Jaafar Ahmed Abdulsaheb

University of Baghdad · Department of Electrical Engineering

A smart parking system based on the Internet of Things (IoT) can assist users in locating parking spaces in crowded regions by offering real-time availability updates online. This technology streamlines the car parking procedure, encompassing the entire process from vehicle entry to payment and subsequent leave. The system utilises NodeMCU, a set o...

The most important research area in robotics is navigation algorithms. Robot path planning (RPP) is the process of choosing the best route for a mobile robot to take before it moves. Finding an ideal or nearly ideal path is referred to as "path planning optimization." Finding the best solution values that satisfy a single or a number of objectives,...

Tis study investigates the feasibility of a mobile robot navigating and discovering its location in unknown environments, followed by the creation of maps of these navigated environments for future use. First, a real mobile robot named TurtleBot3 Burger was used to achieve the simultaneous localization and mapping (SLAM) technique for a complex env...

A disturbance/uncertainty estimation and disturbance rejection technique are proposed in this work and verified on a ground two-wheel differential drive mobile robot (DDMR) in the presence of a mismatched disturbance. The offered scheme is the an improved active disturbance rejection control (IADRC) approach-based enhanced dynamic speed controller....

This work considers the best path planning algorithm for a mobile robot that travels independently in an unknowable environment. To get around the limitations of unstable searches in the conventional Hunter-Prey Optimization Algorithm (HPO), the improved HPO optimization algorithm is used and introduces a new control parameter referred to as random...

This paper discusses the best path planning algorithm for an autonomous mobile robot in an unknown environment with irregular static and dynamic obstacles and a static and dynamic target based on the improved COOT (ICOOT) optimization algorithm. The ICOOT overcomes the drawbacks of unstable searches in the conventional COOT. The path planning probl...

This paper discusses an optimal path planning algorithm based on an Adaptive Multi Objective Artificial Bee Colony Algorithm (AMOABC) for three case studies. First case, two robots wants to reach the different target with two objectives; first objective is to find the minimum distance that is needed by the robot from the start position to the targe...

This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach...