Path planning for mobile robots navigation with obstacle avoidance based on octrees

2020 ◽  
Vol 25 (4) ◽  
pp. 25-30
Author(s):  
Rud V.V. ◽  
◽  
Panaseiko H.N. ◽  
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Real Time ◽  
Detection System ◽  
Test Results ◽  
Depth Sensing ◽  
The Road ◽  
Existing Problems ◽  
Laser Scanners ◽  
Motor Actions

The article considers the problem of navigating mobile robots and finding the best way to the goal in real-time in a space surrounded by unknown objects. The motor actions of the robot must be defined and adapted to changes in the environment. When using only laser scanners on mobile work, objects above or below the lasers' level will remain obstacles to the robot. Current algorithms and principles of navigation are considered. Extended the existing real-time interference detection system using lasers by adding a camera that calculates the length of objects. The new system has been successfully implemented and tested in a mobile robot, ensuring the passage of the road providing collision-free paths. The obtained simulation results are presented in the article. The existing problems of navigation of mobile robots, which are moving in the particular area from their position to the specified destination on the map, were investigated. The current problem is the inability to spot objects that are not on the same level as the mobile robot's lasers. Moreover, the task is complicated when you need to recognize such objects while the robot is moving in real time. The current algorithms and principles of navigation given by previous research and publications are analyzed. As a result of the work, the existing system of recognition and avoidance of obstacles was expanded. Prior to that, the system used only odometry and information obtained from laser scanners, without obtaining data from other sources of environmental information. The idea of development was to use a camera, which was already part of the components of the researched mobile robot. It has become possible to generate a pointcloud relative to the environment, using a depth sensing camera to calculate the distance to objects. Because the density of the received data in the form of a pointcloud is too high for further processing, a downsample VoxelGrid filter was used, which reduces the density of the point cloud. VoxelGrid belongs to the PCL library. Another problem was the removal of information about unnecessary objects in the camera's field of view. These include the floor, ceiling, parts of the robot (such as a manipulator). The PassThrough filter from the PCL library was used to solve this problem. The next step is to process the filtered data using OctoMap. As a result, an octree is generated. A top-down projection is created from the octree generated in the previous step. The resulting projection must be processed and converted into polygonal obstacles. Only then they will be marked by teb_local_planner as obstacles. The developed system was successfully implemented and tested both in the Gazebo simulation and in the researche mobile robot. The path with obstacles will be completed without collisions. The paper presents the obtained test results.

scholarly journals A Low Cost Vision-Based Road-Following System for Mobile Robots

2018 ◽  
Vol 8 (9) ◽  
pp. 1635 ◽  
Author(s):  
Haojie Zhang ◽  
David Hernandez ◽  
Zhibao Su ◽  
Bo Su
Keyword(s):  
Mobile Robots ◽  
Unscented Kalman Filter ◽  
Detection System ◽  
Tracking System ◽  
Low Cost ◽  
Recognition Rate ◽  
Road Detection ◽  
The Road ◽  
Road Following ◽  
Following Error

Navigation is necessary for autonomous mobile robots that need to track the roads in outdoor environments. These functions could be achieved by fusing data from costly sensors, such as GPS/IMU, lasers and cameras. In this paper, we propose a novel method for road detection and road following without prior knowledge, which is more suitable with small single lane roads. The proposed system consists of a road detection system and road tracking system. A color-based road detector and a texture line detector are designed separately and fused to track the target in the road detection system. The top middle area of the road detection result is regarded as the road-following target and is delivered to the road tracking system for the robot. The road tracking system maps the tracking position in camera coordinates to position in world coordinates, which is used to calculate the control commands by the traditional tracking controllers. The robustness of the system is enhanced with the development of an Unscented Kalman Filter (UKF). The UKF estimates the best road borders from the measurement and presents a smooth road transition between frame to frame, especially in situations such as occlusion or discontinuous roads. The system is tested to achieve a recognition rate of about 98.7% under regular illumination conditions and with minimal road-following error within a variety of environments under various lighting conditions.

Navigation of a wheeled mobile robotic agent using modified grey wolf optimization controller

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chittaranjan Paital ◽  
Saroj Kumar ◽  
Manoj Kumar Muni ◽  
Dayal R. Parhi ◽  
Prasant Ranjan Dhal
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Real Time ◽  
Autonomous Navigation ◽  
Simulation Software ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Content Type ◽  
Cluttered Environment

