13 citations · 15 across the 5 of their papers we have counts for
12 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…
Improving Self-supervised Learning for Out-of-distribution Task via Auxiliary Classifier
Harshita Boonlia, Tanmoy Dam, Md Meftahul Ferdaus +2
In real world scenarios, out-of-distribution (OOD) datasets may have a large distributional shift from training datasets. This phenomena generally occurs when a trained classifier…
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…
Does Adversarial Oversampling Help us?
Tanmoy Dam, Md Meftahul Ferdaus, Sreenatha G. Anavatti +2
Traditional oversampling methods are generally employed to handle class imbalance in datasets. This oversampling approach is independent of the classifier; thus, it does not offer…
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…
Towards Crossing the Reality Gap with Evolved Plastic Neurocontrollers
Huanneng Qiu, Matthew Garratt, David Howard +1
A critical issue in evolutionary robotics is the transfer of controllers learned in simulation to reality. This is especially the case for small Unmanned Aerial Vehicles (UAVs), as…