2 citations · 4 across the 10 of their papers we have counts for
5 papers · 1 filter
Constrained Robotic Navigation on Preferred Terrains Using LLMs and Speech Instruction: Exploiting the Power of Adverbs
Faraz Lotfi, Farnoosh Faraji, Nikhil Kakodkar +3
This paper explores leveraging large language models for map-free off-road navigation using generative AI, reducing the need for traditional data collection and annotation. We prop…
A comparison of RL-based and PID controllers for 6-DOF swimming robots: hybrid underwater object tracking
Faraz Lotfi, Khalil Virji, Nicholas Dudek +1
In this paper, we present an exploration and assessment of employing a centralized deep Q-network (DQN) controller as a substitute for the prevalent use of PID controllers in the c…
Uncertainty-aware hybrid paradigm of nonlinear MPC and model-based RL for offroad navigation: Exploration of transformers in the predictive model
Faraz Lotfi, Khalil Virji, Farnoosh Faraji +4
In this paper, we investigate a hybrid scheme that combines nonlinear model predictive control (MPC) and model-based reinforcement learning (RL) for navigation planning of an auton…
ANSEL Photobot: A Robot Event Photographer with Semantic Intelligence
Dmitriy Rivkin, Gregory Dudek, Nikhil Kakodkar +4
Our work examines the way in which large language models can be used for robotic planning and sampling, specifically the context of automated photographic documentation. Specifical…
Trajectory-Constrained Deep Latent Visual Attention for Improved Local Planning in Presence of Heterogeneous Terrain
Stefan Wapnick, Travis Manderson, David Meger +1
We present a reward-predictive, model-based deep learning method featuring trajectory-constrained visual attention for local planning in visual navigation tasks. Our method learns…