Path planning is an essential concern in robotic systems, and it refers to the process of determining a safe and optimal path starting from the source state to the goal one within dynamic environments. We proposed an improved path planning method in this article, which merges the Dijkstra algorithm for path planning with Potential Field (PF) collision avoidance. In real-time, the method attempts to produce multiple paths as well as determine the suitable path that’s both short and reliable (safe). The Dijkstra method is employed to produce multiple paths, whereas the Potential Field is utilized to assess the safety of each route and choose the best one. The proposed method creates links between the routes, enabling the robot to swap between them if it discovers a dynamic obstacle on its current route. Relating to path length and safety, the simulation results illustrate that Dynamic Dijkstra-Potential Field (Dynamic D-PF) achieves better performance than the Dijkstra and Potential Field each separately, and going to make it a promising solution for the application of robotic automation within dynamic environments.
This paper presents the designing of path planning system in an environment contains a set of static polygon obstacles localized and distributed randomly by using differential drive mobile robot. In this paper the designed algorithm (two dimensional path planning algorithm) is proposed in order of investigate the path planning of mobile robot with free collision using the visibility binary tree algorithm. The suggested algorithm is compared with the virtual circles tangents algorithm in the time of arrival and the longest of the path to the target. The aim of this paper is to get an algorithm has better performance than the other algorithms and get less time of arrival and shortest path with free collision.
Path-planning is a crucial part of robotics, helping robots move through challenging places all by themselves. In this paper, we introduce an innovative approach to robot path-planning, a crucial aspect of robotics. This technique combines the power of Genetic Algorithm (GA) and Probabilistic Roadmap (PRM) to enhance efficiency and reliability. Our method takes into account challenges caused by moving obstacles, making it skilled at navigating complex environments. Through merging GA’s exploration abilities with PRM’s global planning strengths, our GA-PRM algorithm improves computational efficiency and finds optimal paths. To validate our approach, we conducted rigorous evaluations against well-known algorithms including A*, RRT, Genetic Algorithm, and PRM in simulated environments. The results were remarkable, with our GA-PRM algorithm outperforming existing methods, achieving an average path length of 25.6235 units and an average computational time of 0.6881 seconds, demonstrating its speed and effectiveness. Additionally, the paths generated were notably smoother, with an average value of 0.3133. These findings highlight the potential of the GA-PRM algorithm in real-world applications, especially in crucial sectors like healthcare, where efficient path-planning is essential. This research contributes significantly to the field of path-planning and offers valuable insights for the future design of autonomous robotic systems.
Obstacle avoidance in mobile robot path planning represents an exciting field of robotics systems. There are numerous algorithms available, each with its own set of features. In this paper a Witch of Agnesi curve algorithm is proposed to prevent a collision by the mobile robot’s orientation beyond the obstacles which represents an important problem in path planning, further, to achieve a minimum arrival time by following the shortest path which leads to minimizing power loss. The proposed approach considers the mobile robot’s platform equipped with the LIDAR 360o sensor to detect obstacle positions in any environment of the mobile robot. Obstacles detected in the sensing range of the mobile robot are dealt with by using the Witch of Agnesi curve algorithm, this establishes the obstacle’s apparent vertices’ virtual minimum bounding circle with minimum error. Several Scenarios are implemented and considered based on the identification of obstacles in the mobile robot environment. The proposed system has been simulated by the V-REP platform by designing several scenarios that emulate the behavior of the robot during the path planning model. The simulation and experimental results show the optimal performance of the mobile robot during navigation is obtained as compared to the other methods with minimum power loss and also with minimum error. It’s given 96.3 percent in terms of the average of the total path while the Bezier algorithm gave 94.67 percent. While in experimental results the proposed algorithm gave 93.45 and the Bezier algorithm gave 92.19 percent.
