Low cost obstacle detection system for wheeled mobile robot

2012 ◽  
Author(s):  
Ibrahim Alsonosi Nasir
Keyword(s):  
Mobile Robot ◽  
Detection System ◽  
Low Cost ◽  
Obstacle Detection ◽  
Wheeled Mobile Robot

A Human-Inspired Method for Point-to-Point and Path-Following Navigation of Mobile Robots

2015 ◽  
Vol 7 (4) ◽  
Author(s):  
F. Heidari ◽  
R. Fotouhi
Keyword(s):  
Mobile Robot ◽  
Real Time ◽  
Path Following ◽  
Obstacle Detection ◽  
Wheeled Mobile Robot ◽  
Sensor Data ◽  
Integrated Navigation ◽  
Fully Integrated ◽  
Point Motion ◽  
Point To Point

This paper describes a human-inspired method (HIM) and a fully integrated navigation strategy for a wheeled mobile robot in an outdoor farm setting. The proposed strategy is composed of four main actions: sensor data analysis, obstacle detection, obstacle avoidance, and goal seeking. Using these actions, the navigation approach is capable of autonomous row-detection, row-following, and path planning motion in outdoor settings. In order to drive the robot in off-road terrain, it must detect holes or ground depressions (negative obstacles) that are inherent parts of these environments, in real-time at a safe distance from the robot. Key originalities of the proposed approach are its capability to accurately detect both positive (over ground) and negative obstacles, and accurately identify the end of the rows of bushes (e.g., in a farm) and enter the next row. Experimental evaluations were carried out using a differential wheeled mobile robot in different settings. The robot, used for experiments, utilizes a tilting unit, which carries a laser range finder (LRF) to detect objects, and a real-time kinematics differential global positioning system (RTK-DGPS) unit for localization. Experiments demonstrate that the proposed technique is capable of successfully detecting and following rows (path following) as well as robust navigation of the robot for point-to-point motion control.

PARAMETER ANALYSIS OF A REMOTELY CONTROLLED HOME MONITORING SYSTEM USING MOBILE ROBOT VIA CAMERA

2017 ◽  
Vol 79 (2) ◽  
Author(s):  
Mariam Md Ghazaly ◽  
Ho Carl Choon ◽  
Mohd Amran Md Ali ◽  
Zulkeflee Abdullah ◽  
Soo Kok Yew ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Monitoring System ◽  
Robot Control ◽  
Pulse Width Modulation ◽  
Detection System ◽  
Home Monitoring ◽  
Obstacle Detection ◽  
Parameter Analysis ◽  
Experimental Result ◽  
Long Distance

In this paper, the performance and prototype of a remotely-controlled home monitoring mobile robot for security and surveillance purposes were discussed. Home monitoring system has been one of the basic infrastructures that is being used in most of the residential compound. However, traditional CCTV system, which requires supporting surfaces and high equipment cost, has forced human to search for an alternative. Thus, this project provided a more flexibility and mobility to the home monitoring system, which consisted of an obstacle detection system and a camera. After discussing the conception of the project, as part of the experiment aspect method, experiment setup and result were presented. In this paper, the objectives also looked into the sensitivity of the obstacle avoidance system, to design and develop a remotely-controlled home monitoring robot, to design and develop a networking system for long distance robot control and to analyze the performance of the motor in terms of pulse width modulation (PWM). In conclusion, the experimental result proved that the proposed project was successfully developed with detailed supporting data.

scholarly journals High-Precision Low-Cost Gimballing Platform for Long-Range Railway Obstacle Detection

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 474
Author(s):  
Elio Hajj Assaf ◽  
Cornelius von von Einem ◽  
Cesar Cadena ◽  
Roland Siegwart ◽  
Florian Tschopp
Keyword(s):  
Long Range ◽  
High Precision ◽  
High Speed ◽  
Detection System ◽  
Low Cost ◽  
Obstacle Detection ◽  
Numerical Control ◽  
Railway Network ◽  
Lever System ◽  
Novel Approach

