GAMMA: Graspability-Aware Mobile MAnipulation Policy Learning based on Online Grasping Pose Fusion

no code implementations • 27 Sep 2023 • Jiazhao Zhang, Nandiraju Gireesh, Jilong Wang, Xiaomeng Fang, Chaoyi Xu, Weiguang Chen, Liu Dai, He Wang

Mobile manipulation constitutes a fundamental task for robotic assistants and garners significant attention within the robotics community.

Sequence-Agnostic Multi-Object Navigation

no code implementations • 10 May 2023 • Nandiraju Gireesh, Ayush Agrawal, Ahana Datta, Snehasis Banerjee, Mohan Sridharan, Brojeshwar Bhowmick, Madhava Krishna

The Multi-Object Navigation (MultiON) task requires a robot to localize an instance (each) of multiple object classes.

Deep Reinforcement Learning Object

Spatial Relation Graph and Graph Convolutional Network for Object Goal Navigation

no code implementations • 27 Aug 2022 • D. A. Sasi Kiran, Kritika Anand, Chaitanya Kharyal, Gulshan Kumar, Nandiraju Gireesh, Snehasis Banerjee, Ruddra dev Roychoudhury, Mohan Sridharan, Brojeshwar Bhowmick, Madhava Krishna

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 starting position.

Bayesian Inference Object +2

Object Goal Navigation using Data Regularized Q-Learning

no code implementations • 27 Aug 2022 • Nandiraju Gireesh, D. A. Sasi Kiran, Snehasis Banerjee, Mohan Sridharan, Brojeshwar Bhowmick, Madhava Krishna

Our framework incrementally builds a semantic map of the environment over time, and then repeatedly selects a long-term goal ('where to go') based on the semantic map to locate the target object instance.

Data Augmentation Deep Reinforcement Learning +3

XRayGAN: Consistency-preserving Generation of X-ray Images from Radiology Reports

no code implementations • 17 Jun 2020 • Xingyi Yang, Nandiraju Gireesh, Eric Xing, Pengtao Xie

To address this problem, we develop methods to generate view-consistent, high-fidelity, and high-resolution X-ray images from radiology reports to facilitate radiology training of medical students.