Vision-Based Navigation Of An Autonomous Guided Vehicle For Tracking

This project proposes a navigation control system for an Autonomous Guided Vehicle (AGV) by detecting and recognizing line tracking with USB (Universal Serial Bus) camera. In this project a commercial robot kit, a laptop computer and a USB camera are used as the main components of the system. The use of Microsoft DirectShow technique and COM programming, the USB camera will enable the system to obtain ' the digital images directly without using frame grabbers. This feature makes the system more economical and compact. The vision-based navigation system structure is composed of several processes such as grabbing images, track detection, fuzzy logic controller and' motor drive controller. During the navigation process, the AGV can recognize the straight and crossing track lines, detect the obstacle that might appear in the navigational path, calculate the position and orientation of the AGV. When the robot has confirmed its position and orientation, the fuzzy controller is used to keep the AGV on the track. This proposed navigation system only needs a minimum modification in implementing on any mobile robot platform that can be used in robotic research, education, laboratories, office environment and factory

Omni Directional Indoor Mobile Robot

This paper presents an approach which uses an omni–directional robot for indoor use. The use of the omni-directional robot describes a ‘no head no tail’ robot. This will reduce movement recovery in time and space. In additions its mechanism makes it possible to run as a reactive robot without any complex programming. This robot is designed to use an algorithm control (reactive) based on the vision control system. The aim of this project is to design an indoor mobile robot for jogging partner operation

Development of a quadruped crawling robot prototype

Although wheeled robots are commonly used, it has limited ability to move to any terrains at ease. They suffer from difficulties when travelling over uneven and rough terrains. Legged robots have an advantage over the wheeled robots in that they are suited for such situations. The implementation of legged robots normally requires many motors to move every joint in a robot leg. Additional motor will increase the construction cost, robot weight, and the demand for power supply. Moreover, robot simulation becomes more complex. This research is related to the design and development of a cost effective quadruped autonomous robot. The robot can moves according to a unique pattern using three servo motors as its actuator in each of its leg. The design of the robot is firstly made with CAD program and then the structure of the body and the leg is analyzed in order to find a conect balance and to make sure the servo motors are capable to move the robot. A prototype of the quadruped robot is fabricated and tested thoroughly. Experimental studies are carried out to test its stability issues when the robot moves. The robot is capable of moving forward, backward, turn left and turn right by crawling its way. A microcontroller is used as the brain of the robot assisted by two analog distance sensor for better obstacle sensing. It uses a rechargeable battery as the power supply for the microcontroller. The servo motors on the other hand are powered by another rechargeable battery. At the end of this research, a working prototype has been developed

Open-source project (OSPS) platform for outdoor quadcopter

In recent years, there has been an increasing interest in quadcopter technology implementation in the real world; for instance in real estate photography, aerial surveying, periodic forest monitoring, and search/rescue missions. Gene rally, each quadcopter implementation required different sensors which are needed to attach and integrate into quadcopter system. However, the most critical part in almost cases is preparing the quad copter flight performance and capability to be suit ed in any outdoor applications. Because of that reason , this paper has proposed an implementation of Open-Source Project (OSPs) platform as autonomous Unmanned Aerial Vehicle (UAV) quadcopter development that can be fitted for any outdoor applications or even in research experimental purposes. We started out with an explanation about the genera l approach that has been used in the development of a quadcopter testbed, and then followed with detail explanations in the OSP platform approach. The OSP platform is the most popular approach. The main reason is because of their flexibility in both hardware and software. The basic quadcopter configuration for autonomous flight also presented and applied. This paper also provided several outdoor experiments results in uncontrolled environment that have been executed using our developed testbed to evaluate their performance, such as attitude and altitude stabilization, interference and vibration effect, and trajectory mapping generation. Finally, throughout this project, we realized that the OPSs quadcopter platform has offered almost complete frameworks in the development of quadcopter for any outdoor applications or even as a research testbed system

UAV Control System with Time to Collision (TTC) Prediction Capability

This paper presents the development of an Unmanned Aerial Vehicle (UAV) control system simulation with collision avoidance prediction capability using the Time-to-Collision (TTC) model. TTC is the time required for a UAV either to collide with any static obstacle or completely stop without applying any braking control system when the throttle is fully released. Flight mission data collected from the quadcopter testbed platform experiments in the real environment in order to develop TTC model. The horizontal ground speed, throttle magnitudes, and flight time stamp are downloaded from the onboard quadcopter, filtered, analyzed, and optimize using Particles Swarm Optimization (PSO) algorithm to find the optimal TTC model. This model provides predictions of time before UAV will collide with the obstacle in the same path based on their current parameters, for instance, current speed and payload. This development of UAV’s control system implemented in Matlab/Simulik. The PID-based controller is utilized to stabilize the quadcopter and collision avoidance control systems with the TTC model to assist the system in order to avoid a collision from happening. Simulation tests performed proved the capability of UAV to stop at a safe distance and avoid collisions with the obstacles that existed based on TTC model prediction during flight successfully

Modelling of time-to collision for unmanned aerial vehicle using particles swarm optimization

A method for the development of Time-to-Collision (TTC) mathematical model for outdoor Unmanned Aerial Vehicle (UAV) using Particles Swarm Optimization (PSO), are presented. TTC is the time required for a UAV either to collide with any static obstacle or completely stop without applying any braking control system when the throttle is fully released. This model provides predictions of time before UAV will collide with the obstacle in the same path based on their parameter, for instance, current speed and payload. However, this paper focus on the methodology of the implementation of PSO to develop the TTC model for 5 different set of payloads. This work utilizes a quadcopter as our testbed system that equipped with a Global Positioning System (GPS) receiver unit, a flight controller with data recording capability and ground control station for real-time monitoring. The recorded onboard flight mission data for 5 different set of payloads has been analyzed to develop a mathematical model of TTC through the PSO approach. The horizontal ground speed, throttle magnitudes and flight time stamp are extracted from the on-board quadcopter flight mission. PSO algorithm is used to find the optimal linear TTC model function, while the mean square error is used to evaluate the best fitness of the solution. The results of the TTC mathematical model for each payload are described

An Improvement On Mechanism Of Motorcycle Rim Adjusting Jig

Abstract

Development Of A Quadruped Crawling Robot Prototype

Although wheeled robots are commonly used, it has limited ability to move to any terrains at ease. They suffer from difficulties when travelling over uneven and rough terrains. Legged robots have an advantage over the wheeled robots in that they are suited for such situations. The implementation of legged robots normally requires many motors to move every joint in a robot leg. Additional motor will increase the construction cost, robot weight, and the demand for power supply. Moreover, robot simulation becomes more complex. This research is related to the design and development of a cost effective quadruped autonomous robot. The robot can moves according to a unique pattern using three servo motors as its actuator in each of its leg. The design of the robot is firstly made with CAD program and then the structure of the body and the leg is analyzed in order to find a correct balance and to make sure the servo motors are capable to move the robot. A prototype of the quadruped robot is fabricated and tested thoroughly. Experimental studies are carried out to test its stability issues when the robot moves. The robot is capable of moving forward, backward, turn left and turn right by crawling its way. A microcontroller is used as the brain of the robot assisted by two analog distance sensor for better obstacle sensing. It uses a rechargeable battery as the power supply for the microcontroller. The servo motors on the other hand are powered by another rechargeable battery. At the end of this research, a working prototype has been developed