5 citations · 13 across the 40 of their papers we have counts for
15 papers · 1 filter
TGrasp6D: Task-Informed Vision-Language Priors and Pose Refinement enable Zero-Shot Task-Oriented 6DoF Grasping
Manav Kulshrestha, Apoorva Vashisth, Damon Conover +1
Task-Oriented Grasping (TOG) has emerged as an important skill for purposeful robotic manipulation. Given the task of using a knife to "slice bread," a robot must choose to grasp f…
Emergence, Not Bandwidth: Physical Coupling and the Limits of Learned Multi-Agent Communication
Mihir Chauhan, Aniket Bera
Rate-limited multi-agent teams raise three questions the emergent-communication literature has answered only empirically: what an optimal message should encode, what compression co…
Faster Visuomotor Policy Learning on Action Manifolds via Riemannian MeanFlow
S. Talha Bukhari, Austin Garrett, Yi Wei +3
Visuomotor policies learn a direct map from raw sensory observations to robot action sequences. Policies based on Diffusion and Flow Matching capture the multimodal distribution ov…
Noctif3R: Feed-Forward Monocular Real-Time SLAM for Photon-Limited Scenes on Embedded Hardware
Mihir Chauhan, Aditya Uday Abhang, Kevin Biju Mathew +1
Robots carrying out tasks in dark environments need to localize from a single RGB camera, in light so low that the per-pixel signal approaches the sensor's own noise, on a power-co…
HEROIC: Heterogeneous Evidential Reasoning for Open-Vocabulary Identification and Cross-Robot Collaboration
Mihir Chauhan, Aarav Jain, Addison Zucek +3
Multi-agent heterogeneous air-ground robot teams are attractive for open world search, with applications for reconnaissance, urban search and rescue missions (USAR), disaster respo…
Latent Energy Action Planning with World Models
Phu Pham, Aniket Bera
Latent world models support efficient model predictive control from high-dimensional observations, yet optimizing a single learned latent objective can favor action sequences whose…
Fast Generative Grasping via Lie Group-Constrained MeanFlow
S. Talha Bukhari, Yi Wei, Ruiqi Ni +2
Grasp synthesis is a core task in robotic manipulation, for which the solution typically forms a multimodal distribution rather than a point estimate. Generative robotic grasping a…
COLMAR: Cooperative View Policy Learning for Multi-Agent Active 3D Reconstruction
Phu Pham, Damon Conover, Aniket Bera
Active 3D reconstruction requires selecting informative viewpoints under limited sensing budgets. In multi-agent settings, coordination inefficiencies such as redundant observation…
PoseShield: Neural Collision Fields for Human Self-Collision Resolution
Zhengyuan Li, Zeyun Deng, Yifan Shen +7
Self-collision remains a persistent challenge in SMPL-based human pose estimation and motion generation. Under extreme articulations or stochastic motion synthesis, generated meshe…
LatentMimic: Terrain-Adaptive Locomotion via Latent Space Imitation
Zhiquan Wang, Yunyu Liu, Dipam Patel +3
Developing natural and diverse locomotion controllers for quadruped robots that can adapt to complex terrains while preserving motion style remains a significant challenge. Existin…
Sketch2Colab: Sketch-Conditioned Multi-Human Animation via Controllable Flow Distillation
Divyanshu Daiya, Aniket Bera
We present Sketch2Colab, which turns storyboard-style 2D sketches into coherent, object-aware 3D multi-human motion with fine-grained control over agents, joints, timing, and conta…
Operator Learning Using Weak Supervision from Walk-on-Spheres
Hrishikesh Viswanath, Hong Chul Nam, Xi Deng +3
Training neural PDE solvers is often bottlenecked by expensive data generation or unstable physics-informed neural network (PINN) involving challenging optimization landscapes due…
Mollified Value Learning
Hrishikesh Viswanath, Juanwu Lu, S. Talha Bukhari +4
Offline goal-conditioned reinforcement learning (GCRL) learns goal-reaching behaviors from static datasets, but accurate value estimation remains challenging under limited state-ac…
HCVR Scene Generation: High Compatibility Virtual Reality Environment Generation for Extended Redirected Walking
Yiran Zhang, Xingpeng Sun, Aniket Bera
Natural walking enhances immersion in virtual environments (VEs), but physical space limitations and obstacles hinder exploration, especially in large virtual scenes. Redirected Wa…
I-Scene: 3D Instance Models are Implicit Generalizable Spatial Learners
Lu Ling, Yunhao Ge, Yichen Sheng +1
Generalization remains the central challenge for interactive 3D scene generation. Existing learning-based approaches ground spatial understanding in limited scene dataset, restrict…