262 citations · 881 across the 33 of their papers we have counts for
7 papers · 1 filter
LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimation
Keunhong Park, Arsalan Mousavian, Yu Xiang +1
Current 6D object pose estimation methods usually require a 3D model for each object. These methods also require additional training in order to incorporate new objects. As a resul…
Manipulation Trajectory Optimization with Online Grasp Synthesis and Selection
Lirui Wang, Yu Xiang, Dieter Fox
In robot manipulation, planning the motion of a robot manipulator to grasp an object is a fundamental problem. A manipulation planner needs to generate a trajectory of the manipula…
Scaling Local Control to Large-Scale Topological Navigation
Xiangyun Meng, Nathan Ratliff, Yu Xiang +1
Visual topological navigation has been revitalized recently thanks to the advancement of deep learning that substantially improves robot perception. However, the scalability and re…
Self-supervised 6D Object Pose Estimation for Robot Manipulation
Xinke Deng, Yu Xiang, Arsalan Mousavian +3
To teach robots skills, it is crucial to obtain data with supervision. Since annotating real world data is time-consuming and expensive, enabling robots to learn in a self-supervis…
The Best of Both Modes: Separately Leveraging RGB and Depth for Unseen Object Instance Segmentation
Christopher Xie, Yu Xiang, Arsalan Mousavian +1
In order to function in unstructured environments, robots need the ability to recognize unseen novel objects. We take a step in this direction by tackling the problem of segmenting…
PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking
Xinke Deng, Arsalan Mousavian, Yu Xiang +3
Tracking 6D poses of objects from videos provides rich information to a robot in performing different tasks such as manipulation and navigation. In this work, we formulate the 6D o…
Neural Autonomous Navigation with Riemannian Motion Policy
Xiangyun Meng, Nathan Ratliff, Yu Xiang +1
End-to-end learning for autonomous navigation has received substantial attention recently as a promising method for reducing modeling error. However, its data complexity, especiall…