Computer network routing is performed based on routing protocol decisions. Open Shortest Path First OSPF is the most known routing protocol. It suffers from congestion problem since it generally uses single (least cost) path to deliver information. Some times OSPF delivers information using more than one path in the case of more than one path have the same cost value. This condition is rarely achieved in normal cases. In this work OSPF is developed to distribute information load across multiple paths and makes load distribution as general case for the routing protocol. The modification supposes no protocol replacement and uses the existing protocol facilities. This makes faster information delivery, load balancing, less congestion, and with little modification on the built in OSPF functions. Disjoint paths are calculated then the costs of the best set of them are adapted using approporate ratio.
A robot is a smart machine that can help people in their daily lives and keep everyone safe. the three general sequences to accomplish any robot task is mapping the environment, the localization, and the navigation (path planning with obstacle avoidance). Since the goal of the robot is to reach its target without colliding, the most important and challenging task of the mobile robot is the navigation. In this paper, the robot navigation problem is solved by proposed two algorithms using low-cost IR receiver sensors arranged as an array, and a robot has been equipped with one IR transmitter. Firstly, the shortest orientation algorithm is proposed, the robot direction is corrected at each step of movement depending on the angle calculation. secondly, an Active orientation algorithm is presented to solve the weakness in the preceding algorithm. A chain of the active sensors in the environment within the sensing range of the virtual path is activated to be scan through the robot movement. In each algorithm, the initial position of the robot is detected using the modified binary search algorithm, various stages are used to avoid obstacles through suitable equations focusing on finding the shortest and the safer path of the robot. Simulation results with multi-resolution environment explained the efficiency of the algorithms, they are compatible with the designed environment, it provides safe movements (without hitting obstacles) and a good system control performance. A Comparison table is also provided.
This paper presents the design of a path planning system in an environment that contains a set of static and dynamic polygon obstacles localized randomly. In this paper, an algorithm so-called (Polygon shape tangents algorithm) is proposed to move a mobile robot from a source point to a destination point with no collision with surrounding obstacles using the visibility binary tree algorithm. The methodology of this algorithm is based on predicting the steps of a robot trajectory from the source to the destination point. The polygon shapes tangent algorithm is compared with the virtual circles' tangents algorithm for different numbers of static and dynamic polygon obstacles for the time of arrival and the length of the path to the target. The obtained result shows that the used algorithm has better performance than the other algorithms and gets less time of arrival and shortest path with free collision.
The main problem of line follower robot is how to make the mobile robot follows a desired path (which is a line drawn on the floor) smoothly and accurately in shortest time. In this paper, the design and implementation of a complex line follower mission is presented by using Matlab Simulink toolbox. The motion of mobile robot on the complex path is simulated by using the Robot Simulator which is programed in Matlab to design and test the performance of the proposed line follower algorithm and the designed PID controller. Due to the complexity of selection the parameters of PID controller, the Particle Swarm Optimization (PSO) algorithm are used to select and tune the parameters of designed PID controller. Five Infrared Ray (IR) sensors are used to collect the information about the location of mobile robot with respect to the desired path (black line). Depending on the collected information, the steering angle of the mobile robot will be controlled to maintain the robot on the desired path by controlling the speed of actuators (two DC motors). The obtained simulation results show that, the motion of mobile robot is still stable even the complex maneuver is performed. The hardware design of the robot system is perform by using the Arduino Mobile Robot (AMR). The Simulink Support Package for Arduino and control system toolbox are used to program the AMR. The practical results show that the performances of real mobile robot are exactly the same of the performances of simulated mobile robot.
Although the Basic RRT algorithm is considered a traditional search method, it has been widely used in the field of robot path planning (manipulator and mobile robot), especially in the past decade. This algorithm has many features that give it superiority over other methods. On the other hand, the Basic RRT suffers from a bad convergence rate (it takes a long time until finding the goal point), especially in environments with cluttered obstacles, or whose targets are located in narrow passages. Many studies have discussed this problem in recent years. This paper introduces an improved method called (Hybrid RRT-A*) to overcome the shortcomings of the original RRT, specifically slow convergence and cost rate. The heuristic function of A-star algorithm is combined with RRT to decrease tree expansion and guide it towards the goal with less nodes and time. Various experiments have been conducted with different environment scenarios to compare the proposed method with the Basic RRT and A-star under the same conditions, which have shown remarkable performance. The time consumed to find the path of the worst one of these scenarios is about 4.9 seconds, whereas it is 18.3 and 34 for A-star and RRT, respectively.
