no code implementations • 5 May 2024 • Ruikun Zhou, Wail Gueaieb, Davide Spinello
We propose a Kullback-Leibler Divergence (KLD) filter to extract anomalies within data series generated by a broad class of proximity sensors, along with the anomaly locations and their relative sizes.
no code implementations • 17 Mar 2023 • Shuzheng Qu, Mohammed Abouheaf, Wail Gueaieb, Davide Spinello
An online model-free policy iteration mechanism is developed here to guide a flock of agents to follow an independent command generator over a time-varying graph topology.
no code implementations • 17 Mar 2023 • Mohammed Abouheaf, Wail Gueaieb, Davide Spinello, Salah Al-Sharhan
Model-reference adaptive systems refer to a consortium of techniques that guide plants to track desired reference trajectories.
no code implementations • 17 Mar 2023 • Shuzheng Qu, Mohammed Abouheaf, Wail Gueaieb, Davide Spinello
The flock-guidance problem enjoys a challenging structure where multiple optimization objectives are solved simultaneously.
no code implementations • 15 Mar 2023 • Mohammed Abouheaf, Derek Boase, Wail Gueaieb, Davide Spinello, Salah Al-Sharhan
For concept demonstration, a trajectory-following optimization problem of a Kinova robotic arm is solved using an integral reinforcement learning approach with guaranteed stability for slowly varying dynamics.
no code implementations • 13 Mar 2023 • Payam Parvizi, Runnan Zou, Colin Bellinger, Ross Cheriton, Davide Spinello
We propose the use of reinforcement learning (RL) to reduce the latency, size and cost of the system by up to $30-40\%$ by learning a control policy through interactions with a low-cost quadrant photodiode rather than a wavefront phase profiling camera.
no code implementations • 1 Apr 2021 • Mohammed Abouheaf, Wail Gueaieb, Md. Suruz Miah, Davide Spinello
In addition, the underlying trajectory-tracking control problems grow in complexity in order to decide the optimal rudder and thrust control signals.
no code implementations • 29 Mar 2021 • Mohammed Abouheaf, Nathaniel Mailhot, Wail Gueaieb, Davide Spinello
This work leverages ideas from instrumentation and measurements, machine learning, and optimization fields in order to develop an autonomous navigation system for a flexible-wing aircraft.