Zobrazeno 1 - 10
of 142
pro vyhledávání: '"Sridharan, Mohan"'
Autor:
Singh, Shivam, Swaminathan, Karthik, Arora, Raghav, Singh, Ramandeep, Datta, Ahana, Das, Dipanjan, Banerjee, Snehasis, Sridharan, Mohan, Krishna, Madhava
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 anticipation, planning, and related problems, but these methods are resou
Externí odkaz:
http://arxiv.org/abs/2404.03587
Autor:
Kim, Oliver, Sridharan, Mohan
Landmarks are facts or actions that appear in all valid solutions of a planning problem. They have been used successfully to calculate heuristics that guide the search for a plan. We investigate an extension to this concept by defining a novel "relev
Externí odkaz:
http://arxiv.org/abs/2403.07510
Autor:
Agrawal, Ayush, Arora, Raghav, Datta, Ahana, Banerjee, Snehasis, Bhowmick, Brojeshwar, Jatavallabhula, Krishna Murthy, Sridharan, Mohan, Krishna, Madhava
Publikováno v:
RO-MAN 2023 Conference
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 models (LLMs) or reinforcement learned (RL) policies for this task, o
Externí odkaz:
http://arxiv.org/abs/2306.01540
Autor:
Dodampegama, Hasra, Sridharan, Mohan
Ad hoc teamwork refers to the problem of enabling an agent to collaborate with teammates without prior coordination. Data-driven methods represent the state of the art in ad hoc teamwork. They use a large labeled dataset of prior observations to mode
Externí odkaz:
http://arxiv.org/abs/2306.00790
We introduce RAMP, an open-source robotics benchmark inspired by real-world industrial assembly tasks. RAMP consists of beams that a robot must assemble into specified goal configurations using pegs as fasteners. As such, it assesses planning and exe
Externí odkaz:
http://arxiv.org/abs/2305.09644
Autor:
Gireesh, Nandiraju, Agrawal, Ayush, Datta, Ahana, Banerjee, Snehasis, Sridharan, Mohan, Bhowmick, Brojeshwar, Krishna, Madhava
Publikováno v:
ICRA 2023 conference
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 a factory. Existing methods for MultiON have viewed this as a direct e
Externí odkaz:
http://arxiv.org/abs/2305.06178
Adapting upper-limb impedance (i.e., stiffness, damping, inertia) is essential for humans interacting with dynamic environments for executing grasping or manipulation tasks. On the other hand, control methods designed for state-of-the-art upper-limb
Externí odkaz:
http://arxiv.org/abs/2209.04937
Autor:
Kiran, D. A. Sasi, Anand, Kritika, Kharyal, Chaitanya, Kumar, Gulshan, Gireesh, Nandiraju, Banerjee, Snehasis, Roychoudhury, Ruddra dev, Sridharan, Mohan, Bhowmick, Brojeshwar, Krishna, Madhava
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. The framework uses a history of robot trajectories to lear
Externí odkaz:
http://arxiv.org/abs/2208.13031
Autor:
Gireesh, Nandiraju, Kiran, D. A. Sasi, Banerjee, Snehasis, Sridharan, Mohan, Bhowmick, Brojeshwar, Krishna, Madhava
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 semantic map of the environment over time, and then repeatedly selects a lon
Externí odkaz:
http://arxiv.org/abs/2208.13009
Autor:
Dodampegama, Hasra, Sridharan, Mohan
We present an architecture for ad hoc teamwork, which refers to collaboration in a team of agents without prior coordination. State of the art methods for this problem often include a data-driven component that uses a long history of prior observatio
Externí odkaz:
http://arxiv.org/abs/2208.11556