3D Vision-Based Autonomous Navigation System Using ANN and Kinect Sensor

Sales, Daniel Oliva; Correa, D.O.; Osório, Fernando Santos; Wolf, Denis F.

doi:10.1007/978-3-642-32909-8_31

Cited by 17 publications

(7 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Image understanding and matching have been long-standing, important research areas in devising safe navigation systems for both robots and humans [ 13 ]. Vision-based navigation systems commonly use feature-based matching in video frames.…”

Section: Methodsmentioning

confidence: 99%

A Navigation System for the Visually Impaired: A Fusion of Vision and Depth Sensor

Kanwal

Bostancı

Currie

et al. 2015

Applied Bionics and Biomechanics

View full text Add to dashboard Cite

For a number of years, scientists have been trying to develop aids that can make visually impaired people more independent and aware of their surroundings. Computer-based automatic navigation tools are one example of this, motivated by the increasing miniaturization of electronics and the improvement in processing power and sensing capabilities. This paper presents a complete navigation system based on low cost and physically unobtrusive sensors such as a camera and an infrared sensor. The system is based around corners and depth values from Kinect's infrared sensor. Obstacles are found in images from a camera using corner detection, while input from the depth sensor provides the corresponding distance. The combination is both efficient and robust. The system not only identifies hurdles but also suggests a safe path (if available) to the left or right side and tells the user to stop, move left, or move right. The system has been tested in real time by both blindfolded and blind people at different indoor and outdoor locations, demonstrating that it operates adequately.

show abstract

Section: Methodsmentioning

confidence: 99%

A Navigation System for the Visually Impaired: A Fusion of Vision and Depth Sensor

Kanwal

Bostancı

Currie

et al. 2015

Applied Bionics and Biomechanics

View full text Add to dashboard Cite

show abstract

“…56 Autonomous navigation. 57,58 Human–computer interaction. 59 Simultaneous localization and mapping (SLAM).…”

Section: Overview Of Contributionsmentioning

confidence: 99%

Advances in sensing and processing methods for three-dimensional robot vision

Chen

2018

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

In this article, we survey the recent developments of sensing methods in three-dimensional robot vision, centering on the current three-dimensional sensors and core techniques embedded in robotic systems. Over 8000 publications have reported rather wide application areas of three-dimensional robot vision in the last 40 years, such as human-robot interaction, object recognition, three-dimensional modeling, object tracking, searching and surveillance, as well as robot manipulation, localization, navigation, mapping, and path planning. Representative works and future research trends are also addressed in this article.

show abstract

“…The second category of methods for obstacle detection is been proposed in [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. These methods detect obstacles using depth information.…”

Section: Introductionmentioning

confidence: 99%

An Indoor Obstacle Detection System Using Depth Information and Region Growth

Huang

Hsieh

Yeh

2015

Sensors

View full text Add to dashboard Cite

This study proposes an obstacle detection method that uses depth information to allow the visually impaired to avoid obstacles when they move in an unfamiliar environment. The system is composed of three parts: scene detection, obstacle detection and a vocal announcement. This study proposes a new method to remove the ground plane that overcomes the over-segmentation problem. This system addresses the over-segmentation problem by removing the edge and the initial seed position problem for the region growth method using the Connected Component Method (CCM). This system can detect static and dynamic obstacles. The system is simple, robust and efficient. The experimental results show that the proposed system is both robust and convenient.

show abstract

3D Vision-Based Autonomous Navigation System Using ANN and Kinect Sensor

Cited by 17 publications

References 19 publications

A Navigation System for the Visually Impaired: A Fusion of Vision and Depth Sensor

A Navigation System for the Visually Impaired: A Fusion of Vision and Depth Sensor

Advances in sensing and processing methods for three-dimensional robot vision

An Indoor Obstacle Detection System Using Depth Information and Region Growth

Contact Info

Product

Resources

About