6 accepted papers
Binary Neural Networks (BNNs) have garnered significant attention due to their immense potential for deployment on edge devices. However, the non-differentiability of the quantization function poses a challenge for the optimization of BNNs, as its derivative cannot be backpropagated. To address this…
This letter proposes a fault-tolerant control (FTC) framework for a novel type of aircraft—lifting-wing multicopters. The core of the framework is an attitude controller based on nonlinear model predictive control (NMPC), where the objective function of the NMPC is designed on the based of the relax
Wind disturbance is a critical challenge for uninhabited aerial vehicles (UAVs), particularly for hybrid vertical takeoff and landing (VTOL) UAVs such as lifting-wing quadcopters, which are prone to aerodynamic disturbances like gusts and turbulence due to their wing structure. Existing control stra
Advanced life forms sustained by the synergistic interaction of neural cognitive mechanisms continually acquire and transfer knowledge throughout their lifespan. In contrast contemporary machine learning paradigms exhibit limitations in emulating the facets of continual learning (CL). Nonetheless th…
Previous work on adversarial examples typically involves a fixed norm perturbation budget, which fails to capture the way humans perceive perturbations. Recent work has shifted towards investigating natural unrestricted adversarial examples (UAEs) that breaks l_p perturbation bounds but nonetheless…
A technological revolution is occurring in the field of robotics with the data-driven deep learning technology. However, building datasets for each local robot is laborious. Meanwhile, data islands between local robots make data unable to be utilized collaboratively. To address this issue, the work…