scholarly journals Global Appearance Applied to Visual Map Building and Path Estimation Using Multiscale Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-23 ◽  
Author(s):  
Francisco Amorós ◽  
Luis Payá ◽  
Oscar Reinoso ◽  
Walterio Mayol-Cuevas ◽  
Andrew Calway
Keyword(s):  
Pose Estimation ◽  
Visual Information ◽  
Multiscale Analysis ◽  
Spatial Arrangement ◽  
Field Of View ◽  
Indoor Environments ◽  
Map Building ◽  
Topological Map ◽  
Complete Field ◽  
Estimation System

In this work we present a topological map building and localization system for mobile robots based on global appearance of visual information. We include a comparison and analysis of global-appearance techniques applied to wide-angle scenes in retrieval tasks. Next, we define multiscale analysis, which permits improving the association between images and extracting topological distances. Then, a topological map-building algorithm is proposed. At first, the algorithm has information only of some isolated positions of the navigation area in the form of nodes. Each node is composed of a collection of images that covers the complete field of view from a certain position. The algorithm solves the node retrieval and estimates their spatial arrangement. With these aims, it uses the visual information captured along some routes that cover the navigation area. As a result, the algorithm builds a graph that reflects the distribution and adjacency relations between nodes (map). After the map building, we also propose a route path estimation system. This algorithm takes advantage of the multiscale analysis. The accuracy in the pose estimation is not reduced to the nodes locations but also to intermediate positions between them. The algorithms have been tested using two different databases captured in real indoor environments under dynamic conditions.

scholarly journals Topological Frontier-Based Exploration and Map-Building Using Semantic Information

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4595 ◽  
Author(s):  
Clara Gomez ◽  
Alejandra C. Hernandez ◽  
Ramon Barber
Keyword(s):  
Open Space ◽  
Semantic Information ◽  
State Of The Art ◽  
Fundamental Problem ◽  
Cost Utility ◽  
Indoor Environments ◽  
Map Building ◽  
Topological Map ◽  
Unknown Area ◽  
Closure Algorithm

Exploration of unknown environments is a fundamental problem in autonomous robotics that deals with the complexity of autonomously traversing an unknown area while acquiring the most important information of the environment. In this work, a mobile robot exploration algorithm for indoor environments is proposed. It combines frontier-based concepts with behavior-based strategies in order to build a topological representation of the environment. Frontier-based approaches assume that, to gain the most information of an environment, the robot has to move to the regions on the boundary between open space and unexplored space. The novelty of this work is in the semantic frontier classification and frontier selection according to a cost–utility function. In addition, a probabilistic loop closure algorithm is proposed to solve cyclic situations. The system outputs a topological map of the free areas of the environment for further navigation. Finally, simulated and real-world experiments have been carried out, their results and the comparison to other state-of-the-art algorithms show the feasibility of the exploration algorithm proposed and the improvement that it offers with regards to execution time and travelled distance.

scholarly journals Augmenting ViSP’s 3D Model-Based Tracker with RGB-D SLAM for 3D Pose Estimation in Indoor Environments

2016 ◽  
Vol XLI-B1 ◽  
pp. 925-932
Author(s):  
J. Li-Chee-Ming ◽  
C. Armenakis
Keyword(s):  
Pose Estimation ◽  
Visual Servoing ◽  
3D Model ◽  
Field Of View ◽  
Indoor Environments ◽  
Camera Motion ◽  
3D Pose Estimation ◽  
Building Models ◽  
Outdoor Environments ◽  
Model Features

This paper presents a novel application of the Visual Servoing Platform’s (ViSP) for pose estimation in indoor and GPS-denied outdoor environments. Our proposed solution integrates the trajectory solution from RGBD-SLAM into ViSP’s pose estimation process. Li-Chee-Ming and Armenakis (2015) explored the application of ViSP in mapping large outdoor environments, and tracking larger objects (i.e., building models). Their experiments revealed that tracking was often lost due to a lack of model features in the camera’s field of view, and also because of rapid camera motion. Further, the pose estimate was often biased due to incorrect feature matches. This work proposes a solution to improve ViSP’s pose estimation performance, aiming specifically to reduce the frequency of tracking losses and reduce the biases present in the pose estimate. This paper explores the integration of ViSP with RGB-D SLAM. We discuss the performance of the combined tracker in mapping indoor environments and tracking 3D wireframe indoor building models, and present preliminary results from our experiments.

scholarly journals An RGB-D-Based Cross-Field of View Pose Estimation System for a Free Flight Target in a Wind Tunnel

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Sheng Liu ◽  
Yuan Feng ◽  
Kang Shen ◽  
Yangqing Wang ◽  
Shengyong Chen
Keyword(s):  
Wind Tunnel ◽  
Real Time ◽  
Pose Estimation ◽  
Dynamic Testing ◽  
Estimation Method ◽  
Spatial Relationship ◽  
Field Of View ◽  
Free Flight ◽  
The Real ◽  
Estimation System

