4 citations · 4 across the 7 of their papers we have counts for
6 papers · 1 filter
A Hybrid Optimization Framework for Grasp Synthesis under Partial Observations
Wenzheng Zhang, Fahira Afzal Maken, Tin Lai +1
We propose a hybrid grasp synthesis framework that combines a learning-based Energy-Based Model (EBM) with an analytical Iterative Closest Point (ICP) method to generate robust gra…
Grasping by parallel shape matching
Wenzheng Zhang, Fahira Afzal Maken, Tin Lai +1
Grasping is essential in robotic manipulation, yet challenging due to object and gripper diversity and real-world complexities. Traditional analytic approaches often have long opti…
Stein Particle Filter for Nonlinear, Non-Gaussian State Estimation
Fahira Afzal Maken, Fabio Ramos, Lionel Ott
Estimation of a dynamical system's latent state subject to sensor noise and model inaccuracies remains a critical yet difficult problem in robotics. While Kalman filters provide th…
Stein ICP for Uncertainty Estimation in Point Cloud Matching
Fahira Afzal Maken, Fabio Ramos, Lionel Ott
Quantification of uncertainty in point cloud matching is critical in many tasks such as pose estimation, sensor fusion, and grasping. Iterative closest point (ICP) is a commonly us…
Estimating Motion Uncertainty with Bayesian ICP
Fahira Afzal Maken, Fabio Ramos, Lionel Ott
Accurate uncertainty estimation associated with the pose transformation between two 3D point clouds is critical for autonomous navigation, grasping, and data fusion. Iterative clos…
Speeding Up Iterative Closest Point Using Stochastic Gradient Descent
Fahira Afzal Maken, Fabio Ramos, Lionel Ott
Sensors producing 3D point clouds such as 3D laser scanners and RGB-D cameras are widely used in robotics, be it for autonomous driving or manipulation. Aligning point clouds produ…