Tauhidul Alam — accepted AI-conference papers

2024

LCD-RIG: Limited Communication Decentralized Robotic Information Gathering Systems

Abdullah Al Redwan Newaz, Paulo Padrao, Jose Fuentes, Tauhidul Alam, Ganesh Govindarajan, Leonardo Bobadilla

RA-L 2024

Effective data collection in collaborative information-gathering systems relies heavily on maintaining uninterrupted connectivity. Yet, real-world communication disruptions often pose challenges to information-gathering processes. To address this issue, we introduce a novel method —a limited communi

Cited by 5 Source ↗Scholar ↗

2023

Decentralized Multi-Robot Information Gathering From Unknown Spatial Fields

Abdullah Al Redwan Newaz, Murtadha Alsayegh, Tauhidul Alam, Leonardo Bobadilla

RA-L 2023

We present an incremental scalable motion planning algorithm for finding maximally informative trajectories for decentralized mobile robots. These robots are deployed to observe an unknown spatial field, where the informativeness of observations is specified as a density function. Existing works tha

Cited by 9 Source ↗Scholar ↗

2021

Long-Term Autonomy for AUVs Operating Under Uncertainties in Dynamic Marine Environments

Abdullah Al Redwan Newaz, Tauhidul Alam, Gregory Murad Reis, Leonardo Bobadilla, Ryan N. Smith

RA-L 2021

There has been significant interest in recent years in the utility and implementation of autonomous underwater and surface vehicles (AUVs and ASVs) for persistent surveillance of the ocean. Example studies include the dynamics of physical phenomena, e.g., ocean fronts, temperature and salinity profi

Cited by 13 Source ↗Scholar ↗

2019

Coordinated multi-robot planning while preserving individual privacy

Li Li, Alfredo Bayuelo, Leonardo Bobadilla, Tauhidul Alam, Dylan A. Shell

ICRA 2019poster

We consider the problem of multiple robots that must cooperate within a shared environment, but which wish to limit the information they disclose during their coordination efforts. Specifically, we examine the problems of privacy-preserving rendezvous and persistent monitoring. In the former, the ro…

Cited by 24 Source ↗Scholar ↗

2018

Space-Efficient Filters for Mobile Robot Localization from Discrete Limit Cycles

Tauhidul Alam, Leonardo Bobadilla, Dylan A. Shell

RA-L 2018

Robot localization is the problem of determining a robot's pose in an environment, typically within a given map or a similar representation. Different methods have been proposed to address this localization problem for robots with limited sensing. In this letter, we present a localization method for

Cited by 14 Source ↗Scholar ↗