Estimating the real-time pose of a free flight aircraft in a complex wind tunnel environment is extremely difficult. Due to the high dynamic testing environment, complicated illumination condition, and the unpredictable motion of target, most general pose estimating methods will fail. In this paper, we introduce a cross-field of view (FOV) real-time pose estimation system, which provides high precision pose estimation of the free flight aircraft in the wind tunnel environment. Multiview live RGB-D streams are used in the system as input to ensure the measurement area can be fully covered. First, a multimodal initialization method is developed to measure the spatial relationship between the RGB-D camera and the aircraft. Based on all the input multimodal information, a so-called cross-FOV model is proposed to recognize the dominating sensor and accurately extract the foreground region in an automatic manner. Second, we develop an RGB-D-based pose estimation method for a single target, by which the 3D sparse points and the pose of the target can be simultaneously obtained in real time. Many experiments have been conducted, and an RGB-D image simulation based on 3D modeling is implemented to verify the effectiveness of our algorithm. Both the real scene’s and simulation scene’s experimental results demonstrate the effectiveness of our method.

scholarly journals An improved bioinspired cognitive map-building system based on episodic memory recognition

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142093094
Author(s):  
Yu Naigong ◽  
Wang Lin ◽  
Jiang Xiaojun ◽  
Yuan Yunhe
Keyword(s):  
Episodic Memory ◽  
Visual Information ◽  
Cognitive Model ◽  
Cognitive Map ◽  
Feature Descriptor ◽  
Map Building ◽  
Cell Competition ◽  
Topological Map ◽  
The Brain ◽  
Memory Recognition

Before the cognitive map is generated through the fire of the rodent hippocampal spatial cells, mammals can obtain the outside knowledge through the visual information, which comes from the eyeball to the brain. The information is encoded and transferred to the two regions of the brain based on the fact of biophysiological research, which are known as “what” loop and “where” loop. In this article, we simulate an episodic memory recognition unit consisting of the integration of two-loop information, which is applied to building the accurate bioinspired spatial cognitive map of real environments. We employ the visual bag of word algorithm based on oriented Feature from Accelerated Segment Test and rotated Binary Robust Independent Elementary Features feature to build the “what” loop and the hippocampal spatial cells cognitive model, which comes from the front-end visual information input system to build the “where” loop. At the same time, the environmental cognitive map is a topological map containing information about place cell competition firing rate, oriented Feature from Accelerated Segment Test and rotated Binary Robust Independent Elementary Features feature descriptor, similarity of image retrieval, and relative location of cognitive map nodes. The simulation experiments and physical experiments in a mobile robot platform have been done to verify the environmental adaptability and robustness of the algorithm. This proposing algorithm would provide a foundation for further research on bioinspired navigation of robots.

Recognition of Indoor Environment by Robot Partner Using Conversation

2013 ◽  
Vol 17 (5) ◽  
pp. 753-760 ◽  
Author(s):  
Jinseok Woo ◽  
◽  
Naoyuki Kubota
Keyword(s):  
Indoor Environment ◽  
Daily Life ◽  
Indoor Environments ◽  
Map Building ◽  
Human Beings ◽  
Topological Map ◽  
Symbolic Information ◽  
Localization And Mapping ◽  
Environment Recognition ◽  
Environment Perception

To support daily life before performing an action, a robot partner must perceive an unknown environment. Much research has been done from various viewpoints on self-localization estimation and environment perception. In our research, the robot partner performs self-localization and environment recognition using Simultaneous Localization and Mapping for self-localization estimation and map building. In this paper, we propose a method for recognizing indoor environments by robot partners based on conversations with human beings. Information acquired from maps is identified in order to share the meaning with human beings after the required interpretation. In this paper, we therefore propose a method for recognizing environmental maps by labeling these maps based on symbolic information developed through conversation with human beings. The proposed method is composed of four parts. First, the robot partner applies a steady-state genetic algorithm for self-localization estimation. Second, we use a map building algorithm for expressing the topological map. Third, conversation with human beings is performed for acquiring symbolic information in order to recognize object and position locations through the map. Fourth, we perform experiments and discuss the effectiveness of the proposed technique.

scholarly journals Augmenting ViSP’s 3D Model-Based Tracker with RGB-D SLAM for 3D Pose Estimation in Indoor Environments

2016 ◽  
Vol XLI-B1 ◽  
pp. 925-932 ◽  
Author(s):  
J. Li-Chee-Ming ◽  
C. Armenakis
Keyword(s):  
Pose Estimation ◽  
Visual Servoing ◽  
3D Model ◽  
Field Of View ◽  
Indoor Environments ◽  
Camera Motion ◽  
3D Pose Estimation ◽  
Building Models ◽  
Outdoor Environments ◽  
Model Features

