90 citations · 115 across the 14 of their papers we have counts for
13 papers · 1 filter
GHOST: Hierarchical Sub-Goal Policies for Generalizing Robot Manipulation
Sriram Krishna, Ben Eisner, Haotian Zhan +5
We present GHOST, a framework for learning visuomotor manipulation policies that generalize beyond the training distribution. GHOST factorizes control into (i) a high-level policy…
Planning from Point Clouds over Continuous Actions for Multi-object Rearrangement
Kallol Saha, Amber Li, Angela Rodriguez-Izquierdo +4
Long-horizon planning for robot manipulation is a challenging problem that requires reasoning about the effects of a sequence of actions on a physical 3D scene. While traditional t…
Learn from What We HAVE: History-Aware VErifier that Reasons about Past Interactions Online
Yishu Li, Xinyi Mao, Ying Yuan +3
We introduce a novel History-Aware VErifier (HAVE) to disambiguate uncertain scenarios online by leveraging past interactions. Robots frequently encounter visually ambiguous object…
Non-rigid Relative Placement through 3D Dense Diffusion
Eric Cai, Octavian Donca, Ben Eisner +1
The task of "relative placement" is to predict the placement of one object in relation to another, e.g. placing a mug onto a mug rack. Through explicit object-centric geometric rea…
FlowBotHD: History-Aware Diffuser Handling Ambiguities in Articulated Objects Manipulation
Yishu Li, Wen Hui Leng, Yiming Fang +2
We introduce a novel approach for manipulating articulated objects which are visually ambiguous, such doors which are symmetric or which are heavily occluded. These ambiguities can…
Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks
Ben Eisner, Yi Yang, Todor Davchev +3
Many robot manipulation tasks can be framed as geometric reasoning tasks, where an agent must be able to precisely manipulate an object into a position that satisfies the task from…
On Time-Indexing as Inductive Bias in Deep RL for Sequential Manipulation Tasks
M. Nomaan Qureshi, Ben Eisner, David Held
While solving complex manipulation tasks, manipulation policies often need to learn a set of diverse skills to accomplish these tasks. The set of skills is often quite multimodal -…
FlowBot++: Learning Generalized Articulated Objects Manipulation via Articulation Projection
Harry Zhang, Ben Eisner, David Held
Understanding and manipulating articulated objects, such as doors and drawers, is crucial for robots operating in human environments. We wish to develop a system that can learn to…
TAX-Pose: Task-Specific Cross-Pose Estimation for Robot Manipulation
Chuer Pan, Brian Okorn, Harry Zhang +2
How do we imbue robots with the ability to efficiently manipulate unseen objects and transfer relevant skills based on demonstrations? End-to-end learning methods often fail to gen…
FlowBot3D: Learning 3D Articulation Flow to Manipulate Articulated Objects
Ben Eisner, Harry Zhang, David Held
We explore a novel method to perceive and manipulate 3D articulated objects that generalizes to enable a robot to articulate unseen classes of objects. We propose a vision-based sy…
Self-supervised Transparent Liquid Segmentation for Robotic Pouring
Gautham Narayan Narasimhan, Kai Zhang, Ben Eisner +2
Liquid state estimation is important for robotics tasks such as pouring; however, estimating the state of transparent liquids is a challenging problem. We propose a novel segmentat…
Robotic Grasping through Combined Image-Based Grasp Proposal and 3D Reconstruction
Daniel Yang, Tarik Tosun, Ben Eisner +2
We present a novel approach to robotic grasp planning using both a learned grasp proposal network and a learned 3D shape reconstruction network. Our system generates 6-DOF grasps f…
Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner
Tarik Tosun, Eric Mitchell, Ben Eisner +6
We present a novel method enabling robots to quickly learn to manipulate objects by leveraging a motion planner to generate "expert" training trajectories from a small amount of hu…