1 citations · 3 across the 9 of their papers we have counts for
10 papers
VANDERER: Map-Free Exploration using Future-Aware and Visual-Curiosity-Guided Diffusion Policy
Venkata Naren Devarakonda, Raktim Gautam Goswami, Prashanth Krishnamurthy +1
Mobile agents require efficient exploration strategies to map unseen environments and autonomously plan tasks. Traditional methods rely on generating occupancy maps and optimizing…
Unifying Object-Centric World Models and Diffusion Policy: A Hierarchical Framework for Multi-Stage Robotic Tasks
Raktim Gautam Goswami, Prashanth Krishnamurthy, Yann LeCun +1
Visual world models have shown great potential in learning complex system dynamics. Recent advancements leverage these models as transition functions within Model Predictive Contro…
World Models for Learning Dexterous Hand-Object Interactions from Human Videos
Raktim Gautam Goswami, Amir Bar, David Fan +6
Modeling dexterous hand-object interactions is challenging as it requires understanding how subtle finger motions influence the environment through contact with objects. While rece…
OSVI-WM: One-Shot Visual Imitation for Unseen Tasks using World-Model-Guided Trajectory Generation
Raktim Gautam Goswami, Prashanth Krishnamurthy, Yann LeCun +1
Visual imitation learning enables robotic agents to acquire skills by observing expert demonstration videos. In the one-shot setting, the agent generates a policy after observing a…
RoboPEPP: Vision-Based Robot Pose and Joint Angle Estimation through Embedding Predictive Pre-Training
Raktim Gautam Goswami, Prashanth Krishnamurthy, Yann LeCun +1
Vision-based pose estimation of articulated robots with unknown joint angles has applications in collaborative robotics and human-robot interaction tasks. Current frameworks use ne…
Open-Architecture End-to-End System for Real-World Autonomous Robot Navigation
Venkata Naren Devarakonda, Ali Umut Kaypak, Raktim Gautam Goswami +4
Enabling robots to autonomously navigate unknown, complex, and dynamic real-world environments presents several challenges, including imperfect perception, partial observability, l…
FlashMix: Fast Map-Free LiDAR Localization via Feature Mixing and Contrastive-Constrained Accelerated Training
Raktim Gautam Goswami, Naman Patel, Prashanth Krishnamurthy +1
Map-free LiDAR localization systems accurately localize within known environments by predicting sensor position and orientation directly from raw point clouds, eliminating the need…
SALSA: Swift Adaptive Lightweight Self-Attention for Enhanced LiDAR Place Recognition
Raktim Gautam Goswami, Naman Patel, Prashanth Krishnamurthy +1
Large-scale LiDAR mappings and localization leverage place recognition techniques to mitigate odometry drifts, ensuring accurate mapping. These techniques utilize scene representat…
Data-Driven Deep Learning Based Feedback Linearization of Systems with Unknown Dynamics
Raktim Gautam Goswami, Prashanth Krishnamurthy, Farshad Khorrami
A methodology is developed to learn a feedback linearization (i.e., nonlinear change of coordinates and input transformation) using a data-driven approach for a single input contro…
Phase Aware Speech Enhancement using Realisation of Complex-valued LSTM
Raktim Gautam Goswami, Sivaganesh Andhavarapu, K Sri Rama Murty
Most of the deep learning based speech enhancement (SE) methods rely on estimating the magnitude spectrum of the clean speech signal from the observed noisy speech signal, either b…