This paper presents a novel application of the Visual Servoing Platform’s (ViSP) for pose estimation in indoor and GPS-denied outdoor environments. Our proposed solution integrates the trajectory solution from RGBD-SLAM into ViSP’s pose estimation process. Li-Chee-Ming and Armenakis (2015) explored the application of ViSP in mapping large outdoor environments, and tracking larger objects (i.e., building models). Their experiments revealed that tracking was often lost due to a lack of model features in the camera’s field of view, and also because of rapid camera motion. Further, the pose estimate was often biased due to incorrect feature matches. This work proposes a solution to improve ViSP’s pose estimation performance, aiming specifically to reduce the frequency of tracking losses and reduce the biases present in the pose estimate. This paper explores the integration of ViSP with RGB-D SLAM. We discuss the performance of the combined tracker in mapping indoor environments and tracking 3D wireframe indoor building models, and present preliminary results from our experiments.

scholarly journals Audiovisual Bimodal and Interactive Effects for Soundscape Design of the Indoor Environments: A Systematic Review

2021 ◽  
Vol 13 (1) ◽  
pp. 339
Author(s):  
Yoshimi Hasegawa ◽  
Siu-Kit Lau
Keyword(s):  
Systematic Review ◽  
Visual Information ◽  
Web Of Science ◽  
Interactive Effects ◽  
Indoor Environments ◽  
Sound Sources ◽  
Noise Annoyance ◽  
Visual Variable ◽  
Soundscape Studies ◽  
Potential Use

A growing number of soundscape studies involving audiovisual factors have been conducted; however, their bimodal and interactive effects on indoor soundscape evaluations have not yet been thoroughly reviewed. The overarching goal of this systematic review was to develop the framework for designing sustainable indoor soundscapes by focusing on audiovisual factors and relations. A search for individual studies was conducted through three databases and search engines: Scopus, Web of Science, and PubMed. Based on the qualitative reviews of the selected thirty papers, a framework of indoor soundscape evaluation concerning visual and audiovisual indicators was proposed. Overall, the greenery factor was the most important visual variable, followed by the water features and moderating noise annoyance perceived by occupants in given indoor environments. The presence of visual information and sound-source visibility would moderate perceived noise annoyance and influence other audio-related perceptions. Furthermore, sound sources would impact multiple perceptual responses (audio, visual, cognitive, and emotional perceptions) related to the overall soundscape experiences when certain visual factors are interactively involved. The proposed framework highlights the potential use of the bimodality and interactivity of the audiovisual factors for designing indoor sound environments in more effective ways.

scholarly journals A novel edge gradient algorithm for multiple mobile robots cooperative mapping in unknown environment

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986038
Author(s):  
Huang Yiqing ◽  
Wang Hui ◽  
Wei Lisheng ◽  
Gao Wengen ◽  
Ge Yuan
Keyword(s):  
Visual Field ◽  
Mobile Robots ◽  
Information Exchange ◽  
Field Of View ◽  
Gradient Algorithm ◽  
Movement Direction ◽  
Mapping Technique ◽  
Map Building ◽  
Multiple Mobile Robots ◽  
Motion Behavior

This article presented a cooperative mapping technique using a novel edge gradient algorithm for multiple mobile robots. The proposed edge gradient algorithm can be divided into four behaviors such as adjusting the movement direction, evaluating the safety of motion behavior, following behavior, and obstacle information exchange, which can effectively prevent multiple mobile robots falling into concave obstacle areas. Meanwhile, a visual field factor is constructed based on biological principles so that the mobile robots can have a larger field of view when moving away from obstacles. Also, the visual field factor will be narrowed due to the obstruction of the obstacle when approaching an obstacle and the obtained map-building data are more accurate. Finally, three sets of simulation and experimental results demonstrate the performance superiority of the presented algorithm.

scholarly journals CONCURRENT MAP BUILDING AND LOCALIZATION ON INDOOR DYNAMIC ENVIRONMENTS

2002 ◽  
Vol 16 (03) ◽  
pp. 361-374 ◽  
Author(s):  
JUAN ANDRADE-CETTO ◽  
ALBERTO SANFELIU
Keyword(s):  
Learning Rule ◽  
Dynamic Environments ◽  
Position Estimation ◽  
Indoor Environments ◽  
Map Building ◽  
Robust Learning ◽  
Map Construction ◽  
Map Updating ◽  
Dynamic Map ◽  
Robot Position

A system that builds and maintains a dynamic map for a mobile robot is presented. A learning rule associated to each observed landmark is used to compute its robustness. The position of the robot during map construction is estimated by combining sensor readings, motion commands, and the current map state by means of an Extended Kalman Filter. The combination of landmark strength validation and Kalman filtering for map updating and robot position estimation allows for robust learning of moderately dynamic indoor environments.

Vehicle Pose Estimation System Base on Pressure Sensor Array for Clamping Parking Robot

2021 ◽  
Author(s):  
Juzhong Zhang ◽  
Yuyi Chu ◽  
Zhisen Wang ◽  
Tingfeng Ye ◽  
Liming Cai ◽  
...  
Keyword(s):  
Pose Estimation ◽  
Pressure Sensor ◽  
Sensor Array ◽  
Estimation System
Sign in / Sign up

Export Citation Format

Share Document