Development of Low-Cost Compact Omnidirectional Vision Sensors

2001 ◽  
pp. 23-38 ◽  
Author(s):  
H. Ishiguro
Keyword(s):  
Low Cost ◽  
Omnidirectional Vision ◽  
Vision Sensors

scholarly journals Practical Approach for Developing Lateral Motion Control of Autonomous Lane Change System

2020 ◽  
Vol 10 (9) ◽  
pp. 3143 ◽  
Author(s):  
Jaemin Baek ◽  
Changmook Kang ◽  
Wonhee Kim
Keyword(s):  
Vehicle Dynamics ◽  
Low Cost ◽  
Computation Time ◽  
Practical Approach ◽  
Lane Changes ◽  
The Road ◽  
Control Units ◽  
Vision Sensors ◽  
Lateral Offset ◽  
Change System

In this paper, we present a practical approach to address the vehicle lateral control problem. The proposed method can overcome practical problems associated with vehicle lane changes on highways. The vehicle state with respect to the road, which is called lateral offset, jumps in camera vision sensors when the vehicle changes lanes. Thus, in this study, we solve the state jump problem by translating it into a new domain called the cylinder domain. In addition, we proposed the design of a parameter-varying controller to overcome the nonlinear term of vehicle dynamics by considering it as a varying parameter. The proposed method does not consider the lateral offset jump when changing lanes. Furthermore, its significant advantage in terms of computation time makes it suitable for implementation in low-cost electronic control units (ECUs). The proposed algorithm is validated using MATLAB/Simulink with the vehicle dynamics analysis program CarSim.

scholarly journals Using Omnidirectional Vision to Create a Model of the Environment: A Comparative Evaluation of Global-Appearance Descriptors

2016 ◽  
Vol 2016 ◽  
pp. 1-21 ◽  
Author(s):  
L. Payá ◽  
O. Reinoso ◽  
Y. Berenguer ◽  
D. Úbeda
Keyword(s):  
Visual Information ◽  
Comparative Evaluation ◽  
Relevant Information ◽  
Omnidirectional Vision ◽  
Map Building ◽  
Robust Solution ◽  
Robust Model ◽  
Vision Sensors ◽  
Feature Based ◽  
Source Of Information

Nowadays, the design of fully autonomous mobile robots is a key discipline. Building a robust model of the unknown environment is an important ability the robot must develop. Using this model, this robot must be able to estimate its current position and to navigate to the target points. The use of omnidirectional vision sensors is usual to solve these tasks. When using this source of information, the robot must extract relevant information from the scenes both to build the model and to estimate its position. The possible frameworks include the classical approach of extracting and describing local features or working with the global appearance of the scenes, which has emerged as a conceptually simple and robust solution. While feature-based techniques have been extensively studied in the literature, appearance-based ones require a full comparative evaluation to reveal the performance of the existing methods and to tune correctly their parameters. This work carries out a comparative evaluation of four global-appearance techniques in map building tasks, using omnidirectional visual information as the only source of data from the environment.

Real-time human tracking system with multiple omnidirectional vision sensors

2004 ◽  
Vol 35 (2) ◽  
pp. 79-90 ◽  
Author(s):  
Takushi Sogo ◽  
Hiroshi Ishiguro ◽  
Mohan M. Trivedi
Keyword(s):  
Real Time ◽  
Tracking System ◽  
Human Tracking ◽  
Omnidirectional Vision ◽  
Vision Sensors

Active Stereo Vision for Precise Autonomous Vehicle Control

2020 ◽  
Vol 2020 (16) ◽  
pp. 258-1-258-6
Author(s):  
Michael Feller ◽  
Jae-Sang Hyun ◽  
Song Zhang
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Low Cost ◽  
Autonomous Vehicle ◽  
Texture Mapping ◽  
Laser Speckle ◽  
Projection System ◽  
Vision Sensors ◽  
Active Stereo ◽  
Lateral Error

This paper describes the development of a low-cost, lowpower, accurate sensor designed for precise, feedback control of an autonomous vehicle to a hitch. The solution that has been developed uses an active stereo vision system, combining classical stereo vision with a low cost, low power laser speckle projection system, which solves the correspondence problem experienced by classic stereo vision sensors. A third camera is added to the sensor for texture mapping. A model test of the hitching problem was developed using an RC car and a target to represent a hitch. A control system is implemented to precisely control the vehicle to the hitch. The system can successfully control the vehicle from within 35° of perpendicular to the hitch, to a final position with an overall standard deviation of 3.0 m m of lateral error and 1.5° of angular error.

scholarly journals An FPGA-Based Omnidirectional Vision Sensor for Motion Detection on Mobile Robots

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Jones Y. Mori ◽  
Janier Arias-Garcia ◽  
Camilo Sánchez-Ferreira ◽  
Daniel M. Muñoz ◽  
Carlos H. Llanos ◽  
...  
Keyword(s):  
Image Processing ◽  
Mobile Robots ◽  
Background Subtraction ◽  
Vision System ◽  
Low Cost ◽  
Center Of Mass ◽  
Omnidirectional Vision ◽  
Embedded Microprocessor ◽  
Xpc Target ◽  
Convex Mirror

This work presents the development of an integrated hardware/software sensor system for moving object detection and distance calculation, based on background subtraction algorithm. The sensor comprises a catadioptric system composed by a camera and a convex mirror that reflects the environment to the camera from all directions, obtaining a panoramic view. The sensor is used as an omnidirectional vision system, allowing for localization and navigation tasks of mobile robots. Several image processing operations such as filtering, segmentation and morphology have been included in the processing architecture. For achieving distance measurement, an algorithm to determine the center of mass of a detected object was implemented. The overall architecture has been mapped onto a commercial low-cost FPGA device, using a hardware/software co-design approach, which comprises a Nios II embedded microprocessor and specific image processing blocks, which have been implemented in hardware. The background subtraction algorithm was also used to calibrate the system, allowing for accurate results. Synthesis results show that the system can achieve a throughput of 26.6 processed frames per second and the performance analysis pointed out that the overall architecture achieves a speedup factor of 13.78 in comparison with a PC-based solution running on the real-time operating system xPC Target.

scholarly journals A State-of-the-Art Review on Mapping and Localization of Mobile Robots Using Omnidirectional Vision Sensors

2017 ◽  
Vol 2017 ◽  
pp. 1-20 ◽  
Author(s):  
L. Payá ◽  
A. Gil ◽  
O. Reinoso
Keyword(s):  
Computer Vision ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Autonomous Vehicles ◽  
Scientific Community ◽  
Mobile Robotics ◽  
State Of The Art ◽  
Omnidirectional Vision ◽  
Vision Sensors ◽  
Source Of Information

Nowadays, the field of mobile robotics is experiencing a quick evolution, and a variety of autonomous vehicles is available to solve different tasks. The advances in computer vision have led to a substantial increase in the use of cameras as the main sensors in mobile robots. They can be used as the only source of information or in combination with other sensors such as odometry or laser. Among vision systems, omnidirectional sensors stand out due to the richness of the information they provide the robot with, and an increasing number of works about them have been published over the last few years, leading to a wide variety of frameworks. In this review, some of the most important works are analysed. One of the key problems the scientific community is addressing currently is the improvement of the autonomy of mobile robots. To this end, building robust models of the environment and solving the localization and navigation problems are three important abilities that any mobile robot must have. Taking it into account, the review concentrates on these problems; how researchers have addressed them by means of omnidirectional vision; the main frameworks they have proposed; and how they have evolved in recent years.

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