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Jimmy Chiun

5 accepted papers

2025

Heterogeneous Multi-robot Task Allocation and Scheduling via Reinforcement Learning

RA-L 2025

Many multi-robot applications require allocating a team of heterogeneous agents (robots) with different abilities to cooperatively complete a given set of spatially distributed tasks as quickly as possible. We focus on tasks that can only be initiated when all required agents are present otherwise a

Cited by 19SourceScholar
2025

MARVEL: Multi-Agent Reinforcement Learning for Constrained Field-of-View Multi-Robot Exploration in Large-Scale Environments

ICRA 2025

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 LiDAR, this is impractical for small robots such as drones, where lightweight, directional sensors like cameras may be th

Cited by 10SourcecodeScholar
2025

Search-TTA: A Multi-Modal Test-Time Adaptation Framework for Visual Search in the Wild

CoRL 2025poster

To perform autonomous visual search for environmental monitoring, a robot may leverage satellite imagery as a prior map. This can help inform coarse, high level search and exploration strategies, even when such images lack sufficient resolution to allow fine-grained, explicit visual recognition of t…

Cited by 0SourceScholar
2024

ViPER: Visibility-based Pursuit-Evasion via Reinforcement Learning

CoRL 2024poster

In visibility-based pursuit-evasion tasks, a team of mobile pursuer robots with limited sensing capabilities is tasked with detecting all evaders in a multiply-connected planar environment, whose map may or may not be known to pursuers beforehand. This requires tight coordination among multiple agen…

Cited by 1SourceScholar
2023

Context-Aware Deep Reinforcement Learning for Autonomous Robotic Navigation in Unknown Area

CoRL 2023poster

Mapless navigation refers to a challenging task where a mobile robot must rapidly navigate to a predefined destination using its partial knowledge of the environment, which is updated online along the way, instead of a prior map of the environment. Inspired by the recent developments in deep reinfor…

Cited by 25SourceScholar