Arial images are very high resolution. The automation for map generation and semantic segmentation of aerial images are challenging problems in semantic segmentation. The semantic segmentation process does not give us precise details of the remote sensing images due to the low resolution of the aerial images. Hence, we propose an algorithm U-Net Architecture to solve this problem. It is classified into two paths. The compression path (also called: the encoder) is the first path and is used to capture the image's context. The encoder is just a convolutional and maximal pooling layer stack. The symmetric expanding path (also called: the decoder) is the second path, which is used to enable exact localization by transposed convolutions. This task is commonly referred to as dense prediction, which is completely connected to each other and also with the former neurons which gives rise to dense layers. Thus it is an end-to-end fully convolutional network (FCN), i.e. it only contains convolutional layers and does not contain any dense layer because of which it can accept images of any size. The performance of the model will be evaluated by improving the image using the proposed method U-NET and obtaining an improved image by measuring the accuracy compared with the value of accuracy with previous methods.
Due to the last increase in data and information technology, the need to use robots in many life areas is increased. There is a great diversity in this field, depending on the type of task required, as the robot enters the parcels of air, land, and water. In this paper, a robot's mission designed to move things is concentrated, relying on line-tracing technology that makes it easy to track its path safely, the RFID is distributed in its approach. When the robot reads the RFID tag, it stops until it raises the load from above, the robot continues its path toward the target. When an obstacle obstructs the robot path, the robot deviates and returns after a while to its previous approach. All this technology is implemented using a new algorithm which is programmed using the visual basic program. The robot designed to transfer the stored material is used according to a site known as an identifier that is identified by the RFID value, where the robot is programmed through a microcontroller and a unique store program that determines the current location and the desired location, then is given the task for the robot to do it as required. The robot is controlled using an ATmega controller to control other parts connected to the electronic circuit, the particular infrared sensor, and ultrasound to avoid potential obstacles within the robot's path to reach the target safely. In addition to this, the robot is made up of an RFID sensor to give unique to each desired target site. Through the console, it is possible to know the link indicated by the target. The H-bridge is also used to obtain a particular command and guide the robot as needed to move freely in all directions and a DC motor which is unique for moving wheels at the desired speed, and Bluetooth for programmable and secure wireless transmission and reception with all these parts through a unique program that also uses application inventory. The robot has proven to be a great success in performing the required task through several tests that have been practically performed.
In this paper two theoretical models have been considered for the prediction of path loss for two different districts in Mosul city, using MATLAB 7.4 program. The Walfisch-Ikegami (W-I) model for uniform heights and similar buildings in the Karama district . The other model is Okumura-Hata (OH) model applied for irregular and dissimilar buildings in the Almajmoa'a district. The information buildings heights are obtained from the civil Eng. Depart. in Mosul university. In this paper it can be shown that The effect of distance in regular area (karama) on path loss is about 10 dB larger than irregular area (Almajmoa'a), and The effect of varying antenna height in regular area (karama) on path loss is about 7 dB greater than irregular area (Almajmoa'a) for 40 meter variation.
This paper deals with the navigation of a mobile robot in unknown environment using artificial potential field method. The aim of this paper is to develop a complete method that allows the mobile robot to reach its goal while avoiding unknown obstacles on its path. An approach proposed is introduced in this paper based on combing the artificial potential field method with fuzzy logic controller to solve drawbacks of artificial potential field method such as local minima problems, make an effective motion planner and improve the quality of the trajectory of mobile robot.
