Publications

2025

1. AI

   

   Bridging Neural ODE and ResNet: A Formal Error Bound for Safety Verification

   Abdelrahman Sayed Sayed, Pierre-Jean Meyer, and Mohamed Ghazel

   In International Symposium on AI Verification, 2025

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   A neural ordinary differential equation (neural ODE) is a machine learning model that is commonly described as a continuousdepth generalization of a residual network (ResNet) with a single residual block, or conversely, the ResNet can be seen as the Euler discretization of the neural ODE. These two models are therefore strongly related in a way that the behaviors of either model are considered to be an approximation of the behaviors of the other. In this work, we establish a more formal relationship between these two models by bounding the approximation error between two such related models. The obtained error bound then allows us to use one of the models as a verification proxy for the other, without running the verification tools twice: if the reachable output set expanded by the error bound satisfies a safety property on one of the models, this safety property is then guaranteed to be also satisfied on the other model. This feature is fully reversible, and the initial safety verification can be run indifferently on either of the two models. This novel approach is illustrated on a numerical example of a fixed-point attractor system modeled as a neural ODE.

   @inproceedings{sayed2025bridgingneuraloderesnet,
     title = {Bridging Neural ODE and ResNet: A Formal Error Bound for Safety Verification},
     author = {Sayed, Abdelrahman Sayed and Meyer, Pierre-Jean and Ghazel, Mohamed},
     booktitle = {International Symposium on AI Verification},
     year = {2025},
     eprint = {2506.03227},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG},
     url = {https://openreview.net/forum?id=8r0dHcrZ2j},
   }

2023

1. Robotics

   

   Risk Assessment of an Autonomous Underwater Snake Robot in Confined Operations

   Abdelrahman Sayed Sayed

   In OCEANS 2023-Limerick, 2023

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   The growing interest in ocean discovery imposes a need for inspection and intervention in confined and demanding environments. Eely’s slender shape, in addition to its ability to change its body configurations, makes articulated underwater robots an adequate option for such environments. However, operation of Eely in such environments imposes demanding requirements on the system, as it must deal with uncertain and unstructured environments, extreme environmental conditions, and reduced navigational capabilities. This paper proposes a Bayesian approach to assess the risks of losing Eely during two mission scenarios. The goal of this work is to improve Eely’s performance and the likelihood of mission success. Sensitivity analysis results are presented in order to demonstrate the causes having the highest impact on losing Eely.

   @inproceedings{sayed2023risk,
     title = {Risk Assessment of an Autonomous Underwater Snake Robot in Confined Operations},
     author = {Sayed, Abdelrahman Sayed},
     booktitle = {OCEANS 2023-Limerick},
     pages = {1--9},
     year = {2023},
     organization = {IEEE},
     url = {https://ieeexplore.ieee.org/abstract/document/10244516},
   }

2. Control

   

   Design of a Fuzzy Type-2 Controller for 1-DOF Pitch Axis Twin Rotor System

   Abdelrahman Sayed Sayed, Walid K Shaker, Hossam Hassan Ammar, and 2 more authors

   In 2023 International Conference on Control, Automation and Diagnosis (ICCAD), 2023

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   This paper presents the design, manufacturing, modeling, and control of a novel 1-DOF pitch axis Twin Rotor system. An IMU sensor is used to precisely access the desired pitch angle of the system. A type-2 fuzzy controller is designed and implemented to achieve fast rise time and low overshoot, which are the desired response specifications for the system. In terms of overshoot and settling time, the performance of the type-2 fuzzy-PID controller is compared to that of the type-l fuzzy-PID controller and the conventional PID controller. The type-2 fuzzy-PID controller’s performance is promising when compared to that of the other controllers, proving that it is useful for taming the Twin Rotor system’s non-linearities.

