activity
20202026
most citedRobot Learning of Mobile Manipulation with Reachability Behavior Priors

45 citations · 47 across the 11 of their papers we have counts for

collaborators

13 papers

cs.AI2026

Think Twice, Act Once: Verifier-Guided Action Selection For Embodied Agents

Nishad Singhi, Christian Bialas, Snehal Jauhri +4

Building generalist embodied agents capable of solving complex real-world tasks remains a fundamental challenge in AI. Multimodal Large Language Models (MLLMs) have significantly a…

cs.RO2026

Whole-Body Mobile Manipulation using Offline Reinforcement Learning on Sub-optimal Controllers

Snehal Jauhri, Vignesh Prasad, Georgia Chalvatzaki

Mobile Manipulation (MoMa) of articulated objects, such as opening doors, drawers, and cupboards, demands simultaneous, whole-body coordination between a robot's base and arms. Cla…

cs.RO2026

MolmoB0T: Large-Scale Simulation Enables Zero-Shot Manipulation

Abhay Deshpande, Maya Guru, Rose Hendrix +23

A prevailing view in robot learning is that simulation alone is not enough; effective sim-to-real transfer is widely believed to require at least some real-world data collection or…

cs.RO2026

MolmoSpaces: A Large-Scale Open Ecosystem for Robot Navigation and Manipulation

Yejin Kim, Wilbert Pumacay, Omar Rayyan +23

Deploying robots at scale demands robustness to the long tail of everyday situations. The countless variations in scene layout, object geometry, and task specifications that charac…

cs.RO2025

UniFField: A Generalizable Unified Neural Feature Field for Visual, Semantic, and Spatial Uncertainties in Any Scene

Christian Maurer, Snehal Jauhri, Sophie Lueth +1

Comprehensive visual, geometric, and semantic understanding of a 3D scene is crucial for successful execution of robotic tasks, especially in unstructured and complex environments.…

cs.CV2025

2HandedAfforder: Learning Precise Actionable Bimanual Affordances from Human Videos

Marvin Heidinger, Snehal Jauhri, Vignesh Prasad +1

When interacting with objects, humans effectively reason about which regions of objects are viable for an intended action, i.e., the affordance regions of the object. They can also…

cs.CV2024

6DOPE-GS: Online 6D Object Pose Estimation using Gaussian Splatting

Yufeng Jin, Vignesh Prasad, Snehal Jauhri +2

Efficient and accurate object pose estimation is an essential component for modern vision systems in many applications such as Augmented Reality, autonomous driving, and robotics.…

cs.RO2023

Active-Perceptive Motion Generation for Mobile Manipulation

Snehal Jauhri, Sophie Lueth, Georgia Chalvatzaki

Mobile Manipulation (MoMa) systems incorporate the benefits of mobility and dexterity, due to the enlarged space in which they can move and interact with their environment. However…

cs.RO2023★ 1 cited

Learning Any-View 6DoF Robotic Grasping in Cluttered Scenes via Neural Surface Rendering

Snehal Jauhri, Ishikaa Lunawat, Georgia Chalvatzaki

A significant challenge for real-world robotic manipulation is the effective 6DoF grasping of objects in cluttered scenes from any single viewpoint without the need for additional…

cs.RO2022★ 1 cited

Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction

Puze Liu, Kuo Zhang, Davide Tateo +4

Safety is a crucial property of every robotic platform: any control policy should always comply with actuator limits and avoid collisions with the environment and humans. In reinfo…

cs.RO2022

Regularized Deep Signed Distance Fields for Reactive Motion Generation

Puze Liu, Kuo Zhang, Davide Tateo +3

Autonomous robots should operate in real-world dynamic environments and collaborate with humans in tight spaces. A key component for allowing robots to leave structured lab and man…

cs.RO2022★ 45 cited

Robot Learning of Mobile Manipulation with Reachability Behavior Priors

Snehal Jauhri, Jan Peters, Georgia Chalvatzaki

Mobile Manipulation (MM) systems are ideal candidates for taking up the role of a personal assistant in unstructured real-world environments. Among other challenges, MM requires ef…

cs.RO2020

Interactive Imitation Learning in State-Space

Snehal Jauhri, Carlos Celemin, Jens Kober

Imitation Learning techniques enable programming the behavior of agents through demonstrations rather than manual engineering. However, they are limited by the quality of available…