Many assistive devices have been developed for visually impaired (VI) person in recent years which solve the problems that face VI person in his/her daily moving. Most of researches try to solve the obstacle avoidance or navigation problem, and others focus on assisting VI person to recognize the objects in his/her surrounding environment. However, a few of them integrate both navigation and recognition capabilities in their system. According to above needs, an assistive device is presented in this paper that achieves both capabilities to aid the VI person to (1) navigate safely from his/her current location (pose) to a desired destination in unknown environment, and (2) recognize his/her surrounding objects. The proposed system consists of the low cost sensors Neato XV-11 LiDAR, ultrasonic sensor, Raspberry pi camera (CameraPi), which are hold on a white cane. Hector SLAM based on 2D LiDAR is used to construct a 2D-map of unfamiliar environment. While A* path planning algorithm generates an optimal path on the given 2D hector map. Moreover, the temporary obstacles in front of VI person are detected by an ultrasonic sensor. The recognition system based on Convolution Neural Networks (CNN) technique is implemented in this work to predict object class besides enhance the navigation system. The interaction between the VI person and an assistive system is done by audio module (speech recognition and speech synthesis). The proposed system performance has been evaluated on various real-time experiments conducted in indoor scenarios, showing the efficiency of the proposed system.
In this paper, a new algorithm called the virtual circle tangents is introduced for mobile robot navigation in an environment with polygonal shape obstacles. The algorithm relies on representing the polygonal shape obstacles by virtual circles, and then all the possible trajectories from source to target is constructed by computing the visible tangents between the robot and the virtual circle obstacles. A new method for searching the shortest path from source to target is suggested. Two states of the simulation are suggested, the first one is the off-line state and the other is the on-line state. The introduced method is compared with two other algorithms to study its performance.
The last few years Quadrotor became an important topic, many researches have implemented and tested concerning that topic. Quadrotor also called an unmanned Aerial Vehicle (UAV), it's highly used in many applications like security, civil applications, aid, rescue and a lot of other applications. It’s not a conventional helicopter because of small size, low cost and the ability of vertical and takeoff landing (VTOL). The models kept an eye on quadrotors were presented, the advancement of this new kind of air vehicle is hindered for a very long while because of different reasons, for example, mechanical multifaceted nature, enormous size and weight, and challenges in charge particularly. Just as of late a lot of interests and endeavors have been pulled in on it; a quadrotor has even become a progressively discretionary vehicle for useful application. Quadrotor can be used in variable, different , outdoor and indoor missions; these missions should be implemented with high value of accuracy and quality. In this work two scenarios suggested for different two missions. First mission the quadrotor will be used to reach different goals in the simulated city for different places during one flight using path following algorithm. The second mission will be an indoor arrival mission, during that mission quadrotor will avoid obstacles by using only Pure pursuit algorithm (PPA). To show the benefit of using the new strategy it will compare with a victor field histogram algorithm (VFH) which is used widely in robotics for avoiding obstacles, the comparison will be in terms of reaching time and distance of reaching the goal. The Gazebo Simulator (GS) is used to visualize the movement of the quadrotor. The gazebo has another preferred position it helps to show the motion development of the quadrotor without managing the mathematical model of the quadrotor. The Robotic Operating System (ROS) is used to transfer the data between the MATLAB Simulink program and the Gazebo Simulator. The diversion results show that, the proposed mission techniques win to drive the quarter on the perfect route similarly at the limit with regards to the quadrotor to go without hitting any obstacle in the perfect way.
The Leader detecting and following are one of the main challenges in designing a leader-follower multi-robot system, in addition to the challenge of achieving the formation between the robots, while tracking the leader. The biological system is one of the main sources of inspiration for understanding and designing such multi-robot systems, especially, the aggregations that follow an external stimulus such as light. In this paper, a multi-robot system in which the robots are following a spotlight is designed based on the behavior of the Artemia aggregations. Three models are designed: kinematic and two dynamic models. The kinematic model reveals the light attraction behavior of the Artemia aggregations. The dynamic model will be derived based on the newton equation of forces and its parameters are evaluated by two methods: first, a direct method based on the physical structure of the robot and, second, the Least Square Parameter Estimation method. Several experiments are implemented in order to check the success of the three proposed systems and compare their performance. The experiments are divided into three scenarios of simulation according to three paths: the straight line, circle, zigzag path. The V-Rep software has been used for the simulation and the results appeared the success of the proposed system and the high performance of tracking the spotlight and achieving the flock formation, especially the dynamic models.
