18 citations · 23 across the 11 of their papers we have counts for
11 papers
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…
ProxiTrak: Intelligent Enablement of Social Distancing & Contact Tracing for a Safer Workplace in the New Normal
Vivek Chandel, Snehasis Banerjee, Avik Ghose
This paper describes an innovative solution that enables the enterprises to bring their associates (or employees) back to physical workspaces for critical operations in a safe mann…
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…
Towards Wide Learning: Experiments in Healthcare
Snehasis Banerjee, Tanushyam Chattopadhyay, Swagata Biswas +4
In this paper, a Wide Learning architecture is proposed that attempts to automate the feature engineering portion of the machine learning (ML) pipeline. Feature engineering is wide…