7 papers
B-ActiveSEAL: Scalable Uncertainty-Aware Active Exploration with Tightly Coupled Localization-Mapping
Min-Won Seo, Aamodh Suresh, Carlos Nieto-Granda +1
Active robot exploration requires decision-making processes that integrate localization and mapping under tightly coupled uncertainty. However, managing these interdependent uncert…
BEASST: Behavioral Entropic Gradient based Adaptive Source Seeking for Mobile Robots
Donipolo Ghimire, Aamodh Suresh, Carlos Nieto-Granda +1
This paper presents BEASST (Behavioral Entropic Gradient-based Adaptive Source Seeking for Mobile Robots), a novel framework for robotic source seeking in complex, unknown environm…
Behaviorally Heterogeneous Multi-Agent Exploration Using Distributed Task Allocation
Nirabhra Mandal, Aamodh Suresh, Carlos Nieto-Granda +1
We study a problem of multi-agent exploration with behaviorally heterogeneous robots. Each robot maps its surroundings using SLAM and identifies a set of areas of interest (AoIs) o…
Behaviorally Adaptive Multi-Robot Hazard Localization in Failure-Prone, Communication-Denied Environments
Alkesh K. Srivastava, Aamodh Suresh, Carlos Nieto-Granda
We address the challenge of multi-robot autonomous hazard mapping in high-risk, failure-prone, communication-denied environments such as post-disaster zones, underground mines, cav…
Robust Output-Feedback MPC for Nonlinear Systems with Applications to Robotic Exploration
Scott Brown, Mohammad Khajenejad, Aamodh Suresh +1
This paper introduces a novel method for robust output-feedback model predictive control (MPC) for a class of nonlinear discrete-time systems. We propose a novel interval-valued pr…
Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning
Wesley A. Suttle, Aamodh Suresh, Carlos Nieto-Granda
Entropy-based objectives are widely used to perform state space exploration in reinforcement learning (RL) and dataset generation for offline RL. Behavioral entropy (BE), a rigorou…