This paper presents a developed algorithm for reliability sensitivity analysis of engineering networks. Reliability Modeling is proposed for the Iraqi Kurdistan Regional Power Network (IKRPN) using Symbolic Reliability function of the model. The written Pascal code for the developed algorithm finds efficiently path sets and cut sets of the model. Reliability and Unreliability indices are found. The sensitivity of these indices are found with respect to the variation of the network’s elements reliabilities
Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mobile vehicles. Several studies have tackled the task offloading problem in the VFC field. However, recent studies have not carefully addressed the transmission path to the destination node and did not consider the energy consumption of vehicles. This paper aims to optimize the task offloading process in the VFC system in terms of latency and energy objectives under deadline constraint by adopting a Multi-Objective Evolutionary Algorithm (MOEA). Road Side Units (RSUs) x-Vehicles Mutli- Objective Computation offloading method (RxV-MOC) is proposed, where an elite of vehicles are utilized as fog nodes for tasks execution and all vehicles in the system are utilized for tasks transmission. The well-known Dijkstra's algorithm is adopted to find the minimum path between each two nodes. The simulation results show that the RxV-MOC has reduced significantly the energy consumption and latency for the VFC system in comparison with First-Fit algorithm, Best-Fit algorithm, and the MOC method.
The demand for application of mobile robots in performing boring and extensive tasks are increasing rapidly due to unavailability of human workforce. Navigation by humans within the warehouse is one among such repetitive and exhaustive task. Autonomous navigation of mobile robots for picking and dropping the shelves within the warehouse will save time and money for the warehousing business. Proposing an optimization model for automated storage and retrieval systems by the goals of its planning is investigated to minimize travel time in multi-robot systems. This paper deals with designing a system for storing and retrieving a group of materials within an environment arranged in rows and columns. Its intersections represent storage locations. The title of any subject is indicated by the row number and the column in it. A method was proposed to store and retrieve a set of requests (materials) using a number of robots as well as one receiving and delivery port. Several simulation results are tested to show this improvement in length of path and time of arrival.
In maze maneuvering, it is needed for a mobile robot to feasibly plan the shortest path from its initial posture to the desired destination in a given environment. To achieve that, the mobile robot is combined with multiple distance sensors to assist the navigation while avoiding obstructing obstacles and following the shortest path toward the target. Additionally, a vision sensor is used to detect and track colored objects. A new algorithm is proposed based on different type of utilized sensors to aid the maneuvering of differential drive mobile robot in an unknown environment. In the proposed algorithm, the robot has the ability to traverse surrounding hindrances and seek for a particular object based on its color. Six infrared sensors are used to detect any located obstacles and one color detection sensor is used to locate the colored object. The Mobile Robotics Simulation Toolbox in Matlab is used to test the proposed algorithm. Three different scenarios are studied to prove the efficiency of the proposed algorithm. The simulation results demonstrate that the mobile robot has successfully accomplished the tracking and locating of a colored object without collision with hurdles.
Although the advanced technology in satellites and optical fiber communication systems exists now a day, but the researches in HF sky wave propagation for Mesopotamia (Iraq) area is suffered from shortage. In this paper, the novelty is that the communication path from Baghdad to any distance out of Iraqi border had been predicted, calculated and measured experimentally by using real data (Ionogram) supplemented by Nicosia Ionosound station 1000Km from Baghdad and a radio station model TS-130SE as a transmitter. The Predicted results generated by using MATLAB and NTIA/ITS software package like VOACAP. Radio communication using TS-130SE with 36 countries had been done experimentally. A comparison between the theoretical and experimental results was done. The experimental results were in the range of the predicated results which emphasis proposed method Presented in this paper .
