4 citations · 6 across the 9 of their papers we have counts for
6 papers · 1 filter
HDFlow: Hierarchical Diffusion-Flow Planning for Long-horizon Tasks
Nandiraju Gireesh, Yuanliang Ju, Chaoyi Xu +3
Recent advances in generative models have shown promise in generating behavior plans for long-horizon, sparse reward tasks. While these approaches have achieved promising results,…
Watch Less, Feel More: Sim-to-Real RL for Generalizable Articulated Object Manipulation via Motion Adaptation and Impedance Control
Tan-Dzung Do, Nandiraju Gireesh, Jilong Wang +1
Articulated object manipulation poses a unique challenge compared to rigid object manipulation as the object itself represents a dynamic environment. In this work, we present a nov…
GAMMA: Graspability-Aware Mobile MAnipulation Policy Learning based on Online Grasping Pose Fusion
Jiazhao Zhang, Nandiraju Gireesh, Jilong Wang +5
Mobile manipulation constitutes a fundamental task for robotic assistants and garners significant attention within the robotics community. A critical challenge inherent in mobile m…
Sequence-Agnostic Multi-Object Navigation
Nandiraju Gireesh, Ayush Agrawal, Ahana Datta +4
The Multi-Object Navigation (MultiON) task requires a robot to localize an instance (each) of multiple object classes. It is a fundamental task for an assistive robot in a home or…
Spatial Relation Graph and Graph Convolutional Network for Object Goal Navigation
D. A. Sasi Kiran, Kritika Anand, Chaitanya Kharyal +7
This paper describes a framework for the object-goal navigation task, which requires a robot to find and move to the closest instance of a target object class from a random startin…
Object Goal Navigation using Data Regularized Q-Learning
Nandiraju Gireesh, D. A. Sasi Kiran, Snehasis Banerjee +3
Object Goal Navigation requires a robot to find and navigate to an instance of a target object class in a previously unseen environment. Our framework incrementally builds a semant…