64 citations · 71 across the 9 of their papers we have counts for
9 papers
Active Sensing Strategy: Multi-Modal, Multi-Robot Source Localization and Mapping in Real-World Settings with Fixed One-Way Switching
Vu Phi Tran, Asanka G. Perera, Matthew A. Garratt +2
This paper introduces a state-machine model for a multi-modal, multi-robot environmental sensing algorithm tailored to dynamic real-world settings. The algorithm uniquely combines…
Radio Source Localization using Sparse Signal Measurements from Uncrewed Ground Vehicles
Asanka Perera, Vu Phi Tran, Sreenatha Anavatti +2
Radio source localization can benefit many fields, including wireless communications, radar, radio astronomy, wireless sensor networks, positioning systems, and surveillance system…
Coverage Path Planning with Budget Constraints for Multiple Unmanned Ground Vehicles
Vu Phi Tran, Asanka Perera, Matthew A. Garratt +2
This paper proposes a state-machine model for a multi-modal, multi-robot environmental sensing algorithm. This multi-modal algorithm integrates two different exploration algorithms…
Robust Fuzzy Q-Learning-Based Strictly Negative Imaginary Tracking Controllers for the Uncertain Quadrotor Systems
Vu Phi Tran, M. A Mabrok, Sreenatha G. Anavatti +2
Quadrotors are one of the popular unmanned aerial vehicles (UAVs) due to their versatility and simple design. However, the tuning of gains for quadrotor flight controllers can be l…
Frontier-led Swarming: Robust Multi-Robot Coverage of Unknown Environments
Vu Phi Tran, Matthew A. Garratt, Kathryn Kasmarik +1
This paper proposes a novel swarm-based control algorithm for exploration and coverage of unknown environments, while maintaining a formation that permits short-range communication…
Continuous Deep Hierarchical Reinforcement Learning for Ground-Air Swarm Shepherding
Hung The Nguyen, Tung Duy Nguyen, Vu Phi Tran +5
The control and guidance of multi-robots (swarm) is a non-trivial problem due to the complexity inherent in the coupled interaction among the group. Whether the swarm is cooperativ…