Hubert Szolc

2024

1. 

   SPA
   Preludium
   

   Tangled Program Graphs as an alternative to DRL-based control algorithms for UAVs

   Hubert Szolc, Karol Desnos, and Tomasz Kryjak

   In 2024 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA) , Sep 2024

   Awarded Abstract DOI arXiv Bib Code Poster Website

   Best Paper Award

   Deep reinforcement learning (DRL) is currently the most popular AI-based approach to autonomous vehicle control. An agent, trained for this purpose in simulation, can interact with the real environment with a human-level performance. Despite very good results in terms of selected metrics, this approach has some significant drawbacks: high computational requirements and low explainability. Because of that, a DRL-based agent cannot be used in some control tasks, especially when safety is the key issue. Therefore we propose to use Tangled Program Graphs (TPGs) as an alternative for deep reinforcement learning in control-related tasks. In this approach, input signals are processed by simple programs that are combined in a graph structure. As a result, TPGs are less computationally demanding and their actions can be explained based on the graph structure. In this paper, we present our studies on the use of TPGs as an alternative for DRL in control-related tasks. In particular, we consider the problem of navigating an unmanned aerial vehicle (UAV) through the unknown environment based solely on the onboard LiDAR sensor. The results of our work show promising prospects for the use of TPGs in control related-tasks.

   @inproceedings{10715635,
     author = {Szolc, Hubert and Desnos, Karol and Kryjak, Tomasz},
     booktitle = {2024 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)},
     title = {Tangled Program Graphs as an alternative to DRL-based control algorithms for UAVs},
     year = {2024},
     volume = {},
     number = {},
     pages = {36--41},
     keywords = {Measurement;Laser radar;Navigation;Signal processing algorithms;Process control;Computer architecture;Deep reinforcement learning;Autonomous aerial vehicles;Safety;Tangled Program Graphs;TPG;Deep Reinforcement Learning;DRL;control algorithms;unmanned aerial vehicle;UAV},
     doi = {10.23919/SPA61993.2024.10715635},
     issn = {2326-0319},
     month = sep,
     projects = {Preludium},
     acronym = {SPA},
   }

2023

1. Sterowanie autonomicznym bezzalogowym statkiem powietrznym z wykorzystaniem uczenia przez wzmacnianie

   Pawel Miera, Hubert Szolc, and Tomasz Kryjak

   PAR Pomiary Automatyka Robotyka, Sep 2023

   DOI

2022

1. An efficient real-time FPGA-based ORB feature extraction for an UHD video stream for embedded visual SLAM

   Mateusz Wasala, Hubert Szolc, and Tomasz Kryjak

   Electronics, Sep 2022

   DOI
2. Automotive perception system evaluation with reference data from a UAV’s camera using ArUco markers and DCNN

   Krzysztof Blachut, Michal Danilowicz, Hubert Szolc, Mateusz Wasala, Tomasz Kryjak, and 1 more author

   Journal of Signal Processing Systems for Signal, Image, and Video Technology, Sep 2022

   DOI
3. Hardware-in-the-loop simulation of a UAV autonomous landing algorithm implemented in SoC FPGA

   Hubert Szolc and Tomasz Kryjak

   In , Sep 2022

   DOI
4. Real-time CLAHE algorithm implementation in SoC FPGA device for 4K UHD video stream

   Tomasz Kryjak, Krzysztof Blachut, Hubert Szolc, and Mateusz Wasala

   Electronics, Sep 2022

   DOI

2021

1. A simple vision-based navigation and control strategy for autonomous drone racing

   Artur Cyba, Hubert Szolc, and Tomasz Kryjak

   In , Sep 2021

   DOI
2. Automotive perception system evaluation with reference data obtained by a UAV

   Krzysztof Blachut, Michal Danilowicz, Hubert Szolc, Mateusz Wasala, Tomasz Kryjak, and 2 more authors

   In , Sep 2021

   DOI
3. Real-time FPGA implementation of parallel connected component labelling for a 4K video stream

   Marcin Kowalczyk, Piotr Ciarach, Dominika Przewlocka-Rus, Hubert Szolc, and Tomasz Kryjak

   Journal of Signal Processing Systems for Signal, Image, and Video Technology, Sep 2021

   DOI

2020

1. A vision based hardwares̄oftware realt̄ime control system for the autonomous landing of an UAV

   Krzysztof Blachut, Hubert Szolc, Mateusz Wasala, Tomasz Kryjak, and Marek Gorgon

   In , Sep 2020

   DOI
2. Optimisation of a Siamese neural network for realt̄ime energy efficient object tracking

   Dominika Przewlocka-Rus, Mateusz Wasala, Hubert Szolc, Krzysztof Blachut, and Tomasz Kryjak

   In , Sep 2020

   DOI