3 citations · 4 across the 6 of their papers we have counts for
6 papers
R-WhONet: Recalibrated Wheel Odometry Neural Network for Vehicular Positioning using Transfer Learning
Uche Onyekpe, Alicja Szkolnik, Vasile Palade +2
This paper proposes a transfer learning approach to recalibrate our previously developed Wheel Odometry Neural Network (WhONet) for vehicle positioning in environments where Global…
WhONet: Wheel Odometry Neural Network for Vehicular Localisation in GNSS-Deprived Environments
Uche Onyekpe, Vasile Palade, Anuradha Herath +2
In this paper, a deep learning approach is proposed to accurately position wheeled vehicles in Global Navigation Satellite Systems (GNSS) deprived environments. In the absence of G…
Learning to Localise Automated Vehicles in Challenging Environments using Inertial Navigation Systems (INS)
Uche Onyekpe, Vasile Palade, Stratis Kanarachos
An algorithm based on Artificial Neural Networks is proposed in this paper to improve the accuracy of Inertial Navigation System (INS)/ Global Navigation Satellite System (GNSS) in…
IO-VNBD: Inertial and Odometry Benchmark Dataset for Ground Vehicle Positioning
Uche Onyekpe, Vasile Palade, Stratis Kanarachos +1
Low-cost inertial navigation sensors (INS) can be exploited for a reliable tracking solution for autonomous vehicles. However, position errors grow exponentially due to noises in t…
Spontaneous Fruit Fly Optimisation for truss weight minimisation: Performance evaluation based on the no free lunch theorem
Uche Onyekpe, Stratis Kanarachos, Michael E. Fitzpatrick
Over the past decade, several researchers have presented various optimisation algorithms for use in truss design. The no free lunch theorem implies that no optimisation algorithm f…
Performance Boundary Identification for the Evaluation of Automated Vehicles using Gaussian Process Classification
Felix Batsch, Alireza Daneshkhah, Madeline Cheah +2
Safety is an essential aspect in the facilitation of automated vehicle deployment. Current testing practices are not enough, and going beyond them leads to infeasible testing requi…