13 citations · 14 across the 3 of their papers we have counts for
10 papers
Lightweight Monocular Depth Estimation with an Edge Guided Network
Xingshuai Dong, Matthew A. Garratt, Sreenatha G. Anavatti +2
Monocular depth estimation is an important task that can be applied to many robotic applications. Existing methods focus on improving depth estimation accuracy via training increas…
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…
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…
Evolving Spiking Neural Networks for Nonlinear Control Problems
Huanneng Qiu, Matthew Garratt, David Howard +1
Spiking Neural Networks are powerful computational modelling tools that have attracted much interest because of the bioinspired modelling of synaptic interactions between neurons.…
Distributed Obstacle and Multi-Robot Collision Avoidance in Uncertain Environments
Vu Phi Tran, Matthew Garratt, Ian R. Petersen
This paper tackles the distributed leader-follower (L-F) control problem for heterogeneous mobile robots in unknown environments requiring obstacle avoidance, inter-robot collision…
PAC: A Novel Self-Adaptive Neuro-Fuzzy Controller for Micro Aerial Vehicles
Md Meftahul Ferdaus, Mahardhika Pratama, Sreenatha G. Anavatti +2
There exists an increasing demand for a flexible and computationally efficient controller for micro aerial vehicles (MAVs) due to a high degree of environmental perturbations. In t…