From the 1 of 5 linked papers with an AI index.
5 papers
Dec-MARVEL: Decentralized Multi-Agent Exploration without Communication under Budget Constraints
Janghyun Cho, Jimmy Chiun, Guillaume Sartoretti +1
The paper introduces Dec-MARVEL, a decentralized framework that enables multiple UAVs to explore unknown environments without explicit communication, using observed teammate motion…
ORION: Option-Regularized Deep Reinforcement Learning for Cooperative Multi-Agent Online Navigation
Shizhe Zhang, Jingsong Liang, Zhitao Zhou +6
Existing methods for multi-agent navigation typically assume fully known environments, offering limited support for partially known scenarios with outdated or imperfect prior maps,…
Search-TTA: A Multimodal Test-Time Adaptation Framework for Visual Search in the Wild
Derek Ming Siang Tan, Shailesh, Boyang Liu +8
To perform outdoor visual navigation and search, a robot may leverage satellite imagery to generate visual priors. This can help inform high-level search strategies, even when such…
ZING-3D: Zero-shot Incremental 3D Scene Graphs via Vision-Language Models
Pranav Saxena, Jimmy Chiun
Understanding and reasoning about complex 3D environments requires structured scene representations that capture not only objects but also their semantic and spatial relationships.…
MARVEL: Multi-Agent Reinforcement Learning for constrained field-of-View multi-robot Exploration in Large-scale environments
Jimmy Chiun, Shizhe Zhang, Yizhuo Wang +2
In multi-robot exploration, a team of mobile robot is tasked with efficiently mapping an unknown environments. While most exploration planners assume omnidirectional sensors like L…