Publications
Our peer-reviewed research publications
2025
Hung, Pham Duy; Ngo, Trung Dung
Multi-Layered Distributed Control for Collective Movement and Coverage of Robot Swarms in Unknown Structured Environments Journal Article
In: IEEE Access, vol. 13, pp. 64610-64626, 2025.
@article{10960514,
title = {Multi-Layered Distributed Control for Collective Movement and Coverage of Robot Swarms in Unknown Structured Environments},
author = {Pham Duy Hung and Trung Dung Ngo},
doi = {10.1109/ACCESS.2025.3559424},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
journal = {IEEE Access},
volume = {13},
pages = {64610-64626},
abstract = {In this study, we propose a novel multi-layered distributed control (MDC) framework for multi-robot deployment and coverage strategies in unknown structured environments. The MDC is structured with strategic function-based layers of swarm deployment, coverage, and withdrawal built on top of the underlying behavior-based motion control layer. The behavior-based motion control layer is responsible for preserving the network integrity and guaranteeing collision avoidance for mobile robots. To enable adaptability and flexibility of control strategies in various unknown structured environments, the behavior suppression mechanism is created to modulate and substitute individual behaviors for appropriate swarm strategies including swarm movement in aggregation, one-chain configuration, collective coverage with target-tracking motions. We have examined and evaluated our proposed method through both simulation and real-world experiments. The results demonstrate that the MDC achieves high performance in both task completion and coverage rate while maintaining flexibility and scalability, highlighting its potential for real-world applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this study, we propose a novel multi-layered distributed control (MDC) framework for multi-robot deployment and coverage strategies in unknown structured environments. The MDC is structured with strategic function-based layers of swarm deployment, coverage, and withdrawal built on top of the underlying behavior-based motion control layer. The behavior-based motion control layer is responsible for preserving the network integrity and guaranteeing collision avoidance for mobile robots. To enable adaptability and flexibility of control strategies in various unknown structured environments, the behavior suppression mechanism is created to modulate and substitute individual behaviors for appropriate swarm strategies including swarm movement in aggregation, one-chain configuration, collective coverage with target-tracking motions. We have examined and evaluated our proposed method through both simulation and real-world experiments. The results demonstrate that the MDC achieves high performance in both task completion and coverage rate while maintaining flexibility and scalability, highlighting its potential for real-world applications.
2024
Nguyen, Trung-Tin; Ngo, Trung Dung
Spatiotemporal Motion Profiles for Cost-Based Optimal Approaching Pose Estimation Proceedings Article
In: 2024 IEEE/SICE International Symposium on System Integration (SII), pp. 92-98, 2024.
@inproceedings{10417396,
title = {Spatiotemporal Motion Profiles for Cost-Based Optimal Approaching Pose Estimation},
author = {Trung-Tin Nguyen and Trung Dung Ngo},
doi = {10.1109/SII58957.2024.10417396},
year = {2024},
date = {2024-01-01},
booktitle = {2024 IEEE/SICE International Symposium on System Integration (SII)},
pages = {92-98},
abstract = {Recent public perceptions indicate a positive shift towards a society with human and robot co-existing, especially aged populations. The ability to socially navigate become crucial for mobile robots by enabling them to guarantee not only human physical safety but also psychological comfort, and enhance robots contextual awareness in human-robot interactions (HRI). In this study, we introduce an extended navigation scheme to approach moving target based on the tracking of human spatiotemporal motion, social studies on proxemics, and kino-dynamics of the mobile robot. The strategy utilizes existing multi-layer cost-based navigation mapping for complete integration with plannings and introduce soft social constraints by extending the costmap value range. The primary contributions include (i) spatio-temporal motion profiles (SMPs) of all humans under tracking, (ii) a social navigation cost function (SNCF) for filtering socially-optimal goal poses. The results drawn from simulated testings across three normative social situations, and statistical analysis demonstrate the SMPs effectiveness through measured spatial and temporal coefficients. The driving factors safety and appropriate social construct are determined to be either statistically or practically significant, while also introducing a complete navigation scheme taking into account of socially acceptable behaviours for the robot.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Recent public perceptions indicate a positive shift towards a society with human and robot co-existing, especially aged populations. The ability to socially navigate become crucial for mobile robots by enabling them to guarantee not only human physical safety but also psychological comfort, and enhance robots contextual awareness in human-robot interactions (HRI). In this study, we introduce an extended navigation scheme to approach moving target based on the tracking of human spatiotemporal motion, social studies on proxemics, and kino-dynamics of the mobile robot. The strategy utilizes existing multi-layer cost-based navigation mapping for complete integration with plannings and introduce soft social constraints by extending the costmap value range. The primary contributions include (i) spatio-temporal motion profiles (SMPs) of all humans under tracking, (ii) a social navigation cost function (SNCF) for filtering socially-optimal goal poses. The results drawn from simulated testings across three normative social situations, and statistical analysis demonstrate the SMPs effectiveness through measured spatial and temporal coefficients. The driving factors safety and appropriate social construct are determined to be either statistically or practically significant, while also introducing a complete navigation scheme taking into account of socially acceptable behaviours for the robot.
BibTeX Citation
Abstract