18 citations · 23 across the 11 of their papers we have counts for
9 papers · 1 filter
LLM-Powered Interactive Robotic Action Synthesis from Multimodal Speech, Gestures, and Music
Snehasis Banerjee, Ranjan Dasgupta
The quest for intuitive and natural human-robot interaction (HRI) remains a significant challenge in robotics. Traditional methods often rely on rigid, pre-programmed commands that…
A Modular Vision-Language-Action Robotics Framework for Indoor Environments
Anindya Jana, Snehasis Banerjee, Arup Sadhu +1
This paper presents an integrated system for the CMU Vision-Language-Action (VLA) Challenge, designed to enable an autonomous agent to perform complex tasks based on natural langua…
Anticipate, Adapt, Act: A Hybrid Framework for Task Planning
Nabanita Dash, Ayush Kaura, Shivam Singh +4
Anticipating and adapting to failures is a key capability robots need to collaborate effectively with humans in complex domains. This continues to be a challenge despite the impres…
Anticipate & Collab: Data-driven Task Anticipation and Knowledge-driven Planning for Human-robot Collaboration
Shivam Singh, Karthik Swaminathan, Raghav Arora +6
An agent assisting humans in daily living activities can collaborate more effectively by anticipating upcoming tasks. Data-driven methods represent the state of the art in task ant…
CLIPGraphs: Multimodal Graph Networks to Infer Object-Room Affinities
Ayush Agrawal, Raghav Arora, Ahana Datta +5
This paper introduces a novel method for determining the best room to place an object in, for embodied scene rearrangement. While state-of-the-art approaches rely on large language…
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…
Talk-to-Resolve: Combining scene understanding and spatial dialogue to resolve granular task ambiguity for a collocated robot
Pradip Pramanick, Chayan Sarkar, Snehasis Banerjee +1
The utility of collocating robots largely depends on the easy and intuitive interaction mechanism with the human. If a robot accepts task instruction in natural language, first, it…