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Author: Lana Jalal
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659478390
Category :
Languages : en
Pages : 116
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Book Description
In this book, Modified Genetic Algorithm (MGA) and Modified Particle Swarm Optimization (MPSO) are developed to increase the capability of these optimization algorithms for a global path planning. Despite the fact that (GA) has rapid search and high search quality, infeasible paths and high computational cost problems are exist associated with this algorithm. To address these problems, the MGA is presented. Improvements presented in MPSO are mainly trying to address the problem of premature convergence associated with the original PSO. In the MPSO an error factor is modelled to ensure that the PSO converges. A modified procedure is carrying out in the MPSO to solve the infeasible path problem. According to the simulation results using Matlab version R2012 (m-file), both algorithms (MGA and MPSO) are tested in different environments and the results are compared with previous researches. The results demonstrate that these two algorithms have a great potential to solve mobile robot path planning with satisfactory results in terms of minimizing distance and execution time.
Author: Lana Jalal
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659478390
Category :
Languages : en
Pages : 116
Get Book Here
Book Description
In this book, Modified Genetic Algorithm (MGA) and Modified Particle Swarm Optimization (MPSO) are developed to increase the capability of these optimization algorithms for a global path planning. Despite the fact that (GA) has rapid search and high search quality, infeasible paths and high computational cost problems are exist associated with this algorithm. To address these problems, the MGA is presented. Improvements presented in MPSO are mainly trying to address the problem of premature convergence associated with the original PSO. In the MPSO an error factor is modelled to ensure that the PSO converges. A modified procedure is carrying out in the MPSO to solve the infeasible path problem. According to the simulation results using Matlab version R2012 (m-file), both algorithms (MGA and MPSO) are tested in different environments and the results are compared with previous researches. The results demonstrate that these two algorithms have a great potential to solve mobile robot path planning with satisfactory results in terms of minimizing distance and execution time.
Author: Luis Payá
Publisher: MDPI
ISBN: 3039286706
Category : Technology & Engineering
Languages : en
Pages : 298
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Book Description
The presence of mobile robots in diverse scenarios is considerably increasing to perform a variety of tasks. Among them, many developments have occurred in the fields of ground, underwater, and flying robotics. Independent of the environment where they move, navigation is a fundamental ability of mobile robots so that they can autonomously complete high-level tasks. This problem can be efficiently addressed through the following actions: First, it is necessary to perceive the environment in which the robot has to move, and extract some relevant information (mapping problem). Second, the robot must be able to estimate its position and orientation within this environment (localization problem). With this information, a trajectory toward the target points must be planned (path planning), and the vehicle must be reactively guided along this trajectory considering either possible changes or interactions with the environment or with the user (control). Given this information, this book introduces current frameworks in these fields (mapping, localization, path planning, and control) and, in general, approaches to any problem related to the navigation of mobile robots, such as odometry, exploration, obstacle avoidance, and simulation.
Author: Jose A. Castellanos
Publisher: Springer Science & Business Media
ISBN: 146154405X
Category : Technology & Engineering
Languages : en
Pages : 212
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Book Description
During the last decade, many researchers have dedicated their efforts to constructing revolutionary machines and to providing them with forms of artificial intelligence to perform some of the most hazardous, risky or monotonous tasks historically assigned to human beings. Among those machines, mobile robots are undoubtedly at the cutting edge of current research directions. A rough classification of mobile robots can be considered: on the one hand, mobile robots oriented to human-made indoor environments; on the other hand, mobile robots oriented to unstructured outdoor environments, which could include flying oriented robots, space-oriented robots and underwater robots. The most common motion mechanism for surface mobile robots is the wheel-based mechanism, adapted both to flat surfaces, found in human-made environments, and to rough terrain, found in outdoor environments. However, some researchers have reported successful developments with leg-based mobile robots capable of climbing up stairs, although they require further investigation. The research work presented here focuses on wheel-based mobile robots that navigate in human-made indoor environments. The main problems described throughout this book are: Representation and integration of uncertain geometric information by means of the Symmetries and Perturbations Model (SPmodel). This model combines the use of probability theory to represent the imprecision in the location of a geometric element, and the theory of symmetries to represent the partiality due to characteristics of each type of geometric element. A solution to the first location problem, that is, the computation of an estimation for the mobile robot location when the vehicle is completely lost in the environment. The problem is formulated as a search in an interpretation tree using efficient matching algorithms and geometric constraints to reduce the size of the solution space. The book proposes a new probabilistic framework adapted to the problem of simultaneous localization and map building for mobile robots: the Symmetries and Perturbations Map (SPmap). This framework has been experimentally validated by a complete experiment which profited from ground-truth to accurately validate the precision and the appropriateness of the approach. The book emphasizes the generality of the solutions proposed to the different problems and their independence with respect to the exteroceptive sensors mounted on the mobile robot. Theoretical results are complemented by real experiments, where the use of multisensor-based approaches is highlighted.
Author: Lei Wang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Hanafiah Yussof
Publisher: IntechOpen
ISBN: 9789537619831
Category : Computers
Languages : en
Pages : 588
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Book Description
Localization and mapping are the essence of successful navigation in mobile platform technology. Localization is a fundamental task in order to achieve high levels of autonomy in robot navigation and robustness in vehicle positioning. Robot localization and mapping is commonly related to cartography, combining science, technique and computation to build a trajectory map that reality can be modelled in ways that communicate spatial information effectively. This book describes comprehensive introduction, theories and applications related to localization, positioning and map building in mobile robot and autonomous vehicle platforms. It is organized in twenty seven chapters. Each chapter is rich with different degrees of details and approaches, supported by unique and actual resources that make it possible for readers to explore and learn the up to date knowledge in robot navigation technology. Understanding the theory and principles described in this book requires a multidisciplinary background of robotics, nonlinear system, sensor network, network engineering, computer science, physics, etc.
