In the last few years, there has been an increasing trend to consider Structure from Motion (SfM, in computer vision) and Simultaneous Localization and Mapping (SLAM, in robotics) problems from the point of view of pose averaging (also known as global SfM, in computer vision) or Pose Graph Optimization (PGO, in robotics), where the motion of the camera is reconstructed by considering only relative rigid body transformations instead of including also 3-D points (as done in a full Bundle Adjustment).
