Design and Path Planning of Autonomous Solar Lawn Mower

2021 ◽  
Author(s):  
Souhail Hazem ◽  
Mohamed Mostafa ◽  
Ehab Mohamed ◽  
Mohamed Hesham ◽  
Abdelrahman Mohamed ◽  
...  
Keyword(s):  
Path Planning ◽  
Mechanical Design ◽  
Operating Time ◽  
Lithium Ion ◽  
Base Station ◽  
Raspberry Pi ◽  
Processing Application ◽  
Lawn Mower ◽  
Running Cost ◽  
Robotic Vehicle

Abstract Current conventional lawn mowers have the following drawbacks; high initial costs, increasing engine noise levels, high operating costs due to high fuel consumption rates, the need to implement perimeter wires across the desired lawn mowing field, and high exhaustion of the operator in the long operating time. Hence, the need for a system that can achieve the same cutting effect of the existing lawn mowers with little or no operator’s fatigue, minimized noise pollution and running cost has risen. In present work, design of an autonomous solar lawn mower, a robotic vehicle that cut grass automatically with little human intervention, is discussed. The robotic vehicle is powered by Lithium-Ion batteries and depend on solar power delivered from a solar base station for charging the batteries. The mechanical design of the vehicle is flexible with the ability to control the height of the vehicle during grass mowing. Differential steering, with the implementation of multiple sensors is presented for obstacle avoidance. Also, a Raspberry Pi microcontroller for the image processing application through a camera is used for path planning. Furthermore, a solar based station structure is designed for charging the robotic vehicle batteries with minimized running cost, utilization of renewable energy source, no health hazards, not having any effect on the environment, and human’s effort and time are saved.

scholarly journals OATCR: Outdoor Autonomous Trash-Collecting Robot Design Using YOLOv4-Tiny

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2292
Author(s):  
Medhasvi Kulshreshtha ◽  
Sushma S. Chandra ◽  
Princy Randhawa ◽  
Georgios Tsaramirsis ◽  
Adil Khadidos ◽  
...  
Keyword(s):  
Path Planning ◽  
Object Detection ◽  
Mechanical Design ◽  
Ultrasonic Sensor ◽  
Raspberry Pi ◽  
Robot Design ◽  
Detection Time ◽  
Average Precision ◽  
The Brain ◽  
Potential Use

This paper proposed an innovative mechanical design using the Rocker-bogie mechanism for resilient Trash-Collecting Robots. Mask-RCNN, YOLOV4, and YOLOv4-tiny were experimented on and analyzed for trash detection. The Trash-Collecting Robot was developed to be completely autonomous as it was able to detect trash, move towards it, and pick it up while avoiding any obstacles along the way. Sensors including a camera, ultrasonic sensor, and GPS module played an imperative role in automation. The brain of the Robot, namely, Raspberry Pi and Arduino, processed the data from the sensors and performed path-planning and consequent motion of the robot through actuation of motors. Three models for object detection were tested for potential use in the robot: Mask-RCNN, YOLOv4, and YOLOv4-tiny. Mask-RCNN achieved an average precision (mAP) of over 83% and detection time (DT) of 3973.29 ms, YOLOv4 achieved 97.1% (mAP) and 32.76 DT, and YOLOv4-tiny achieved 95.2% and 5.21 ms DT. The YOLOv4-tiny was selected as it offered a very similar mAP to YOLOv4, but with a much lower DT. The design was simulated on different terrains and behaved as expected.

A Modified QPSO for Robotic Vehicle Path Planning

2018 ◽  
Author(s):  
Pedro B. Fernandes ◽  
Roberto C. Limao De Oliveira ◽  
Joao Viana Fonseca Neto
Keyword(s):  
Path Planning ◽  
Robotic Vehicle ◽  
Vehicle Path

scholarly journals A Path Planning Strategy with Ant Colony Algorithm for Series Connected Batteries

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1816
Author(s):  
Yang Chen ◽  
Teng Shen ◽  
Shiyan Yang ◽  
Xiaofang Liu ◽  
Ru Yang ◽  
...  
Keyword(s):  
Path Planning ◽  
Lithium Ion Batteries ◽  
Ant Colony Algorithm ◽  
Graph Model ◽  
Lithium Ion ◽  
Operating Conditions ◽  
Ant Colony ◽  
Planning Strategy ◽  
Battery Cells

This article presents a path planning strategy with ant colony algorithm for series connected batteries. The motive of this paper is the increasing need for efficient and fast equalization for Lithium-ion batteries. There are many great papers on the design of the equalization circuits. However, they lack the part of path planning strategy for the balancing circuits. To solve this issue, we adopt the graph model to represent the balancing paths among different battery cells and then construct two optimal models based on the best efficiency and speed, respectively. Finally, ant colony algorithm is used to solve these two models. This makes it possible to achieve different goals according to the practical operating conditions. We validate the function of the proposed path planning strategy through an example of 13 series connected battery balancing system.

