Position Estimation of a Mobile Robot Using Monocular Vision PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Position Estimation of a Mobile Robot Using Monocular Vision PDF full book. Access full book title Position Estimation of a Mobile Robot Using Monocular Vision by Saraswat Ushakumari. Download full books in PDF and EPUB format.
Author: Saraswat Ushakumari
Publisher:
ISBN:
Category : Coal mines and mining
Languages : en
Pages : 126
Get Book Here
Book Description
Author: Saraswat Ushakumari
Publisher:
ISBN:
Category : Coal mines and mining
Languages : en
Pages : 126
Get Book Here
Book Description
Author: Jose A. Castellanos
Publisher: Springer Science & Business Media
ISBN: 146154405X
Category : Technology & Engineering
Languages : en
Pages : 212
Get Book Here
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: Michael Tribou
Publisher:
ISBN:
Category :
Languages : en
Pages : 188
Get Book Here
Book Description
A combined relative pose and target object model estimation framework using a monocular camera as the primary feedback sensor has been designed and validated in a simulated robotic environment. The monocular camera is mounted on the end-effector of a robot manipulator and measures the image plane coordinates of a set of point features on a target workpiece object. Using this information, the relative position and orientation, as well as the geometry, of the target object are recovered recursively by a Kalman filter process. The Kalman filter facilitates the fusion of supplemental measurements from range sensors, with those gathered with the camera. This process allows the estimated system state to be accurate and recover the proper environment scale. Current approaches in the research areas of visual servoing control and mobile robotics are studied in the case where the target object feature point geometry is well-known prior to the beginning of the estimation. In this case, only the relative pose of target object frames is estimated over a sequence of frames from a single monocular camera. An observability analysis was carried out to identify the physical configurations of camera and target object for which the relative pose cannot be recovered by measuring only the camera image plane coordinates of the object point features. A popular extension to this is to concurrently estimate the target object model concurrently with the relative pose of the camera frame, a process known as Simultaneous Localization and Mapping (SLAM). The recursive framework was augmented to facilitate this larger estimation problem. The scale of the recovered solution is ambiguous using measurements from a single camera. A second observability analysis highlights more configurations for which the relative pose and target object model are unrecoverable from camera measurements alone. Instead, measurements which contain the global scale are required to obtain an accurate solution. A set of additional sensors are detailed, including range finders and additional cameras. Measurement models for each are given, which facilitate the fusion of this supplemental data with the original monocular camera image measurements. A complete framework is then derived to combine a set of such sensor measurements to recover an accurate relative pose and target object model estimate.
Author: Héctor . M Becerra
Publisher: Springer
ISBN: 3319057839
Category : Technology & Engineering
Languages : en
Pages : 127
Get Book Here
Book Description
Vision-based control of wheeled mobile robots is an interesting field of research from a scientific and even social point of view due to its potential applicability. This book presents a formal treatment of some aspects of control theory applied to the problem of vision-based pose regulation of wheeled mobile robots. In this problem, the robot has to reach a desired position and orientation, which are specified by a target image. It is faced in such a way that vision and control are unified to achieve stability of the closed loop, a large region of convergence, without local minima and good robustness against parametric uncertainty. Three different control schemes that rely on monocular vision as unique sensor are presented and evaluated experimentally. A common benefit of these approaches is that they are valid for imaging systems obeying approximately a central projection model, e.g., conventional cameras, catadioptric systems and some fisheye cameras. Thus, the presented control schemes are generic approaches. A minimum set of visual measurements, integrated in adequate task functions, are taken from a geometric constraint imposed between corresponding image features. Particularly, the epipolar geometry and the trifocal tensor are exploited since they can be used for generic scenes. A detailed experimental evaluation is presented for each control scheme.
Author: L. Feng
Publisher:
ISBN:
Category :
Languages : en
Pages : 212
Get Book Here
Book Description
Author: Alejandra Barrera
Publisher: BoD – Books on Demand
ISBN: 9533070765
Category : Technology & Engineering
Languages : en
Pages : 684
Get Book Here
Book Description
Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described.
