no code implementations • 3 Apr 2024 • Alessandro Giuliano, S. Andrew Gadsden, Waleed Hilal, John Yawney
The large amounts of data along with security concerns call for new compression and encryption techniques capable of preserving reconstruction quality while minimizing the transmission cost of this data back to Earth.
no code implementations • 23 Mar 2024 • Zhe Xu, Tao Yan, Simon X. Yang, S. Andrew Gadsden, Mohammad Biglarbegian
This paper addresses the challenges of distributed formation control in multiple mobile robots, introducing a novel approach that enhances real-world practicability.
no code implementations • 26 Oct 2023 • Andrei Buin, Hung Yi Chiang, S. Andrew Gadsden, Faraz A. Alderson
We present here a combination of two networks, Recurrent Neural Networks (RNN) and Temporarily Convolutional Neural Networks (TCN) in de novo reaction generation using the novel Reaction Smiles-like representation of reactions (CGRSmiles) with atom mapping directly incorporated.
no code implementations • 18 Aug 2023 • Tao Yan, Zhe Xu, Simon X. Yang, S. Andrew Gadsden
Robust constrained formation tracking control of underactuated underwater vehicles (UUVs) fleet in three-dimensional space is a challenging but practical problem.
no code implementations • 3 May 2023 • Zhe Xu, Tao Yan, Simon X. Yang, S. Andrew Gadsden
This paper investigated the distributed leader follower formation control problem for multiple differentially driven mobile robots.
no code implementations • 3 Sep 2022 • Zhe Xu, Tao Yan, Simon X. Yang, S. Andrew Gadsden
In comparative studies, the proposed combined hybrid control strategy has ensured control signals smoothness, which is critical in real world applications, especially for an unmanned underwater vehicle that needs to operate in complex underwater environments.