scholarly journals Extending Smart Phone Based Techniques to Provide AI Flavored Interaction with DIY Robots, over Wi-Fi and LoRa interfaces

2019 ◽  
Vol 9 (3) ◽  
pp. 224 ◽  
Author(s):  
Dimitrios Loukatos ◽  
Konstantinos G. Arvanitis
Keyword(s):  
Credit Card ◽  
Learning Experience ◽  
Low Cost ◽  
Voice Recognition ◽  
Smart Phone ◽  
Learning Activity ◽  
Raspberry Pi ◽  
Programming Environments ◽  
Robotic Vehicle ◽  
Educational Applications

Inspired by the mobile phone market boost, several low cost credit card-sized computers have made the scene, able to support educational applications with artificial intelligence features, intended for students of various levels. This paper describes the learning experience and highlights the technologies used to improve the function of DIY robots. The paper also reports on the students’ perceptions of this experience. The students participating in this problem based learning activity, despite having a weak programming background and a confined time schedule, tried to find efficient ways to improve the DIY robotic vehicle construction and better interact with it. Scenario cases under investigation, mainly via smart phones or tablets, involved from touch button to gesture and voice recognition methods exploiting modern AI techniques. The robotic platform used generic hardware, namely arduino and raspberry pi units, and incorporated basic automatic control functionality. Several programming environments, from MIT app inventor to C and python, were used. Apart from cloud based methods to tackle the voice recognition issues, locally running software alternatives were assessed to provide better autonomy. Typically, scenarios were performed through Wi-Fi interfaces, while the whole functionality was extended by using LoRa interfaces, to improve the robot’s controlling distance. Through experimentation, students were able to apply cutting edge technologies, to construct, integrate, evaluate and improve interaction with custom robotic vehicle solutions. The whole activity involved technologies similar to the ones making the scene in the modern agriculture era that students need to be familiar with, as future professionals.

scholarly journals An Iot Based Forest Fire Detection using Raspberry Pi

2019 ◽  
Vol 8 (4) ◽  
pp. 9126-9132
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Early Stage ◽  
Fire Detection ◽  
Base Station ◽  
Raspberry Pi ◽  
Alert Message ◽  
Forest Fire Detection ◽  
Monitoring Stations

As we all know forests are the main source of oxygen and its protection is essential to sustain the human and animal race. Since we all learnt about the necessity of air, yet we lack at taking measures to protect our mother forest. Forest Fires are the main reason for the deforestation and destruction of trees and wildlife. Forest Fires are due to these two ways either by man-made or naturally caused. In either way we have to pay for the loss occurred because we have left with only certain area for the forest. So, we have to take measures to prevent forest fire at its early stage. The main aim of our project is to design and implement an IoT based hardware module that could detect the fire and prevent it by alerting the monitoring stations with an alert message and also provides location to the nearest base station. An automatic message will be sent to the nearest base station in addition to these, it has a 360 degrees rotation camera which helps to provide continuous surveillance. We can rotate the camera in any direction from the base station itself. A buzzer that alarms when the incident is happening and a water motor, this water motor will be on automatically. We can also find location where the incident is taking place with the help of Wi-Fi module. This device helps in identifying the fire at its early stage and helps in the prevention of spread all over the forest.

scholarly journals Design and Implementation of Autonomous Quadcopter using SITL Simulator

2020 ◽  
pp. 1-16
Keyword(s):  
Image Processing ◽  
Path Planning ◽  
Service Delivery ◽  
Raspberry Pi ◽  
End User ◽  
Autonomous Flight ◽  
Python Script ◽  
Design And Implementation ◽  
Additional Task ◽  
Military Security

In recent years Quadcopter has been used in many applications such as military, security & surveillance, service delivery, disaster rescue and much more due to its flexibility of flying. In this paper, Quadcopter will be used for mail delivery between many locations that is received from the end user. The Quadcopter will execute an autonomous flight using the concept of companion PC. Raspberry PI 3 (RPI3) will control the Quadcopter by command the controller of the drone (Pixhawk) by using DroneKit-Python API to send MAVLink messages to the Ardupilot. This concept is useful to perform an additional task to the autopilot and provide such a smart capability like image processing and path planning which cannot be done by the flight controller alone. Basically, the idea has been stimulated and the code has been tested by using the SITL Simulator with MAVProxy under Ubuntu environment. The result of controlling the Quadcopter using Python script was excellent and give a motivation to implement the same script on a real Quadcopter. The implementation on real Quadcopter was perfect as it has given the same behavior as the SITL drone in the simulation.

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