Increasing demand for rail transportation results transportation by rail, resulting in denser and more high-speed usage of the existing railway network, making makes new and more advanced vehicle safety systems necessary. Furthermore, high traveling speeds and the greatlarge weights of trains lead to long braking distances—all of which necessitates Long braking distances, due to high travelling speeds and the massive weight of trains, necessitate a Long-Range Obstacle Detection (LROD) system, capable of detecting humans and other objects more than 1000 m in advance. According to current research, only a few sensor modalities are capable of reaching this far and recording sufficiently accurate enoughdata to distinguish individual objects. The limitation of these sensors, such as a 1D-Light Detection and Ranging (LiDAR), is however a very narrow Field of View (FoV), making it necessary to use ahigh-precision means of orienting to target them at possible areas of interest. To close this research gap, this paper presents a novel approach to detecting railway obstacles by developinga high-precision pointing mechanism, for the use in a future novel railway obstacle detection system In this work such a high-precision pointing mechanism is developed, capable of targeting aiming a 1D-LiDAR at humans or objects at the required distance. This approach addresses To address the challenges of a low target pricelimited budget, restricted access to high-precision machinery and equipment as well as unique requirements of our target application., a novel pointing mechanism has been designed and developed. By combining established elements from 3D printers and Computer Numerical Control (CNC) machines with a double-hinged lever system, simple and cheaplow-cost components are capable of precisely orienting an arbitrary sensor platform. The system’s actual pointing accuracy has been evaluated using a controlled, in-door, long-range experiment. The device was able to demonstrate a precision of 6.179 mdeg, which is at the limit of the measurable precision of the designed experiment.

Design for AGV Based on Binocular Stereo Vision

2011 ◽  
Vol 271-273 ◽  
pp. 137-143
Author(s):  
Lin Feng Xu ◽  
Zhi Xiang Tian
Keyword(s):  
Mobile Robot ◽  
Stereo Vision ◽  
Sliding Mode ◽  
Variable Structure ◽  
Obstacle Detection ◽  
Wheeled Mobile Robot ◽  
Control Law ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Sliding Mode Variable Structure

Based on the sliding mode variable structure control theory, the sliding mode control algorithm is proposed for a nonholonomic mobile robot system. The Lyapunov function and exponential approximation law are used for designing the control law of the mobile robot. And the binocular stereo vision method is proposed for the four wheeled AGV to implement the obstacle detection and the depth calculation. Finally, the control law is designed and simulated by the proposed algorithm for the wheeled mobile robot, and the simulation results show that the proposed algorithm is efficient, and also can reduce the chattering of the system, and in the experiment the four wheeled mobile robot can also successfully detect obstacles.

scholarly journals A New Roadway Eventual Obstacle Detection System Based on Computer Vision

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5109
Author(s):  
Mariano Gonzalez-de-Soto ◽  
Rocio Mora ◽  
José Antonio Martín-Jiménez ◽  
Diego Gonzalez-Aguilera
Keyword(s):  
Computer Vision ◽  
Open Source Software ◽  
Detection System ◽  
Low Cost ◽  
Obstacle Detection ◽  
Road Accidents ◽  
The Past ◽  
Video Images ◽  
Infra Red ◽  
Different Types

A new roadway eventual obstacle detection system based on computer vision is described and evaluated. This system uses low-cost hardware and open-source software to detect and classify moving elements in roads using infra-red and colour video images as input data. This solution represents an important advancement to prevent road accidents due to eventual obstacles which have considerably increased in the past decades, mainly with wildlife. The experimental evaluation of the system demonstrated that the proposed solution detects and classifies correctly different types of moving obstacles on roads, working robustly under different weather and illumination conditions.

scholarly journals Vision Based Obstacle Detection Module for a Wheeled Mobile Robot

10.5772/8997 ◽  
2010 ◽  
Author(s):  
Oscar Montiel ◽  
Alfredo Gonzalez ◽  
Roberto Sepulve
Keyword(s):  
Mobile Robot ◽  
Obstacle Detection ◽  
Wheeled Mobile Robot

Point to-Point and Path Following Navigation of Mobile Robot in Farm Settings

2014 ◽  
Author(s):  
F. Heidari ◽  
R. Fotouhi
Keyword(s):  
Mobile Robot ◽  
Path Following ◽  
Obstacle Detection ◽  
Wheeled Mobile Robot ◽  
Sensor Data ◽  
Integrated Navigation ◽  
Fully Integrated ◽  
Navigation Strategy ◽  
Point Motion ◽  
Point To Point

A fully integrated navigation strategy of a wheeled mobile robot in farm settings and off-road terrains is described here. The proposed strategy is composed of four main actions which are: sensor data analysis, obstacle detection, obstacle avoidance, and goal seeking. Using these actions, the navigation approach is capable of autonomous row-detection, row-following and path planning motion in outdoor settings such as farms. In order to drive the robot in off-road terrain, it must detect holes or ground depressions (negative obstacles), that are inherent parts of these environments, in real-time at a safe distance from the robot. Key originalities of the proposed approach are its capability to accurately detect both positive (over ground) and negative obstacles, and accurately identify the end of the rows of trees/bushes in farm/orchard and enter the next row. Experimental evaluations were carried out using a differential wheeled mobile robot in different farm settings. The mobile robot, used for experiments, utilizes a tilting unit which carries a laser range finder to detect objects in the environment, and a RTK-DGPS unit for localization. The experiments demonstrate that the proposed technique is capable of successfully detecting and following rows (path following) as well as robust navigation of the robot for point-to-point motion.

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