Gait as a biometric can be used to identify subjects at a distance and thus it receives great attention from the research community for security and surveillance applications. One of the challenges that affects gait recognition performance is view variation. Much work has been done to tackle this challenge. However, the majority of the work assumes that gait silhouettes are captured by affine cameras where only the height of silhouettes changes and the difference in viewing angle of silhouettes in one gait cycle is relatively small. In this paper, we analyze the variation in gait recognition performance when using silhouettes from projective cameras and from affine cameras with different distance from the center of a walking path. This is done by using 3D models of walking people in the gallery set and 2D gait silhouettes from independent (single) cameras in the probe set. Different factors that affect matching 3D human models with 2D gait silhouettes from single cameras for view-independent gait recognition are analyzed. In all experiments, we use 258 multi-view sequences belong to 46 subjects from Multi-View Soton gait dataset. We evaluate the matching performance for 12 different views using Gait Energy Image (GEI) as gait features. Then, we analyze the effect of using different camera configurations for 3D model reconstruction, the GEI from cameras with different settings, the upper and lower body parts for recognition and different GEI resolutions. The results illustrate that low recognition performance is achieved when using gait silhouettes from affine cameras while lower recognition performance is obtained when using gait silhouettes from projective cameras.
In this paper, a two-dimensional (2-D) circular-support wavelet transform (2-D CSWT) is presented. 2-D CSWT is a new geometrical image transform, which can efficiently represent images using 2-D circular spectral split schemes (circularly- decomposed frequency subspaces). 2-D all-pass functions and lattice structure are used to produce 1-level circular symmetric 2-D discrete wavelet transform with approximate linear phase 2-D filters. The classical one-dimensional (1-D) analysis Haar filter bank branches H 0 (z) and H 1 (z) which work as low-pass and high-pass filters, respectively are transformed into their 2-D counterparts H 0 (z 1 ,z 2 ) and H 1 (z 1 ,z 2 ) by applying a circular-support version of the digital spectral transformation (DST). The designed 2-D wavelet filter bank is realized in a separable architecture. The proposed architecture is simulated using Matlab program to measure the deflection ratio (DR) of the high frequency coefficient to evaluate its performance and compare it with the performance of the classical 2-D wavelet architecture. The correlation factor between the input and reconstructed images is also calculated for both architectures. The FPGA (Spartan-3E) Kit is used to implement the resulting architecture in a multiplier-less manner and to calculate the die area and the critical path or maximum frequency of operation. The achieved multiplier-less implementation takes a very small area from FPGA Kit (the die area in 3-level wavelet decomposition takes 300 slices with 7% occupation ratio only at a maximum frequency of 198.447 MHz).
Most of routing protocols used for Mobile Ad hoc Network (MANET), such as Ad hoc on demand distance vector (AODV) routing, uses minimum hops as the only metric for choosing a route. This decision might lead to cause some nodes become congested which will degrade the network performance. This paper proposes an improvement of AODV routing algorithm by making routing decisions depend on fuzzy cost based on the delay in conjunction with number of hops in each path. Our simulation was carried out using OMNET++ 4.0 simulator and the evaluation results show that the proposed Fuzzy Multi-Constraint AODV routing performs better than the original AODV in terms of average end-to-end delay and packet delivery.
The reluctance of industry to allow wireless paths to be incorporated in process control loops has limited the potential applications and benefits of wireless systems. The challenge is to maintain the performance of a control loop, which is degraded by slow data rates and delays in a wireless path. To overcome these challenges, this paper presents an application–level design for a wireless sensor/actuator network (WSAN) based on the “automated architecture”. The resulting WSAN system is used in the developing of a wireless distributed control system (WDCS). The implementation of our wireless system involves the building of a wireless sensor network (WSN) for data acquisition and controller area network (CAN) protocol fieldbus system for plant actuation. The sensor/actuator system is controlled by an intelligent digital control algorithm that involves a controller developed with velocity PID- like Fuzzy Neural Petri Net (FNPN) system. This control system satisfies two important real-time requirements: bumpless transfer and anti-windup, which are needed when manual/auto operating aspect is adopted in the system. The intelligent controller is learned by a learning algorithm based on back-propagation. The concept of petri net is used in the development of FNN to get a correlation between the error at the input of the controller and the number of rules of the fuzzy-neural controller leading to a reduction in the number of active rules. The resultant controller is called robust fuzzy neural petri net (RFNPN) controller which is created as a software model developed with MATLAB. The developed concepts were evaluated through simulations as well validated by real-time experiments that used a plant system with a water bath to satisfy a temperature control. The effect of disturbance is also studied to prove the system's robustness.
