2 citations · 3 across the 10 of their papers we have counts for
10 papers
PRISM: Performer RS-IMLE for Single-pass Multisensory Imitation Learning
Amisha Bhaskar, Pratap Tokekar, Stefano Di Cairano +1
Robotic imitation learning typically requires models that capture multimodal action distributions while operating at real-time control rates and accommodating multiple sensing moda…
VARP: Reinforcement Learning from Vision-Language Model Feedback with Agent Regularized Preferences
Anukriti Singh, Amisha Bhaskar, Peihong Yu +4
Designing reward functions for continuous-control robotics often leads to subtle misalignments or reward hacking, especially in complex tasks. Preference-based RL mitigates some of…
Sketch-to-Skill: Bootstrapping Robot Learning with Human Drawn Trajectory Sketches
Peihong Yu, Amisha Bhaskar, Anukriti Singh +2
Training robotic manipulation policies traditionally requires numerous demonstrations and/or environmental rollouts. While recent Imitation Learning (IL) and Reinforcement Learning…
Mitigating Memorization in LLMs using Activation Steering
Manan Suri, Nishit Anand, Amisha Bhaskar
The memorization of training data by Large Language Models (LLMs) poses significant risks, including privacy leaks and the regurgitation of copyrighted content. Activation steering…
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…
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…
REBEL: Reward Regularization-Based Approach for Robotic Reinforcement Learning from Human Feedback
Souradip Chakraborty, Anukriti Singh, Amisha Bhaskar +3
The effectiveness of reinforcement learning (RL) agents in continuous control robotics tasks is mainly dependent on the design of the underlying reward function, which is highly pr…
AG-CVG: Coverage Planning with a Mobile Recharging UGV and an Energy-Constrained UAV
Nare Karapetyan, Ahmad Bilal Asghar, Amisha Bhaskar +3
In this paper, we present an approach for coverage path planning for a team of an energy-constrained Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV). Both the UA…