   @inproceedings{sayed2023design,
     title = {Design of a Fuzzy Type-2 Controller for 1-DOF Pitch Axis Twin Rotor System},
     author = {Sayed, Abdelrahman Sayed and Shaker, Walid K and Ammar, Hossam Hassan and Azar, Ahmad Taher and Njima, Chakib Ben},
     booktitle = {2023 International Conference on Control, Automation and Diagnosis (ICCAD)},
     pages = {1--6},
     year = {2023},
     organization = {IEEE},
     url = {https://ieeexplore.ieee.org/abstract/document/10152432},
   }

2020

1. Robotics

   

   Centralized multi-agent mobile robots SLAM and navigation for COVID-19 field hospitals

   Abdelrahman Sayed Sayed, Hossam Hassan Ammar, and Rafaat Shalaby

   In 2020 2nd Novel intelligent and leading emerging sciences conference (NILES), 2020

   Abs Bib PDF Video

   In this paper we focus on the proof of concept prototype of fully autonomous centralized Multi-Robot System (MRS) consisting of a Hexapod walking robot and a six wheeled mobile robot. Recently, there has been an increasing demand for such systems as they can be involved in several tasks such as collaborative search and rescue, surveillance, monitoring, and disinfecting Field hospitals. To name a few, COVID-19 pandemic showed the weak points in the medical sector around the world, including those in the most advanced nations that had to go through hard decisions due to the lack of medical supplies and personal protective equipment. The developed system was rapidly adjusted due to COVID-19 pandemic to perform additional tasks like disinfection and remote body temperature detection. The developed system abide by ISO 13482 safety requirements for personal care robots, meaning it will be used and deployed in Field hospitals. We implemented the proposed approach in a game setting of a field hospital where the Hexapod is used to scan and draw a map of the Field hospital environment and to draw a path then the six wheeled mobile robot acts as a medical cargo delivery that enters based on the predefined map and path.

   @inproceedings{sayed2020centralized,
     title = {Centralized multi-agent mobile robots SLAM and navigation for COVID-19 field hospitals},
     author = {Sayed, Abdelrahman Sayed and Ammar, Hossam Hassan and Shalaby, Rafaat},
     booktitle = {2020 2nd Novel intelligent and leading emerging sciences conference (NILES)},
     pages = {444--449},
     year = {2020},
     organization = {IEEE},
     url = {https://ieeexplore.ieee.org/abstract/document/9257919},
   }

2. AI & Robotics

   Experimental modeling of hexapod robot using artificial intelligence

   Abdelrahman Sayed Sayed, Amr Ahmed Mohamed, Ahmed Magd Aly, and 4 more authors

   In The International Conference on Artificial Intelligence and Computer Vision, 2020

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   Hexapod Robots gave us the opportunity to study walking robots without facing problems such as stability and expensive custom made hardware. It has a great deal of flexibility in moving over different terrains even if some legs become malfunctioned or facing some difficulties in movement. In this study the kinematic analysis of CH3-R 18DOF Hexapod Robot is discussed where each leg contains three revolute joints in order to mimic the structure of a spider. To develop the overall kinematic model of CH3-R robot, direct and inverse kinematic analyses for each leg have been considered where the Denavit-Hartenberg (D-H) conventions will be used to perform the forward kinematic analysis of the six-legged robot while the inverse kinematics are obtained by simplifying the architecture of the robot into 7 modules, a hexagon trunk and 6 limbs between the trunk and the ground. A neural network (NN) model was employed in order to compare and decide the angles prediction, training time and overall performance with the ones obtained from the analytical solution of the inverse kinematics. The data points used for training the two models and testing their performance was acquired from giving the robot an initial and final position and recording the change in the coordinates and time by using an IMU sensor.

   @inproceedings{sayed2020experimental,
     title = {Experimental modeling of hexapod robot using artificial intelligence},
     author = {Sayed, Abdelrahman Sayed and Mohamed, Amr Ahmed and Aly, Ahmed Magd and Hassan, Youssef Mohamed and Abdulaziz, Abdallah Mahir and Ammar, Hossam Hassan and Shalaby, Rafaat},
     booktitle = {The International Conference on Artificial Intelligence and Computer Vision},
     pages = {26--36},
     year = {2020},
     organization = {Springer},
     url = {https://link.springer.com/chapter/10.1007/978-3-030-44289-7_3},
   }

3. AI & Robotics

   Deep learning based kinematic modeling of 3-RRR parallel manipulator

   Abdelrahman Sayed Sayed, Ahmad Taher Azar, Zahra Fathy Ibrahim, and 3 more authors

   In The International Conference on Artificial Intelligence and Computer Vision, 2020

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   This paper presents a novel low cost design for a 3-RRR Planar Parallel Manipulator (PPM). These manipulators proved their superiority over serial manipulators due to their speed, precision and smaller work space where the work space area is accounted for in the design to ensure that the robot is performing its task in a smooth and simple way without getting into any singularity points. The challenge with PPM is to obtain the kinematic constraint equations of the manipulator due to their complex non-linear behavior. Screw theory is a new approach that is used to compute the direct and inverse kinematics based on the relation between each link and its’ predecessor. The design is then inserted into ADAMS to study its dynamical behavior and to obtain a data set that would be used in analyzing the system in MATLAB. A Neuro-Fuzzy Inference System (NFIS) model was constructed in order to predict the end-effector position inside the work space and it is tuned with Particle swarm optimization (PSO) and Genetic algorithm (GA).

