activity
20182025
most citedLearning Implicit Sampling Distributions for Motion Planning

4 citations · 5 across the 12 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.RO2023★ 1 cited

VFAS-Grasp: Closed Loop Grasping with Visual Feedback and Adaptive Sampling

Pedro Piacenza, Jiacheng Yuan, Jinwook Huh +1

We consider the problem of closed-loop robotic grasping and present a novel planner which uses Visual Feedback and an uncertainty-aware Adaptive Sampling strategy (VFAS) to close t…

cs.RO2023

HIO-SDF: Hierarchical Incremental Online Signed Distance Fields

Vasileios Vasilopoulos, Suveer Garg, Jinwook Huh +2

A good representation of a large, complex mobile robot workspace must be space-efficient yet capable of encoding relevant geometric details. When exploring unknown environments, it…

cs.RO2023

Real-time Simultaneous Multi-Object 3D Shape Reconstruction, 6DoF Pose Estimation and Dense Grasp Prediction

Shubham Agrawal, Nikhil Chavan-Dafle, Isaac Kasahara +3

Robotic manipulation systems operating in complex environments rely on perception systems that provide information about the geometry (pose and 3D shape) of the objects in the scen…

cs.RO2023

RAMP: Hierarchical Reactive Motion Planning for Manipulation Tasks Using Implicit Signed Distance Functions

Vasileios Vasilopoulos, Suveer Garg, Pedro Piacenza +2

We introduce Reactive Action and Motion Planner (RAMP), which combines the strengths of sampling-based and reactive approaches for motion planning. In essence, RAMP is a hierarchic…

cs.RO2023

Pick2Place: Task-aware 6DoF Grasp Estimation via Object-Centric Perspective Affordance

Zhanpeng He, Nikhil Chavan-Dafle, Jinwook Huh +2

The choice of a grasp plays a critical role in the success of downstream manipulation tasks. Consider a task of placing an object in a cluttered scene; the majority of possible gra…