| Exploration in deep reinforcement learning: A survey P Ladosz, L Weng, M Kim, H Oh Information Fusion 85, 1-22, 2022 | 396 | 2022 |
| Optimal positioning of communication relay unmanned aerial vehicles in urban environments P Ladosz, H Oh, WH Chen 2016 International Conference on Unmanned Aircraft Systems (ICUAS), 1140-1147, 2016 | 55 | 2016 |
| Measurement of boundary layer ozone concentrations on‐board a Skywalker unmanned aerial vehicle S Illingworth, G Allen, C Percival, P Hollingsworth, M Gallagher, ... Atmospheric Science Letters 15 (4), 252-258, 2014 | 47 | 2014 |
| Trajectory planning for communication relay unmanned aerial vehicles in urban dynamic environments P Ladosz, H Oh, WH Chen Journal of Intelligent & Robotic Systems 89, 7-25, 2018 | 41 | 2018 |
| Gaussian process based channel prediction for communication-relay UAV in urban environments P Ladosz, H Oh, G Zheng, WH Chen IEEE Transactions on Aerospace and Electronic Systems 56 (1), 313-325, 2019 | 35 | 2019 |
| A hybrid approach of learning and model-based channel prediction for communication relay UAVs in dynamic urban environments P Ladosz, H Oh, G Zheng, WH Chen IEEE Robotics and Automation Letters 4 (3), 2370-2377, 2019 | 29 | 2019 |
| Deep reinforcement learning with modulated Hebbian plus Q-network architecture P Ladosz, E Ben-Iwhiwhu, J Dick, N Ketz, S Kolouri, JL Krichmar, PK Pilly, ... IEEE Transactions on Neural Networks and Learning Systems 33 (5), 2045-2056, 2021 | 20 | 2021 |
| Optimal communication relay positioning in mobile multi-node networks J Kim, P Ladosz, H Oh Robotics and Autonomous Systems 129, 103517, 2020 | 20 | 2020 |
| A Generic ROS Based System for Rapid Development and Testing of Algorithms for Autonomous Ground and Aerial Vehicles P Ladosz, M Coombes, J Smith, M Hutchinson Robot Operating System (ROS), 113-153, 2018 | 17 | 2018 |
| Prediction of air-to-ground communication strength for relay UAV trajectory planner in urban environments P Ladosz, H Oh, WH Chen 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 17 | 2017 |
| Experimental assessment of plume mapping using point measurements from unmanned vehicles M Hutchinson, P Ladosz, C Liu, WH Chen 2019 International Conference on Robotics and Automation (ICRA), 7720-7726, 2019 | 15 | 2019 |
| Evolving inborn knowledge for fast adaptation in dynamic pomdp problems E Ben-Iwhiwhu, P Ladosz, J Dick, WH Chen, P Pilly, A Soltoggio Proceedings of the 2020 genetic and evolutionary computation conference, 280-288, 2020 | 13 | 2020 |
| Source term estimation using deep reinforcement learning with Gaussian mixture model feature extraction for mobile sensors M Park, P Ladosz, H Oh IEEE Robotics and Automation Letters 7 (3), 8323-8330, 2022 | 12 | 2022 |
| Receding horizon-based infotaxis with random sampling for source search and estimation in complex environments M Park, P Ladosz, J Kim, H Oh IEEE Transactions on Aerospace and Electronic Systems 59 (1), 591-609, 2022 | 9 | 2022 |
| Communication-aware convoy following guidance for UAVs in a complex urban environment H Oh, HS Shin, S Kim, P Ladosz, WH Chen 2016 24th Mediterranean Conference on Control and Automation (MED), 1230-1235, 2016 | 9 | 2016 |
| A genetic algorithm optimiser for dynamic product routing in agile manufacturing environment P Ladosz, O Banjo, S De Guido, M Zalasiewicz 2018 IEEE 16th International Conference on Industrial Informatics (INDIN …, 2018 | 8 | 2018 |
| Detecting changes and avoiding catastrophic forgetting in dynamic partially observable environments J Dick, P Ladosz, E Ben-Iwhiwhu, H Shimadzu, P Kinnell, PK Pilly, ... Frontiers in neurorobotics 14, 578675, 2020 | 7 | 2020 |
| Autonomous landing on a moving platform using vision-based deep reinforcement learning P Ladosz, M Mammadov, H Shin, W Shin, H Oh IEEE Robotics and Automation Letters, 2024 | 6 | 2024 |
| Monocular vision-based time-to-collision estimation for small drones by domain adaptation of simulated images M Kim, P Ladosz, H Oh Expert Systems with Applications 199, 116973, 2022 | 6 | 2022 |
| The configurable tree graph (ct-graph): measurable problems in partially observable and distal reward environments for lifelong reinforcement learning A Soltoggio, E Ben-Iwhiwhu, C Peridis, P Ladosz, J Dick, PK Pilly, ... arXiv preprint arXiv:2302.10887, 2023 | 4 | 2023 |
