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Ronghao Zheng

9 accepted papers

2025

Adaptive-Resolution Cooperative Field Mapping With Event-Triggered Distributed Map Fusion

RA-L 2025

Cooperative scalar field mapping is an important task for multi-robot systems. However, the limited communication and computation resources of robots have hindered the application of cooperative field mapping in large-scale scenarios. This letter proposes an adaptive-resolution Gaussian process mapp

Cited by 1SourceScholar
2025

Decentralized but Not Compromised: Modular Architecture with Refined Observation for Multi-Agent Model-Based Reinforcement Learning

IROS 2025

Multi-agent adversarial tasks such as swarm robotics and autonomous vehicle coordination, demand efficient decentralized collaboration under partial observability. While model-free multi-agent RL (MF-MARL) methods suffer from necessitating extensive environment interactions, most existing multi-agen

Cited by 0SourceScholar
2024

A Path Planning Approach for Multi-AUV Systems With Concurrent Stationary Node Access and Adaptive Sampling

RA-L 2024

Stationary node data retrieval and adaptive sampling are two important tasks in marine environment monitoring based on autonomous underwater vehicles (AUVs). Enabling AUVs to carry out these two heterogeneous tasks within a single deployment is crucial for the efficient utilization of hardware resou

Cited by 20SourceScholar
2024

Resource-Efficient Cooperative Online Scalar Field Mapping via Distributed Sparse Gaussian Process Regression

RA-L 2024

Cooperative online scalar field mapping is an important task for multi-robot systems. Gaussian process regression is widely used to construct a map that represents spatial information with confidence intervals. However, it is difficult to handle cooperative online mapping tasks because of its high c

Cited by 6SourceScholar
2023

CARE: Confidence-Rich Autonomous Robot Exploration Using Bayesian Kernel Inference and Optimization

RA-L 2023

In this letter, we consider improving the efficiency of information-based autonomous robot exploration in unknown and complex environments. We first utilize Gaussian process (GP) regression to learn a surrogate model to infer the confidence-rich mutual information (CRMI) of querying control actions,

Cited by 7SourcecodeScholar
2022

Confidence-rich Localization and Mapping based on Particle Filter for Robotic Exploration

IROS 2022poster

This paper mainly studies the localization and mapping of range sensing robots in the confidence-rich map (CRM) and then extends it to provide a full state estimate for information-theoretic exploration. Most previous works about active simultaneous localization and mapping and exploration always as…

Cited by 10SourcecodeScholar
2021

Multi-Robot Task Planning under Individual and Collaborative Temporal Logic Specifications

IROS 2021poster

This paper investigates the task coordination of multi-robot where each robot has a private individual temporal logic task specification; and also has to jointly satisfy a globally given collaborative temporal logic task specification. To efficiently generate feasible and optimized task execution pl…

Cited by 8SourceScholar