Abrar Alajlan

Sensor Fusion Based Model for Collision Free Mobile Robot Navigation

Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot’s wheels, and 24 fuzzy rules for the robot’s movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes.

Multi-sensor based collision avoidance algorithm for mobile robot

Collision Avoidance (CA) systems have been used in wide range of different robotics areas and had extraordinary success in minimizing the risk of collisions. It is a critical requirement in building mobile robot systems where they all featured some kind of obstacle detection techniques in order to avoid two or more objects from colliding. The purpose of this paper is to present an algorithm for performing collision avoidance in mobile robot that is relying on the use of low-cost ultrasonic with infrared sensors, and involving some other modules, so that it can be easily used in real-time robotic applications. The proposed algorithm is implemented in multiple scenarios with several obstacles placed in different locations around the robot. Our experimental run shows that the robot has been successfully detecting obstacles and avoiding collisions along its path.

Development of efficient obstacle avoidance and line following mobile robot with the integration of fuzzy logic system in static and dynamic environments

Autonomous mobile robots have been widely used in many researches and applications. Mobile robots can be programmed to do specific tasks such as collision avoidance and trajectory planning. Various types of sensors and actuators are mounted on these robots for sensing the surrounding environment and making decisions accordingly. In this paper, we develop collision avoidance and line following techniques for mobile robot navigation in static and dynamic environments with the integration of fuzzy logic fusion. For the collision avoidance technique, eight proximity sensors are used to detect static and dynamic obstacles. The proposed fuzzy logic for the line following mechanism consists of one input and two outputs. The input is the difference between right and left ground sensors values whereas the outputs are the left and right speeds to steer the mobile robot. Several membership functions and fuzzy rules are designed. The proposed method has been successfully tested in Webots Pro simulator and in real time experiment.

Sorting N elements using quantum entanglement sets

To search for an element in an unsorted database, it requires O(N) operations using classical computers, where it takes only O(√ N) operations in quantum systems. In this paper, we provide an in-depth look at the existing quantum searching algorithms and emphasize the quantum entanglement feature to propose a new technique for sorting N elements and thus improve the sorting process.

An Optimal and Energy Efficient Multi-Sensor Collision-Free Path Planning Algorithm for a Mobile Robot in Dynamic Environments

There has been a remarkable growth in many different real-time systems in the area of autonomous mobile robots. This paper focuses on the collaboration of efficient multi-sensor systems to create new optimal motion planning for mobile robots. A proposed algorithm is used based on a new model to produce the shortest and most energy-efficient path from a given initial point to a goal point. The distance and time traveled, in addition to the consumed energy, have an asymptotic complexity of O(nlogn), where n is the number of obstacles. Real time experiments are performed to demonstrate the accuracy and energy efficiency of the proposed motion planning algorithm.