For people with severe disabilities who do not suit with conventional wheelchair driving systems, like the manual ones or the electric with joysticks, for example; alternatives and solutions have been researched, leading to a proposal that has been developed based on an interface that simulates the control of a wheel-driven platform, such as a wheelchair, with an integrated robotic arm, both controlled by head gestures and gaze tracking. A webcam and a facial recognition algorithm are used to read the input movements, and a simulation program to perform the actions.
@article{finaldemo,title={Head and gaze tracking control for a smart wheelchair with a robot arm},author={Stevedan, Ogochukwu, Omodolor and Pablo, Mañas, Pellejero and Javier, Pedrosa, Alias},year={2022},my={true}}
Control of the Tiago robot using Pose Estimation and Position-based visual servoing
In this paper, a strategy to control the position of the end-effector and the mobile base of the Tiago robot using visual feedback from a stereo camera is explained. To accomplish this, position based visual servoing technique is employed base on the estimation of position and depth information of the object been tracked. In order to ensure smooth position estimation, multple tecniques like median filtering and kalman filter was used.
@article{VisualServoing,title={Control of the Tiago robot using Pose Estimation and Position-based visual servoing},author={Stevedan, Ogochukwu, Omodolor and Alberto, Sanfeliu, Cortes},year={2022},my={true}}
Implementation of a tossing ball robot using reinforcement learning
Omodolor Stevedan, Cornella Guillem, and Sardà David
n this project, we are implementing a tossing ball robot that learns by means of Reinforcement Learning. The robot is able to determine its optimal actions by using Computer Vision techniques, combined with different solutions, such as Q-learning and DDPG+HER, which have been broadly researched to have a higher accuracy. Simulations have also been done with OpenAI Gym and ROS (Gazebo), prior to the real implementation, to deeply study the best approach and prepare the model for the real scenario. The following videos are some of the results of the thesis
@article{robot_learning,title={Implementation of a tossing ball robot using reinforcement learning},author={Stevedan, Ogochukwu, Omodolor and Guillem, Cornella and David, Hernández, Sardà},year={2022},my={true}}
Distance and orientation-based formation control of UAVs and coordination with UGVs
Omodolor Stevedan
UPC, Escola Tècnica Superior d’Enginyeria Industrial de Barcelona, Departament d’Enginyeria Química, Oct 2022
2020
Simulation and control of a BLDC motor with methods on real-time data exchange and visualization
Omodolor Stevedan
UPC, Escola d’Enginyeria de Barcelona Est, Departament d’Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Jul 2020
Distance and orientation-based formation control of UAVs and coordination with UGVsUPC, Escola Tècnica Superior d’Enginyeria Industrial de Barcelona, Departament d’Enginyeria Química, Oct 2022
Simulation and control of a BLDC motor with methods on real-time data exchange and visualizationUPC, Escola d’Enginyeria de Barcelona Est, Departament d’Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Jul 2020