59 citations · 221 across the 105 of their papers we have counts for
13 papers · 1 filter
When to Localize? A POMDP Approach
Troi Williams, Kasra Torshizi, Pratap Tokekar
Robots often localize to lower navigational errors and facilitate downstream, high-level tasks. However, a robot may want to selectively localize when localization is costly (such…
When to Localize? A Risk-Constrained Reinforcement Learning Approach
Chak Lam Shek, Kasra Torshizi, Troi Williams +1
In a standard navigation pipeline, a robot localizes at every time step to lower navigational errors. However, in some scenarios, a robot needs to selectively localize when it is e…
Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance
Joshua McClellan, Naveed Haghani, John Winder +2
Multi-Agent Reinforcement Learning (MARL) struggles with sample inefficiency and poor generalization [1]. These challenges are partially due to a lack of structure or inductive bia…
Improving Zero-Shot ObjectNav with Generative Communication
Vishnu Sashank Dorbala, Vishnu Dutt Sharma, Pratap Tokekar +1
We propose a new method for improving zero-shot ObjectNav that aims to utilize potentially available environmental percepts for navigational assistance. Our approach takes into acc…
On the Global Optimality of Policy Gradient Methods in General Utility Reinforcement Learning
Anas Barakat, Souradip Chakraborty, Peihong Yu +2
Reinforcement learning with general utilities (RLGU) offers a unifying framework to capture several problems beyond standard expected returns, including imitation learning, pure ex…
IMRL: Integrating Visual, Physical, Temporal, and Geometric Representations for Enhanced Food Acquisition
Rui Liu, Zahiruddin Mahammad, Amisha Bhaskar +1
Robotic assistive feeding holds significant promise for improving the quality of life for individuals with eating disabilities. However, acquiring diverse food items under varying…
PLANRL: A Motion Planning and Imitation Learning Framework to Bootstrap Reinforcement Learning
Amisha Bhaskar, Zahiruddin Mahammad, Sachin R Jadhav +1
Reinforcement Learning (RL) has shown remarkable progress in simulation environments, yet its application to real-world robotic tasks remains limited due to challenges in explorati…
GATSBI: An Online GTSP-Based Algorithm for Targeted Surface Bridge Inspection and Defect Detection
Harnaik Dhami, Charith Reddy, Vishnu Dutt Sharma +2
We study the problem of visual surface inspection of infrastructure for defects using an Unmanned Aerial Vehicle (UAV). We do not assume that the geometric model of the infrastruct…
Fast k-connectivity Restoration in Multi-Robot Systems for Robust Communication Maintenance
Md Ishat-E-Rabban, Guangyao Shi, Griffin Bonner +1
Maintaining a robust communication network plays an important role in the success of a multi-robot team jointly performing an optimization task. A key characteristic of a robust co…
Adaptive Visual Imitation Learning for Robotic Assisted Feeding Across Varied Bowl Configurations and Food Types
Rui Liu, Amisha Bhaskar, Pratap Tokekar
In this study, we introduce a novel visual imitation network with a spatial attention module for robotic assisted feeding (RAF). The goal is to acquire (i.e., scoop) food items fro…
LAVA: Long-horizon Visual Action based Food Acquisition
Amisha Bhaskar, Rui Liu, Vishnu D. Sharma +2
Robotic Assisted Feeding (RAF) addresses the fundamental need for individuals with mobility impairments to regain autonomy in feeding themselves. The goal of RAF is to use a robot…
Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis
Rui Liu, Anish Gupta, Erfaun Noorani +1
Reinforcement Learning (RL) has shown exceptional performance across various applications, enabling autonomous agents to learn optimal policies through interaction with their envir…
Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning
Peihong Yu, Manav Mishra, Alec Koppel +5
Multi-Agent Reinforcement Learning (MARL) algorithms face the challenge of efficient exploration due to the exponential increase in the size of the joint state-action space. While…