Sharif Digital Repository

In recent years the development of Simultaneous Localization and Mapping (SLAM) techniques have enabled social robots to autonomously navigate in routine human workplaces. However, most common SLAM techniques are developed for mapping and localization in static worlds. In this paper, we have developed and analyzed a novel augmentation of the FastSLAM algorithm, including a person tracking module using 2D LiDAR sensor data. Utilizing this module, the SLAM algorithm is capable of filtering measurements coming from walking people who produce noises due to their intrinsic dynamic and unstableness. This augmentation was developed and then tested on our socially assistive mobile robot platform,... 

This paper explores design and implementation of an event-based simulator namely DBMSS for analyzing concurrency protocols in database systems. In the design of DBMSS we interested in event-based approach to create a real world with variety range of event possibilities. DBMSS is explored in the context of the development of a complex simulator for simulating real world conditions and provide an event-based environment to test and evaluate concurrency protocols in database systems. First we discuss the architecture of DBMSS and use it to provide arrival transactions to test and evaluate concurrency protocols in database system. We present the comparison of 4 concurrency protocols in variety... 

A new algorithm named random particle optimization algorithm (RPOA) for local path planning problem of mobile robots in dynamic and unknown environments is proposed. The new algorithm inspired from bacterial foraging technique is based on particles which are randomly distributed around a robot. These particles search the optimal path toward the target position while avoiding the moving obstacles by getting help from the robot's sensors. The criterion of optimal path selection relies on the particles distance to target and Gaussian cost function assign to detected obstacles. Then, a high level decision making strategy will decide to select best mobile robot path among the proceeded particles,... 

In this paper, we propose a new method for mobile robot path planning in dynamic environment when the trajectories of obstacles are unknown. Our algorithm first utilizes a global approach called clearance based probabilistic roadmap method to find a suitable path and then locally apply evolutionary algorithm to keep the structure of the path when obstacles collide with the path. As a result, the path will act like an elastic band. To reach real time applicability, a light fitness function is proposed compare to other genetic algorithms to reduce the computation time needed for calculating and repairing path. Simulation results show that our method not only can keep the original structure of... 

High-bandwidth network analysis is challenging, resource consuming, and inaccurate due to the high volume, velocity, and variety characteristics of the network traffic. The infinite stream of incoming traffic forms a dynamic environment with unexpected changes, which requires analysing approaches to satisfy the high-bandwidth network processing challenges such as incremental learning, inline processing, and outlier handling. This study proposes an inline high-bandwidth network stream clustering algorithm designed to incrementally mine large amounts of continuously transmitting network traffic when some outliers can be dropped before determining the network traffic behaviour. Maintaining... 

Robot navigation is a challenging problem in robotics, which involves determining of robot positioning relative to objects in the environment, and also the mobility of robot through obstacles without colliding into them. The former is known as localization, while the latter is called motion planning. This paper introduces a roadmap method for solving motion planning problem in a dynamic environment based on Generalized Voronoi Diagram (GVD). The efficiency of the proceeding work is verified by examining it in a sample home environment. © 2008 Springer-Verlag  

In this paper, two different important quality metrics, clearance and execution time, for motion planning of mobile robots are studied. Then a new approach, called Clearance-Based Probabilistic Roadmap Method (CBPRM (c)), is proposed which in contrast to VV(c) method, Visibility-Voronoi with clearance c, beside satisfaction of a predefined clearance is very efficient in running time. This provides the CBPRM (c) to be applicable in dynamic environments which require realtime approaches. Experiments showed that the CBPRM(c) is able to generate paths with very low execution time considering determined clearance. © 2008 IEEE  

This paper presents evolutionary methods for optimization in dynamic mobile robot path planning. In dynamic mobile path planning, the goal is to find an optimal feasible path from starting point to target point with various obstacles, as well as smoothness and safety in the proposed path. Pattern search (PS) algorithm, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to find an optimal path for mobile robots to reach to target point with obstacle avoidance. For showing the success of the proposed method, first they are applied to two different paths with a dynamic environment in obstacles. The first results show that the PSO algorithms are converged and minimizethe... 