PurposeSmooth and autonomous navigation of mobile robot in a cluttered environment is the main purpose of proposed technique. That includes localization and path planning of mobile robot. These are important aspects of the mobile robot during autonomous navigation in any workspace. Navigation of mobile robots includes reaching the target from the start point by avoiding obstacles in a static or dynamic environment. Several techniques have already been proposed by the researchers concerning navigational problems of the mobile robot still no one confirms the navigating path is optimal.Design/methodology/approachTherefore, the modified grey wolf optimization (GWO) controller is designed for autonomous navigation, which is one of the intelligent techniques for autonomous navigation of wheeled mobile robot (WMR). GWO is a nature-inspired algorithm, which mainly mimics the social hierarchy and hunting behavior of wolf in nature. It is modified to define the optimal positions and better control over the robot. The motion from the source to target in the highly cluttered environment by negotiating obstacles. The controller is authenticated by the approach of V-REP simulation software platform coupled with real-time experiment in the laboratory by using Khepera-III robot.FindingsDuring experiments, it is observed that the proposed technique is much efficient in motion control and path planning as the robot reaches its target position without any collision during its movement. Further the simulation through V-REP and real-time experimental results are recorded and compared against each corresponding results, and it can be seen that the results have good agreement as the deviation in the results is approximately 5% which is an acceptable range of deviation in motion planning. Both the results such as path length and time taken to reach the target is recorded and shown in respective tables.Originality/valueAfter literature survey, it may be said that most of the approach is implemented on either mathematical convergence or in mobile robot, but real-time experimental authentication is not obtained. With a lack of clear evidence regarding use of MGWO (modified grey wolf optimization) controller for navigation of mobile robots in both the environment, such as in simulation platform and real-time experimental platforms, this work would serve as a guiding link for use of similar approaches in other forms of robots.

scholarly journals A PRELIMINARY STUDY ON UPDATING HIGH DEFINITION MAPS: DETECTING AND POSITIONING A TRAFFIC CONE BY USING A STEREO CAMERA

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 271-274
Author(s):  
M. L. R. Lagahit ◽  
Y. H. Tseng
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Autonomous Vehicles ◽  
Detection System ◽  
Time Data ◽  
High Definition ◽  
Stereo Camera ◽  
The Road ◽  
On The Road ◽  
Self Driving Cars

Abstract. The concept of Autonomous Vehicles (AV) or self-driving cars has been increasingly popular these past few years. As such, research and development of AVs have also escalated around the world. One of those researches is about High-Definition (HD) maps. HD Maps are basically very detailed maps that provide all the geometric and semantic information on the road, which helps the AV in positioning itself on the lanes as well as mapping objects and markings on the road. This research will focus on the early stages of updating said HD maps. The methodology mainly consists of (1) running YOLOv3, a real-time object detection system, on a photo taken from a stereo camera to detect the object of interest, in this case a traffic cone, (2) applying the theories of stereo-photogrammetry to determine the 3D coordinates of the traffic cone, and (3) executing all of it at the same time on a Python-based platform. Results have shown centimeter-level accuracy in terms of obtained distance and height of the detected traffic cone from the camera setup. In future works, observed coordinates can be uploaded to a database and then connected to an application for real-time data storage/management and interactive visualization.

scholarly journals Development of a Real-Time Driver Health Detection System Using a Smart Steering Wheel

2020 ◽  
Vol 9 (3) ◽  
Author(s):  
Jae-Cheon Lee ◽  
Hao Liu
Keyword(s):  
Real Time ◽  
Traffic Safety ◽  
Detection System ◽  
Health Condition ◽  
Steering Wheel ◽  
Test Results ◽  
Vehicle Accidents ◽  
Hand Grip ◽  
State Of Vigilance ◽  
Electrocardiogram Ecg

The number of vehicle accidents due to driver drowsiness continues to increase. Therefore, prompt and effective detection for driver health during driving is crucial to improvement of traffic safety. A set of real-time health detection system built into a smart steering wheel for the driver is proposed in the paper. The driver's health condition (drowsiness) is detected by a developed algorithm by monitoring the driver’s biological signals, including respiration, hand grip force, photoplethysmogram (PPG), and electrocardiogram (ECG). Meanwhile the driver's state of arrhythmia, as a common cardiac disease, can be diagnosed too. The test results indicate that the developed real-time driver health detection system can effectively monitor the state of vigilance and the cardiac state, i.e. arrhythmia, of the driver.

Real-time Rockfall Detection System with Automatic Road Closure and Reopening using Doppler Radar Technology at the Ruinon Landslide, Italy

2021 ◽  
Author(s):  
Susanne Wahlen ◽  
Severin Stähly ◽  
Lino Schmid ◽  
Lorenz Meier ◽  
Tommaso Carlà ◽  
...  
Keyword(s):  
Real Time ◽  
Doppler Radar ◽  
Detection System ◽  
Radar System ◽  
Slope Instability ◽  
Alarm System ◽  
Protection Measures ◽  
Traffic Lights ◽  
The Road ◽  
Road Closure