Author: Marc Krumbein
Publisher:
ISBN:
Category : Mobile robots
Languages : en
Pages : 78
Get Book Here
Book Description
The act of localizing a mobile robot typically can be divided into the measurement of robot position and estimation of robot heading. At present, most existing systems use multiple sensor systems in tandem paired with a mathematical model of robot behavior to achieve one or both of these. This thesis explores an alternative approach to heading estimation utilizing the relative position of multiple position sensors on a mobile robot to infer robot heading. This thesis then goes on to examine the precision of this system, the accuracy in sensor position estimation with respect to sensor orientation, and demonstration of the use of this system applied to the task of plowing snow. This proposed system was demonstrated to provide local X and Y coordinate estimates with a standard deviation under 1 cm and a robot heading estimate with a standard deviation of 0.6 degrees in a static position and orientation. Sensor directionality was explored through the measurement of sensor positions at known orientations at the center of the robot testing area. The collected data was used to create a simple correction function that could be used to adjust for position offsets given sensor orientation. Before correction, it was observed that on rotation of an individual sensor, the estimated sensor position may drift by up to 8 cm in the X or Y direction. After applying the correction function to the gathered data it was observed that the X and Y coordinates were within ± 2 cm of the target location regardless of orientation. The proposed system was then applied to a mobile snowplow robot and used to demonstrate that despite its simple nature, it was adequate to navigate between a set of predefined points. Using estimated heading as proportional feedback in a primitive navigation scheme, the robot was able to navigate between points several meters apart while staying within 20 cm of straight line paths between them.
Author: Liang Yan
Publisher: Springer Nature
ISBN: 981158155X
Category : Technology & Engineering
Languages : en
Pages : 5416
Get Book Here
Book Description
This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircraft. It covers a range of topics, including, but not limited to, intelligent computing communication and control; new methods of navigation, estimation, and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation, and control of miniature aircraft; and sensor systems for guidance, navigation, and control. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.
Author: Emanuele Frontoni
Publisher: Lulu.com
ISBN: 147106977X
Category : Technology & Engineering
Languages : en
Pages : 157
Get Book Here
Book Description
The use of vision in mobile robotics in one of the main goal of this thesis. In particular novel appearance based approaches for image matching metric are introduced. These approaches are applied to the problem of mobile robot localization.Similarity measures between robot's views are used in probabilistic methods for robot pose estimation. In this field of probabilistic localization active approach are proposed allowing the robot to faster and better localize. All methods have been extensively tested using a real robot in an indoor environment.Note: the book is the publication of the PhD thesis discussed in Università Politecnica delle Marche, Ancona, Italy in 2006 by Emanuele Frontoni
Author: Pierre Lamon
Publisher: Springer Science & Business Media
ISBN: 3540782869
Category : Technology & Engineering
Languages : en
Pages : 112
Get Book Here
Book Description
Rough terrain robotics is a fast evolving field of research and a lot of effort is deployed towards enabling a greater level of autonomy for outdoor vehicles. This book demonstrates how the accuracy of 3D position tracking can be improved by considering rover locomotion in rough terrain as a holistic problem. Although the selection of appropriate sensors is crucial to accurately track the rover’s position, it is not the only aspect to consider. Indeed, the use of an unadapted locomotion concept severely affects the signal to noise ratio of the sensors, which leads to poor motion estimates. In this work, a mechanical structure allowing smooth motion across obstacles with limited wheel slip is used. In particular, it enables the use of odometry and inertial sensors to improve the position estimation in rough terrain. A method for computing 3D motion increments based on the wheel encoders and chassis state sensors is developed. Because it accounts for the kinematics of the rover, this method provides better results than the standard approach. To further improve the accuracy of the position tracking and the rover’s climbing performance, a controller minimizing wheel slip is developed. The algorithm runs online and can be adapted to any kind of passive wheeled rover. Finally, sensor fusion using 3D-Odometry, inertial sensors and visual motion estimation based on stereovision is presented. The experimental results demonstrate how each sensor contributes to increase the accuracy and robustness of the 3D position estimation.