This paper provides a two algorithms for designing robust formation control of multiple robots called Leader- Neighbor algorithm and Neighbor-Leader algorithm in unknown environment. The main function of the robot group is to use the RP lidar sensor attached to each robot to form a static geometric polygon. The algorithms consist of two phases implemented to investigate the formation of polygon shape. In the leading- neighbor algorithm, the first stage is the leader alignment and the adjacent alignment is the second stage. The first step uses the information gathered by the main RP Lidar sensor to determine and compute the direction of each adjacent robot. The adjacent RP Lidar sensors are used to align the adjacent robots of the leader by transferring these adjacent robots to the leader. By performing this stage, the neighboring robots will be far from the leader. The second stage uses the information gathered by adjacent RP sensors to reposition the robots so that the distance between them is equal. On the other hand, in the neighbor-leader algorithm, the adjacent robots are rearranged in a regular distribution by moving in a circular path around the leader, with equal angles between each of the two neighbor robots. A new distribution will be generated in this paper by using one leader and four adjacent robots to approve the suggested leader neighbor algorithm and neighbor-leader algorithm .
In coordination of a group of mobile robots in a real environment, the formation is an important task. Multi- mobile robot formations in global knowledge environments are achieved using small robots with small hardware capabilities. To perform formation, localization, orientation, path planning and obstacle and collision avoidance should be accomplished. Finally, several static and dynamic strategies for polygon shape formation are implemented. For these formations minimizing the energy spent by the robots or the time for achieving the task, have been investigated. These strategies have better efficiency in completing the formation, since they use the cluster matching algorithm instead of the triangulation algorithm.
This article emphasizes on a strategy to design a Super Twisting Sliding Mode Control (STSMC) method. The proposed controller depends on the device of Field Programmable Gate Array (FPGA) for controlling the trajectory of robot manipulator. The gains of the suggested controller are optimized using Chaotic Particle Swarm Optimization (PSO) in MATLAB toolbox software and Simulink environment. Since the control systems speed has an influence on their stability requirements and performance, (FPGA) device is taken in consideration. The proposed control method based on FPGA is implemented using Xilinx block sets in the Simulink. Integrated Software Environment (ISE 14.7) and System Generator are employed to create the file of Bitstream which can be downloaded in the device of FPGA. The results show that the designed controller based of on the FPGA by using System Generator is completely verified the effectiveness of controlling the path tracking of the manipulator and high speed. Simulation results explain that the percentage improvement in the Means Square Error (MSEs) of using the STSMC based FPGA and tuned via Chaotic PSO when compared with the same proposed controller tuned with classical PSO are 17.32 % and 13.98 % for two different cases of trajectories respectively.
Energy limitations have become fundamental challenge for designing WSNs. Network lifetime is the most interested and important metric in WSNs. Many works have been developed for prolonging networks lifetime, in which one of the important work is the control of transmission power. This paper proposes a new fuzzy transmission power control technique that operate together with routing protocols for prolonging WSNs lifetime. Dijkstra shortest path routing is considered as the main routing protocol in this work. This paper mainly focuses on transmission power control scheme for prolonging WSNs lifetime. A performance comparison is depicted for maximum and controlled transmission power. Simulation results show an increase in network lifetime equals to 3.4776 for the proposed fuzzy control. The performance of the proposed fuzzy control technique involves a good improvement and contribution in the field of prolonging networks lifetime by using transmission power control.