Acquisition And Recognition Og Natural Landmarks For Vision Based Autonomous Robot Navigation
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Author |
: Salvatore Livatino |
Publisher |
: |
Total Pages |
: 289 |
Release |
: 2003 |
ISBN-10 |
: OCLC:475096180 |
ISBN-13 |
: |
Rating |
: 4/5 (80 Downloads) |
Synopsis Acquisition and Recognition Og Natural Landmarks for Vision-based Autonomous Robot Navigation by : Salvatore Livatino
Author |
: Alan Lipton |
Publisher |
: |
Total Pages |
: 570 |
Release |
: 1996 |
ISBN-10 |
: OCLC:225645728 |
ISBN-13 |
: |
Rating |
: 4/5 (28 Downloads) |
Synopsis Vision Based Mobile Robot Navigation in Unknown Environments Using Natural Landmarks by : Alan Lipton
Author |
: Quoc Vong Do |
Publisher |
: |
Total Pages |
: 185 |
Release |
: 2006 |
ISBN-10 |
: OCLC:225110834 |
ISBN-13 |
: |
Rating |
: 4/5 (34 Downloads) |
Synopsis 2D Object-based Visual Landmark Recognition in a Topological Mobile Robot by : Quoc Vong Do
This thesis addresses the issues of visual landmark recognition in autonomous robot navigation along known routes, by intuitively exploiting the functions of the human visual system and its navigational ability. A feedforward-feedbackward architecture has been developed for recognising visual landmarks in real-time. It integrates the theoretical concepts from the pre-attentive and attentive stages in the human visual system, the selective attention adaptive resonance theory neural network and its derivatives, and computational approaches toward object recognition in computer vision.
Author |
: |
Publisher |
: |
Total Pages |
: 11 |
Release |
: 1996 |
ISBN-10 |
: OCLC:227857315 |
ISBN-13 |
: |
Rating |
: 4/5 (15 Downloads) |
Synopsis Vision Based Autonomous Robot Navigation: Motion Segmentation by :
The ability to acquire and respond appropriately to targets or obstacles. moving or stationary, while underway, is critical for all unmanned mobile robot applications. This is achieved by most animate systems, but has proven difficult for artificial systems. We propose that efficient and extensible solutions to the target acquisition, discrimination, and maintenance problem may be found when the machine sensor-effector control algorithms emulate the mechanisms employed by biological systems. In nature. visual motion provides the basis for these functions. Because visual motion can be due either to target motion or to platform motion, a method of motion segmentation must be found. We present a solution to this problem that emulates natural strategies, and describe its implementation in an autonomous visually controlled mobile robot.
Author |
: Joshua J. Potts |
Publisher |
: |
Total Pages |
: 296 |
Release |
: 1999 |
ISBN-10 |
: OCLC:44455794 |
ISBN-13 |
: |
Rating |
: 4/5 (94 Downloads) |
Synopsis Real-time Vision-based Autonomous Robot Navigation by : Joshua J. Potts
Author |
: |
Publisher |
: |
Total Pages |
: 368 |
Release |
: 1807 |
ISBN-10 |
: OCLC:602892852 |
ISBN-13 |
: |
Rating |
: 4/5 (52 Downloads) |
Synopsis Stolpertus, ein junger Geburtshelfer am Kreissbette by :
Author |
: Konstantinos A. Tsintotas |
Publisher |
: Springer Nature |
Total Pages |
: 125 |
Release |
: 2022-09-01 |
ISBN-10 |
: 9783031093968 |
ISBN-13 |
: 3031093968 |
Rating |
: 4/5 (68 Downloads) |
Synopsis Online Appearance-Based Place Recognition and Mapping by : Konstantinos A. Tsintotas
This book introduces several appearance-based place recognition pipelines based on different mapping techniques for addressing loop-closure detection in mobile platforms with limited computational resources. The motivation behind this book has been the prospect that in many contemporary applications efficient methods are needed that can provide high performance under run-time and memory constraints. Thus, three different mapping techniques for addressing the task of place recognition for simultaneous localization and mapping (SLAM) are presented. The book at hand follows a tutorial-based structure describing each of the main parts needed for a loop-closure detection pipeline to facilitate the newcomers. It mainly goes through a historical review of the problem, focusing on how it was addressed during the years reaching the current age. This way, the reader is initially familiarized with each part while the place recognition paradigms follow.