<p>Transportation corridors in mountain regions are often situated at the bottom of narrow valleys. Changing slope stability conditions can put these routes at critical risk. Slope stabilization works (e.g., rock scaling, blasting) or structural protection measures (e.g., rock sheds, reinforced embankments, tunnels) are not always feasible or may not be cost-effective due to low average daily traffic or the expected event size. Route SP29 is the main connection road to Santa Catarina, a popular tourist resort in the Frodolfo River Valley, Lombardy, Italy. The Ruinon landslide is a major slope instability involving approximately 30 million m<sup>3</sup> of rock and debris and causes repeated rockfalls that can reach as far as the road. </p><p>We present a Doppler radar system for real-time rockfall detection and immediate road closure in case of an event. The rockfall radar permanently monitors the landslide area from the opposite side of the slope with a range of more than 1 km to the upper scarp. Radar technology works reliably regardless of visibility, i.e. in rain, fog or snowfall as well as at night. After an initial calibration period in summer 2020, we activated automatic road closure and reopening in case of a rockfall event; upon detection of rockfall in a defined region of interest, the radar system automatically switches the traffic lights to red. If the rock fall event reaches a defined zone near the road or the road itself, it remains closed and requires manual reset after site inspection with webcams at the radar site and the traffic lights. If the rockfall event remains above the road, then the radar system automatically releases the road again after 90 seconds. Automatic notifications about the status are sent to authorized user via email and SMS. In addition to the deployment of the alarm system using Doppler radar, the embankment along the endangered road section was reinforced and raised. These combined measures of protection structures and alarm system aim at maximising the opening hours of the street while providing the highest possible level of protection. Between July (installation) and December 2020, 60 rockfall events caused a road closure, with the road being automatically reopened by the system in approximately 85% of cases.</p>

Method for Detecting Moving Obstacles Using Passive 3D Visual Sensor

1993 ◽  
Vol 5 (4) ◽  
pp. 388-400
Author(s):  
Jun'ichi Takeno ◽  
◽  
Naoto Mizuguchi ◽  
Sakae Nishiyama ◽  
Kanehiro Sorimachi ◽  
...  
Keyword(s):  
Visual System ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Real Time ◽  
Visual Sensor ◽  
Real Time Processing ◽  
Moving Obstacles ◽  
The Right ◽  
Moving Obstacle ◽  
Auto Focusing

Of primary importance for mobile robots is their smooth movement to the targeted destination. To achieve this purpose, mobile robots must be able to detect a person in their environment, another mobile robot, or an object not described in the map and to avoid collision with it. Recognizing the strong need for providing robots with a visual system to evade obstacles, the authors first developed a real-time visual system to detect a moving obstacle and then studied the possibility of avoiding collisions by mounting the system on a mobile robot. The visual sensor used in this system is a passive optical stereo without any mechanical moving parts. Using a special slit patten, the sensor is configured in order to split the two images obtained by individual cameras place on the right and left and to project the split images onto one CCD sensor, providing approximately 200 auto-focusing subsystems. The sub-systems can operate independently of one another, enabling real-time processing. This paper reports on a visual sensor, a solution to the measurement accuracy problem concerning the detection of moving obstacles using the sensor, and visual system experiments on real-time detection of an actually moving object using the sensor.

Study on Improved APF Algorithm for Autonomous Mobile Robot

2014 ◽  
Vol 519-520 ◽  
pp. 1337-1341 ◽  
Author(s):  
Xiao Meng Shu ◽  
Da Ming Jiang ◽  
Lian Dai
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Local Minimum ◽  
Minimum Point ◽  
Autonomous Mobile Robot ◽  
Simulation Environment ◽  
Local Minimum Point

In algorithms of obstacle avoidance for autonomous mobile robot, APF algorithm is simple, real-time and smooth, but has some limitations for solving problems. For example, the local minimum point may trap mobile robots before reaching its goal. Even though many improved APF algorithms have been put forward, few articles describe the process in detail to show how these algorithms are applied. Considering above factors, this paper focuses on embodiment of abstract improved theory for APF algorithm by showing some changes with formulas and parameters. The whole work has been done in simulation environment. According to the results this paper draws a conclusion.

Stair Climbing of a Track-Driven Mobile Robot with Flipper Arm

2013 ◽  
Vol 393 ◽  
pp. 586-591
Author(s):  
Khairul Azmi Mahadhir ◽  
Cheng Yee Low ◽  
Hizzul Hamli ◽  
Ahmed Jaffar ◽  
Elwan Salleh ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Real Time ◽  
Pid Controller ◽  
Closed Loop ◽  
Stair Climbing ◽  
Matlab Simulink ◽  
Dc Motors

On both natural and manmade terrains, the maneuverability of mobile robots has been improving. Nevertheless, stair climbing remains a challenging functionality for mobile robots. In this paper, a step-by-step stair climbing approach is proposed for a track-driven mobile robot equipped with flipper arms. The flipper arms are actuated by DC motors controlled by PID controller. Potentiometers and rotary encoders are used to provide closed loop feedbacks. Executable codes are generated using Real-Time Workshop of MATLAB/Simulink. The reference angles to be followed by the flipper arm in stair climbing are emulated and verified by real time experiments.

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