   @inproceedings{sayed2020deep,
     title = {Deep learning based kinematic modeling of 3-RRR parallel manipulator},
     author = {Sayed, Abdelrahman Sayed and Azar, Ahmad Taher and Ibrahim, Zahra Fathy and Ibrahim, Habiba A and Mohamed, Nada Ali and Ammar, Hossam Hassan},
     booktitle = {The International Conference on Artificial Intelligence and Computer Vision},
     pages = {308--321},
     year = {2020},
     organization = {Springer},
     url = {https://link.springer.com/chapter/10.1007/978-3-030-44289-7_29},
   }

2019

1. AI & Robotics

   Neuro-fuzzy system for 3-DOF parallel robot manipulator

   Ahmad Taher Azar, Ahmed Magd Aly, Abdelrahman Sayed Sayed, and 2 more authors

   In 2019 Novel Intelligent and Leading Emerging Sciences Conference (NILES), 2019

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   Planar Parallel manipulators (PPMs) are widely used these days, as they have many advantages compared to their serial counterparts. However, their inverse and direct kinematics are hard to obtain, due to the complexity of the manipulators’ behavior. Therefore, this paper provides a comparative analysis for two methods that were used to obtain the inverse kinematics of a 3-RRR manipulator. Instead of the conventional algebraic and graphical methods used for attaining the mathematical models for such manipulators, an adaptive neuro-fuzzy inference structure (AFNIS) model was alternatively employed. It is then compared with a traditional neural network (NN) model for the same manipulator in order to ascertain which model is better in angles prediction, training time and overall performance. The data points used for both training the models and testing their performance are acquired from motion studies in SolidWorks.

   @inproceedings{azar2019neuro,
     title = {Neuro-fuzzy system for 3-DOF parallel robot manipulator},
     author = {Azar, Ahmad Taher and Aly, Ahmed Magd and Sayed, Abdelrahman Sayed and Radwan, Mahmoud ElBakry and Ammar, Hossam Hassan},
     booktitle = {2019 Novel Intelligent and Leading Emerging Sciences Conference (NILES)},
     volume = {1},
     pages = {1--5},
     year = {2019},
     organization = {IEEE},
     url = {https://ieeexplore.ieee.org/abstract/document/8909333},
   }

2. Control & Robotics

   PID controller for 2-DOFs twin rotor MIMO system tuned with particle swarm optimization

   Ahmad Taher Azar, Abdelrahman Sayed Sayed, Abdalla Saber Shahin, and 2 more authors

   In international conference on advanced intelligent systems and informatics, 2019

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   This paper presents the modelling and control of a 2-DOFs Twin rotor multi input multi output (MIMO) system which is a laboratory setup resembling the dynamics of a helicopter. In this paper, the system modelling process is done using the common conventional mathematical model based on Euler-Lagrange method. The transfer functions of the model are used in the different tuning methods to reach the optimal PID gain values. The study uses conventional Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) controllers to obtain a robust controller for the system. Particle Swarm optimization (PSO) technique was used to tune the controller parameters. A state space model is obtained considering some design assumptions and simplifications. Statistical measurement and convergence analysis is evaluated for the optimization of gain parameters of the PID controller for 2-DOF Twin rotor system using PSO by iteratively minimizing integral of squared error (ISE) and integral of time multiplied by the squared error (ITSE). The results are verified through simulations and experiments.

   @inproceedings{azar2019pid,
     title = {PID controller for 2-DOFs twin rotor MIMO system tuned with particle swarm optimization},
     author = {Azar, Ahmad Taher and Sayed, Abdelrahman Sayed and Shahin, Abdalla Saber and Elkholy, Hassan Ashraf and Ammar, Hossam Hassan},
     booktitle = {international conference on advanced intelligent systems and informatics},
     pages = {229--242},
     year = {2019},
     organization = {Springer},
     url = {https://link.springer.com/chapter/10.1007/978-3-030-31129-2_22},
   }