Multi Sensor Fusion Based Framework For Efficient Mobile Robot Collision Avoidance and Path Following System

The field of autonomous mobile robotics has recently gained the interests of many researchers. Due to the specific needs required by various applications of mobile robot systems (especially in navigation), designing a real-time obstacle avoidance and path following robot system has become the backbone of controlling robots in unknown environments. Therefore, an efficient collision avoidance and path following methodology is needed to develop an intelligent and effective autonomous mobile robot system. Mobile robots 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. A new technique for line following and collision avoidance in the mobile robotic systems is introduced. The proposed technique relies on the use of infrared sensors and involves a reasonable level of calculations, to be easily used in real-time control applications. In addition, a fusion model based on fuzzy logic is proposed. 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 twenty four fuzzy rules for the robot’s movement. Webots Pro simulator is used for modeling the environment and robot to show the ability of the robot to follow a path, detect obstacles, and navigate around them to avoid collision. It also shows that the robot has been successfully following extremely congested curves and has avoided any obstacle that emerged on its path. 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 and multiple robots while avoiding obstacles in different shapes and sizes. The proposed methodology reduced the traveled distance of the mobile robot, as well as minimized the energy consumption and the distance between the robot and the obstacle detected as compared to a non-fuzzy logic approach

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.https://doi.org/10.3390/s1601002

Fuzzy Logic Control for Autonomous Mobile Robots in Static and Dynamic Environments

Autonomous mobile robots have been widely used in many researches and applications. In this work, we develop collision avoidance and line following techniques for mobile robot navigation in static and dynamic environments with the integration of fuzzy logic fusion. Eight proximity sensors are used to detect different obstacles whereas three ground sensors are used to detect the line underneath the robot. The proposed method has been successfully tested in Webots Pro simulator and in in real time experiment

Energy-Efficient Dynamic Motion Control for Wheeled Mobile Robots Using Low Cost Resources

Mobile robotic systems have gained significant attention in human interest, where they represent such a complex interaction with challenging environments. Some applications require continuous operations, so the robots motions have to be optimized to reduce their energy consumption. In addition, total energy consumption in mobile robotic applications is one of the most important issues that has not been adequately considered. Mobile robots are limited by the amount of energy supplied by the batteries they carry where a new supply of energy while working is too expensive to be realistic. Thus, this work aiming to minimize the energy consumption of a wheeled mobile robot in dynamic environments

Analytical Study of Pre-Congestion Notification (PCN) Techniques

Maintaining the quality of service (QOS) and controlling the network congestion are quite complicated tasks. They cause degrading the performance of the network, and disturbing the continuous communication process. To overcome these issues, one step towards this dilemma has been taken in form of Pre-congestion notification (PCN) technique. PCN uses a packet marking technique within a PCN domain over IP networks. It is notified by egress node that works as guard at entry point of network. Egress node gives feedback to communicating servers whether rate on the link is exceeded than configured admissible threshold or within the limit. Based on this feedback, admission decisions are taken to determine whether to allow/block new coming flows or terminate already accepted. The actual question is about selection of right algorithm for PCN domain. In this paper, we investigate the analytical behavior of some known PCN algorithms. We make slide modifications in originality of PCN algorithms without disquieting working process in order to employ those within similar types of scenarios. Our goal is to simulate them either in highly congested or less congested realistic scenarios. On the basis of simulation done in ns2, we are able to recommend each PCN algorithm for specific conditions. Finally, we develop a benchmark that helps researchers and scientific communities to pick the right algorithm. Furthermore, the benchmark is designed to achieve specific objectives according to the users’ requirements without congesting the network

TERP: A Trusted and Energy Efficient Routing Protocol for Wireless Sensor Networks (WSNs)

Recently, Wireless Sensor Networks (WSNs) have got researchers attention due to its various useful and helpful applications in the real world with low cost sensors. The task of the sensors is to collect data from the environment and send it to the central node (sink node). However, the power is limited in these sensors and therefore it has a limited lifetime which is a big deal in WSNs. Another important issue in WSNs is the level of security. Since these sensor nodes exchange and transmit data among the network, the security of the data can be at risk. Hence, In this poster, we propose a novel trusted and energy efficient routing protocol (TERP), which is based on the Destination Sequenced Distance Vector Protocol (DSDV). TERP can avoid any malicious nodes (untrusted nodes) and thus increase the security level in the network, and decrease the power consumption level