Author |
: Hyun Nam Lee |
Publisher |
: |
Total Pages |
: |
Release |
: 2010 |
ISBN-10 |
: OCLC:609589015 |
ISBN-13 |
: |
Rating |
: 4/5 (15 Downloads) |
Synopsis Vision-based Navigation for Mobile Robots on Ill-structured Roads by : Hyun Nam Lee
Autonomous robots can replace humans to explore hostile areas, such as Mars and other inhospitable regions. A fundamental task for the autonomous robot is navigation. Due to the inherent difficulties in understanding natural objects and changing environments, navigation for unstructured environments, such as natural environments, has largely unsolved problems. However, navigation for ill-structured environments [1], where roads do not disappear completely, increases the understanding of these difficulties. We develop algorithms for robot navigation on ill-structured roads with monocular vision based on two elements: the appearance information and the geometric information. The fundamental problem of the appearance information-based navigation is road presentation. We propose a new type of road description, a vision vector space (V2-Space), which is a set of local collision-free directions in image space. We report how the V2-Space is constructed and how the V2-Space can be used to incorporate vehicle kinematic, dynamic, and time-delay constraints in motion planning. Failures occur due to the limitations of the appearance information-based navigation, such as a lack of geometric information. We expand the research to include consideration of geometric information. We present the vision-based navigation system using the geometric information. To compute depth with monocular vision, we use images obtained from different camera perspectives during robot navigation. For any given image pair, the depth error in regions close to the camera baseline can be excessively large. This degenerated region is named untrusted area, which could lead to collisions. We analyze how the untrusted areas are distributed on the road plane and predict them accordingly before the robot makes its move. We propose an algorithm to assist the robot in avoiding the untrusted area by selecting optimal locations to take frames while navigating. Experiments show that the algorithm can significantly reduce the depth error and hence reduce the risk of collisions. Although this approach is developed for monocular vision, it can be applied to multiple cameras to control the depth error. The concept of an untrusted area can be applied to 3D reconstruction with a two-view approach.
Author |
: Thomas M. Strat |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 186 |
Release |
: 2012-12-06 |
ISBN-10 |
: 9781461229322 |
ISBN-13 |
: 1461229324 |
Rating |
: 4/5 (22 Downloads) |
Synopsis Natural Object Recognition by : Thomas M. Strat
Natural Object Recognition presents a totally new approach to the automation of scene understanding. Rather than attempting to construct highly specialized algorithms for recognizing physical objects, as is customary in modern computer vision research, the application and subsequent evaluation of large numbers of relatively straightforward image processing routines is used to recognize natural features such as trees, bushes, and rocks. The use of contextual information is the key to simplifying the problem to the extent that well understood algorithms give reliable results in ground-level, outdoor scenes.
Author |
: Michael John Milford |
Publisher |
: Springer |
Total Pages |
: 203 |
Release |
: 2007-12-21 |
ISBN-10 |
: 9783540775201 |
ISBN-13 |
: 354077520X |
Rating |
: 4/5 (01 Downloads) |
Synopsis Robot Navigation from Nature by : Michael John Milford
This pioneering book describes the development of a robot mapping and navigation system inspired by models of the neural mechanisms underlying spatial navigation in the rodent hippocampus. Computational models of animal navigation systems have traditionally had limited performance when implemented on robots. This is the first research to test existing models of rodent spatial mapping and navigation on robots in large, challenging, real world environments.