Design of Robot Lawn Mower Based on Computer Vision

In this paper, we introduce a new research about mowing robot on obstacle avoidanceand path tracking controlling theoretically and practically, and propose the mowing control methodwhich based on computer vision. Lawn images collected by camera, through the extraction ofprogramming dealing with lawn, obstacles and boundary characteristics to achieve edge separation.Through special processing algorithm to determine boundary arises and obstacles location, size andspeed of the robot, with real-time capturing and processing. This paper gives the complete imagerecognition processing, and analyzes several methods of image filtering and edge detection, andproposes simple control algorithm for obstacle avoidance, and applies MATLAB for obstacleavoidance simulation. The results show that: the method can correctly identify the obstacles andboundaries, through the output about location, size of the obstacles and boundary, border slope andspeed of the robot to control robot mower. Most importantly, that computer vision applying in themowing robot itself is an innovation.

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An Optimized Computer Vision and Image Processing Algorithm for Unmarked Road Edge Detection

Advances in Intelligent Systems and Computing - Soft Computing and Signal Processing ◽

10.1007/978-981-13-3600-3_40 ◽

2019 ◽

pp. 429-437 ◽

Cited By ~ 1

Author(s):

Jayalakshmi Annamalai ◽

C. Lakshmikanthan

Keyword(s):

Image Processing ◽

Computer Vision ◽

Edge Detection ◽

Processing Algorithm ◽

Image Processing Algorithm

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Path tracking based on model predictive control with variable predictive horizon

Transactions of the Institute of Measurement and Control ◽

10.1177/01423312211003809 ◽

2021 ◽

pp. 014233122110038

Author(s):

Huiran Wang ◽

Qidong Wang ◽

Wuwei Chen ◽

Linfeng Zhao ◽

Dongkui Tan

Keyword(s):

Model Predictive Control ◽

Real Time ◽

Predictive Control ◽

Control Algorithm ◽

Path Tracking ◽

Response Analysis ◽

Tracking Accuracy ◽

Tracking Method ◽

Comprehensive Performance ◽

Path Tracking Method

Model predictive control is one of the main methods used in path tracking for autonomous vehicles. To improve the path tracking performance of the vehicle, a path tracking method based on model predictive control with variable predictive horizon is proposed in this paper. Based on the designed model predictive controller for path tracking, the response analysis of path tracking control system under the different predictive horizons is carried out to clarify the influence of predictive horizon on path tracking accuracy, driving comfort and real-time of the control algorithm. Then, taking the lateral offset, the steering frequency and the real-time of the control algorithm as comprehensive performance indexes, the particle swarm optimization algorithm is designed to realize the adaptive optimization for the predictive horizon. The effectiveness of the proposed method is evaluated via numerical simulation based on Simulink/CarSim and hardware-in-the-loop experiment on an autonomous driving simulator. The obtained results show that the optimized predictive horizon can adapt to the different driving environment, and the proposed path tracking method has good comprehensive performance in terms of path tracking accuracy of the vehicle, driving comfort and real-time.

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Fuzzy Control for the Obstacle Avoidance of a Quadrotor UAV

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.775.307 ◽

2015 ◽

Vol 775 ◽

pp. 307-313 ◽

Cited By ~ 1

Author(s):

Zi Mu Wen ◽

Shu Dao Zhou ◽

Min Wang

Keyword(s):

Fuzzy Control ◽

Real Time ◽

Obstacle Avoidance ◽

Control Algorithm ◽

Ultrasonic Sensor ◽

Practical Application ◽

Ultrasonic Sensors ◽

Quadrotor Uav ◽

Simulation Results ◽

Fuzzy Control Algorithm

To solve the presence of the phantom phenomenon when single ultrasonic sensor detects obstacles, this paper proposes a multi-ultrasonic sensors design using grouping cycle emission. Using the fuzzy control algorithm in the obstacle avoidance simulation, the quadrotorflies through an unknown environment. The simulation results show that the algorithm can meet the requirements of the quadrotor obstacle avoidance , and have the characteristics of real-time and accuracy , provide the foundation for further practical application.

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Novel design for real time path tracking with computer vision using neural networks

International Journal of Computational Vision and Robotics ◽

10.1504/ijcvr.2010.038193 ◽

2010 ◽

Vol 1 (4) ◽

pp. 380 ◽

Cited By ~ 1

Author(s):

Abhinav Agarwal ◽

Sanketh Datla ◽

Barjeev Tyagi ◽

Rajdeep Niyogi

Keyword(s):

Neural Networks ◽

Computer Vision ◽

Real Time ◽

Path Tracking ◽

Time Path ◽

Novel Design

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Iterative Design of Sonification Techniques to Support People with Visual Impairments in Obstacle Avoidance

ACM Transactions on Accessible Computing ◽

10.1145/3470649 ◽

2021 ◽

Vol 14 (4) ◽

pp. 1-27

Author(s):

Giorgio Presti ◽

Dragan Ahmetovic ◽

Mattia Ducci ◽

Cristian Bernareggi ◽

Luca A. Ludovico ◽

...

Keyword(s):

Computer Vision ◽

Real Time ◽

Obstacle Avoidance ◽

Mobile App ◽

Independent Mobility ◽

Listening Tests ◽

Recent Computer ◽

Computer Vision Technology ◽

White Cane ◽

Real Time Information

Obstacle avoidance is a major challenge during independent mobility for blind or visually impaired (BVI) people. Typically, BVI people can only perceive obstacles at a short distance (about 1 m, in case they are using the white cane), and some obstacles are hard to detect (e.g . , those elevated from the ground), or should not be hit by the white cane (e.g . , a standing person). A solution to these problems can be found in recent computer-vision techniques that can run on mobile and wearable devices to detect obstacles at a distance. However, in addition to detecting obstacles, it is also necessary to convey information about them in real time. This contribution presents WatchOut , a sonification technique for conveying real-time information about the main properties of an obstacle to a BVI person, who can then use this additional feedback to safely navigate in the environment. WatchOut was designed with a user-centered approach, involving four iterations of online listening tests with BVI participants in order to define, improve and evaluate the sonification technique, eventually obtaining an almost perfect recognition accuracy. WatchOut was also implemented and tested as a module of a mobile app that detects obstacles using state-of-the-art computer vision technology. Results show that the system is considered usable and can guide the users to avoid more than 85% of the obstacles.

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