This paper attempts to give a perspective on decentralized formation control of multiple car-like mobile robots using local information and formation changes in a dynamic environment having several obstacles. In addition, for every mobile robot, it takes physical dimensions, mass, moment of inertia, movement constraints, and saturation of actuators into account. This study makes use of Input/Output Feedback Linearization Method to control each robot. Hence, hierarchical leader-follower based algorithm is employed to control the group formation. To avoid collision between robots and obstacles, and of robots with each other, local artificial potential fields are addressed. The group can change... 

This paper presents a new method for motion planning of mobile robots in dynamic environments based on wave expansion approach which avoids wave re-expansion in sudden obstacles case. Wave re-expansion in big scale environments takes considerable amount of time and process. A new wave expansion algorithm for path finding, either local minima or sudden obstacles are met, has been proposed, as socalled Impeditive Wall Following algorithm, that prevents reexpansion of wave. Furthermore, the simulation results reflects that how the work has improved the already-existing methods. By the use of Impeditive Wall following algorithm it's been tried to prevent the re-expansion of the wave. © 2009 IEEE... 

This paper presents a modified sensor-based online method for mobile robot navigation generating paths in dynamic environments. The core of the navigation algorithm is based on the velocity obstacle avoidance method and the guidance-based tracking algorithm. A fuzzy decision maker is designed to combine the two mentioned algorithms intelligently. Hence the robot will be able to decide intelligently in various situations when facing the moving obstacles and moving target. A noble noise cancellation algorithm using Neural Network is designed to navigate the robot in an uncertain dynamic environment safely. The results show that the robot can track a moving target while maneuvering safely in... 

A new hybrid approach for dynamic optimization problems with continuous search spaces is presented. The proposed approach hybridizes efficient features of the particle swarm optimization in tracking dynamic changes with a new evolutionary procedure. In the proposed dynamic hybrid PSO (DHPSO) algorithm, the swarm size is varied in a self-regulatory manner. Inspired from the microbial life, the particles can reproduce infants and the old ones die. The infants are especially reproduced by high potential particles and located near the local optimum points, using the quadratic interpolation method. The algorithm is adapted to perform in continuous search spaces, utilizing continuous movement of... 

In the present study, an adaptive sliding mode control method was employed to control a fish robotic system using hardware in the loop methodology. Up to now, few researches have focused on autonomous control of fish robot in dynamic environments which may be the result of difficulties in modeling of hydrodynamic effects on fish robot. Therefore, following the introduction of the nonlinear model for the robot, elongated body theory, suggested by Lighthill, was used to analyze fish movements. Then, kinematics control to track desired trajectories was designed for under-actuated model of robot. Adaptive sliding mode controller, capable of adapting according to changes and uncertainties, was... 

Regarding the dynamic nature of cognitive radio networks and the delay of the central decision algorithms due to collecting necessary information in a multi-hop wireless network, distributed resource allocation algorithms are of crucial importance. In this paper we propose a new distributed resource allocation algorithm that properly selects link/frequency in a multi-hop cognitive radio network for delay sensitive applications. This algorithm, uses the locally collected information from neighboring nodes to make suitable routing decisions regarding the dynamic environment and the behavior of the neighbors. We consider the delay as the routing criterion, consisting the queueing delay and the... 

This paper presents a modified sensor-based online method for mobile robot navigation generating paths in dynamic environments. The intelligent part of the algorithm is a Fuzzy Decision Maker (FDM) which enables the robot to do both the guidance-based tracking algorithm and the obstacle avoidance simultaneously. The output of FDM is a weighted combination of velocity vectors generated by velocity obstacle algorithm and guidance based tracking algorithm. The results prove that the robot can track a moving target while maneuvering safely in dynamic environment and avoids stationary and moving obstacles  

This paper presents a new approach based on Artificial Potential Fields (APF) which provides real-time and very effective methodology for practical motion planners in unknown dynamic environments. The Maxwell's equations are exploited to define Artificial Magnetoquasistatic Fields (AMF) as an extension of APF, which provides a predictive, intelligent, and natural behavior in contrast with other approaches. The essential aim of the AMF is dealing with moving obstacles, as well as static ones. The main idea is to consider an electrical current in the direction of each moving obstacle which induces magnetic field around it. These moving obstacles could be arbitrary in shape, size, and number....