LEARNING OBJECTIVES
- Students will learn about the mechatronic system design methodology by exploring multiple levels of a complex robotic arm, from concepts like PWM and encoders to applications like image processing and manipulator control
- Students will study and verify the functionality of subsystems by using LabVIEW to realize theoretical concepts like kinematics and techniques in vision processing
- Students apply the mechatronic system design methodology to run a goal directed line following experiment
COURSE ALIGNMENT
| Level |
University |
| Topic |
Mechatronics |
| Style |
Lab Workbook |
| Prerequisite Skills |
Basic LabVIEW familiarity recommended, matrix level mathemathics |
Pulse Width Modulation
This lab introduces students to Pulse Width Modulation (PWM), including the basic mathematical theory and practical application. Students use LabVIEW to generate a PWM signal and vary its properties, including frequency, step size, and duty cycle, and then output the signal to LEDs on the Mechatronic Systems board to control brightness.
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Reading Encoders
In this lab, students will decode quadrature encoder data, implement a LabVIEW VI to decode quadrature encoder data, and add direction sense and calibration functionality. Students will review background information regarding encoders and perform in-lab exercises to learn essential skills. Required: Must complete previous labs before starting this lab.
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Forward Kinematics
In this lab, students will derive forward kinematics equations for determining the the position of an end effector given angular position of bars of a five-bar linkage. They will then model this in LabVIEW, and validate the model using physical coordinate information from the Mechatronic Systems board. To develop the knowledge of these topics, students will review background information and perform in-lab exercises to learn essential skills. Required: Must complete previous labs before starting this lab.
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PID Position Control
In this lab, students will study PID (proportional, integral, derivative) control and explore both mathematical and experimental methods for tuning a PID controller. Students will use LabVIEW to experiment with systems gains, and tune a robotic arm to a specification. The lab includes both background information regarding PID position control and in-lab exercises. Required: Must complete previous labs before starting this lab.
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Inverse Kinematics
In this lab, students will derive inverse kinematics equations for determining the angular position of bars of a five-bar linkage given the position of an end effector. They will then model this in LabVIEW, and validate the model using encoder information from the Mechatronic Systems board. To develop the knowledge of these topics, students will review background information and perform in-lab exercises to learn essential skills. Required: Must complete previous labs before starting this lab.
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Manipulator Control
In this lab, students use kinematic equations and PID to control a robot arm to follow trajectories. Students use LabVIEW experiment with gains to limit task-space error. The lab includes background information regarding manipulator control and in-lab exercises. Required: Must complete previous labs before starting this lab.
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Pattern Matching
In this lab, students will use a pattern matching technique in LabVIEW to recognize an object based on a template image. Students will experiment with different patterns, rotation angles, and match thresholds to find shapes on a landscape. The lab includes both background information regarding image thresholding and in-lab exercises.
In this lab, students will practice application of pattern matching in LabVIEW and use pattern matching to extract road information. To develop the knowledge of these topics, students will review background information regarding pattern matching and perform in-lab exercises to learn essential skills. Required: Must complete previous labs before starting this lab.
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Blob Detection
In this lab, students will learn and apply the blob detection (or particle analysis) technique for image processing. They will analyze static and dynamic images to hypothesize the outcome of blob analysis, and then use LabVIEW to perform the analysis and compare the results. They will also experiment to learn how threshold ranges can be used to improve a blob analysis so that particles can be accurately found in an image. Required: Must complete previous labs before starting this lab.
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Image Threshold
In this lab, students will use an image thresholding technique to segment an image to two categories, foreground and background, with the goal of detecting roads. Students will experiment the effectiveness of different thresholds and troubleshoot varying lighting conditions. The lab includes both background information regarding image thresholding and in-lab exercises.
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Image Processing
In this lab, students will explore image processing using thresholding, pattern matching, and blob analysis techniques. They will complete an activity to detect traffic signs and signals on a map, and use the information to control the behavior of a robotic arm that is navigating the map. The lab includes background information regarding image processing and in-lab exercises. Required: Must complete previous labs before starting this lab.
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State Machine
In this lab, students will learn about the state machine system architecture, and apply it to automate a robot arm to follow a set of rules while navigating a map. In LabVIEW, students will tune the system, configure states, and validate system behavior. The lab includes background information regarding state machines and in-lab exercises. Required: Must complete previous labs before starting this lab.
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Goal Directed Line Following
In this lab, students will complete a culminating lab to implement and analyze a goal directed line following robot arm. Students integrate the subsystems they previously studied, including manipulator control, image processing, and state machines. After integrating the subsystems in LabVIEW, students further experiment to complete different tasks and overcome obstacles with the robot arm, such as moving from point A to point B autonomously, while only travelling along roads and avoiding obstacles.
Required: Must complete previous labs before starting this lab.
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NI ELVIS II/II+
NI ELVIS II/II+
The NI Educational Laboratory Virtual Instrumentation Suite (NI ELVIS) is a versatile laboratory platform that enables educators to teach over 20 different courses across science and engineering departments. The NI ELVIS integrates 12 common lab instruments including an oscilloscope, function...
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LabVIEW
LabVIEW
LabVIEW is systems engineering software for applications that require test, measurement, and control with rapid access to hardware and data insights.
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Quanser QNET Mechatronic Systems Board
Quanser QNET Mechatronic Systems Board
The Quanser QNET Mechatronic Systems Add-On Board is NI's most comprehensive solution to teaching mechatronics. This board includes a four-bar linkage system, DC motors, encoders, and a camera for system-level lab challenges on tasks such as vision, image processing, and low-level signal aspects...
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Detailed Requirements
Required Software
Download Academic Software, Learn About Software Licensing
- NI ELVIS III Software Bundle (2018 or later)
- LabVIEW (Requires license)
- LabVIEW Real-Time Module (Requires license)
- NI ELVIS III Toolkit
- LabVIEW Control Design & Simulation (Requires License)
- Vision Acquisition Software (Requires License)
- Vision Development Module (Requires License)
Required Hardware
Purchase Engineering Education Products
Instructor resources are available.
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