Author: Xj Jing
Publisher: IntechOpen
ISBN: 9789537619015
Category : Technology & Engineering
Languages : en
Pages : 608
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Book Description
In this book, new results or developments from different research backgrounds and application fields are put together to provide a wide and useful viewpoint on these headed research problems mentioned above, focused on the motion planning problem of mobile ro-bots. These results cover a large range of the problems that are frequently encountered in the motion planning of mobile robots both in theoretical methods and practical applications including obstacle avoidance methods, navigation and localization techniques, environmental modelling or map building methods, and vision signal processing etc. Different methods such as potential fields, reactive behaviours, neural-fuzzy based methods, motion control methods and so on are studied. Through this book and its references, the reader will definitely be able to get a thorough overview on the current research results for this specific topic in robotics. The book is intended for the readers who are interested and active in the field of robotics and especially for those who want to study and develop their own methods in motion/path planning or control for an intelligent robotic system.
Author: Johann Borenstein
Publisher: A K PETERS
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 244
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Book Description
Sensors for mobile robot positioning. Systems and menthods for mobile robot positioning.
Author: Mehmet Serdar Güzel
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This study addresses the issue of vision based mobile robot navigation in a partially cluttered indoor environment using a mapless navigation strategy. The work focuses on two key problems, namely vision based obstacle avoidance and vision based reactive navigation strategy. The estimation of optical flow plays a key role in vision based obstacle avoidance problems, however the current view is that this technique is too sensitive to noise and distortion under real conditions. Accordingly, practical applications in real time robotics remain scarce. This dissertation presents a novel methodology for vision based obstacle avoidance, using a hybrid architecture. This integrates an appearance-based obstacle detection method into an optical flow architecture based upon a behavioural control strategy that includes a new arbitration module. This enhances the overall performance of conventional optical flow based navigation systems, enabling a robot to successfully move around without experiencing collisions. Behaviour based approaches have become the dominant methodologies for designing control strategies for robot navigation. Two different behaviour based navigation architectures have been proposed for the second problem, using monocular vision as the primary sensor and equipped with a 2-D range finder. Both utilize an accelerated version of the Scale Invariant Feature Transform (SIFT) algorithm. The first architecture employs a qualitative-based control algorithm to steer the robot towards a goal whilst avoiding obstacles, whereas the second employs an intelligent control framework. This allows the components of soft computing to be integrated into the proposed SIFT-based navigation architecture, conserving the same set of behaviours and system structure of the previously defined architecture. The intelligent framework incorporates a novel distance estimation technique using the scale parameters obtained from the SIFT algorithm. The technique employs scale parameters and a corresponding zooming factor as inputs to train a neural network which results in the determination of physical distance. Furthermore a fuzzy controller is designed and integrated into this framework so as to estimate linear velocity, and a neural network based solution is adopted to estimate the steering direction of the robot. As a result, this intelligent iv approach allows the robot to successfully complete its task in a smooth and robust manner without experiencing collision. MS Robotics Studio software was used to simulate the systems, and a modified Pioneer 3-DX mobile robot was used for real-time implementation. Several realistic scenarios were developed and comprehensive experiments conducted to evaluate the performance of the proposed navigation systems. KEY WORDS: Mobile robot navigation using vision, Mapless navigation, Mobile robot architecture, Distance estimation, Vision for obstacle avoidance, Scale Invariant Feature Transforms, Intelligent framework.
Author: Xj Jing
Publisher: IntechOpen
ISBN: 9789537619015
Category : Technology & Engineering
Languages : en
Pages : 608
Get Book Here
Book Description
In this book, new results or developments from different research backgrounds and application fields are put together to provide a wide and useful viewpoint on these headed research problems mentioned above, focused on the motion planning problem of mobile ro-bots. These results cover a large range of the problems that are frequently encountered in the motion planning of mobile robots both in theoretical methods and practical applications including obstacle avoidance methods, navigation and localization techniques, environmental modelling or map building methods, and vision signal processing etc. Different methods such as potential fields, reactive behaviours, neural-fuzzy based methods, motion control methods and so on are studied. Through this book and its references, the reader will definitely be able to get a thorough overview on the current research results for this specific topic in robotics. The book is intended for the readers who are interested and active in the field of robotics and especially for those who want to study and develop their own methods in motion/path planning or control for an intelligent robotic system.
Author: Teddy Yap (Jr.)
Publisher:
ISBN:
Category : Mobile robots
Languages : en
Pages : 144
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Book Description
Mobile robots are becoming ubiquitous and an essential part of our everyday lives. They are increasingly taking their place in service-oriented applications including domestic and entertainment roles. They open up many potential opportunities, but they also come with challenges in terms of their limited sensing capability and accuracy and minimal on-board computing resources. In this dissertation, we address three fundamental problems in mobile robotics and demonstrate our approach to each of the problems with a mobile robot equipped with low-cost and low-end sensors. The problems we consider are those of mobile robot calibration, mobile robot localization, and simultaneous localization and mapping. Motion and sensor models are crucial components in current algorithms for mobile robot localization and mapping. We demonstrate how the parameters of both the motion and sensor models can be automatically estimated during normal robot operations via machine learning methods thereby eliminating the necessity of manually tuning these models through a laborious calibration process. Mobile robot calibration is important especially for robots relying on cheap and less-accurate sensors. Results from real-world robotic experiments with a robot equipped with wheel encoders and sonar sensors are presented that show the effectiveness of the estimation approach.
