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Matlab advanced work

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1. Installation Method

1.1. Installation Package Acquisition

(1). Send Email to service@rflysim.com to inquiry and buy the desired version, you will obtain an installation package and an activation code. (2). Use MATLAB to enter the folder of the installation package, and run “OnekeyScript” to input your activation code as shown below.

../_images/A-1.jpg Fig. 4.1 RflySim registration dialog

(3). Then， click the “OK” button, and all tools and apps of RflySim platform will be installed automatically.

../_images/AutoInstall.gif Fig. 4.2 One-key installation and configuration

1.2. Product Price List

You can read our latest document about the advanced features of RflySim platform: lesson13

Please Contact with service@rflysim.com for Price.

RflyExpCode

This is the instructional package for ‘Multicopter Design and Control Practice’. Please see https://rflysim.com for detailed information.
You should download and install the RflySim Basic package to use the PPTs and codes, the download link is https://rflysim.com/download

Introduction

The model in “e0” is mainly used for the introduction of the experimental platform, corresponding to the relevant content in Chapters 3 and 4 of the book.
The last 8 chapters of the book correspond to 8 experiments, of which Propulsion System Design Experiment has no relevant instructional package. Experiments 2 to 8 correspond to the contents of Chapters 6 to 12, and the corresponding files are e2 to e8.
There are three sub-files in each folder, which correspond to the basic experiment, analysis experiment and design experiment in each experiment. Analysis experiment of chapter 2 has no source file package–“e2/e2.2”,becasuse it mainly focus on theoretical calculation and analysis.

Details

The comparison between the instructional package and each experiment is as follows:
e2:Dynamic Modeling Experiment;
e3:Sensor Calibration Experiment;
e4:State Estimation and Filter Design Experiment;
e5:Attitude Controller Design Experiment;
e6:Set-point Controller Design Experiment;
e7:Semi-autonomous Control Model Design Experiment;
e8:Failsafe Logic Design Experiment.

1.3. Effect after Installation

You will obtain the following shortcuts on Desktop, where Python38Env is a Python environment for vison/OpenCV development, RflySim3D is our latest UE4-based 3D environment simulation program, HITLRun is an one-key script for hardware-in-the-loop simulation of multiple vehicles, and SITLRun is an one-key script for Software-in-the-loop simulation of multiple vehicles.

../_images/Advanced1.png These software tools along with other program installed into the system play important role in accelerate the development efficiency of control systems. Their relationships and using phase are presented in the following figure.

../_images/Advanced2.png Among all apps, the CopterSim is the core software for RlfySim platform. The complete UI of CopterSim after registration is mainly divided into five parts. The box (a) of the figure below is the interface for configuring the multicopter model and flight environment parameters, where readers can select propulsion system components to assemble different types of multicopters for subsequent simulations. Box (b) is the model parameter calculation and database management interface, which is mainly used to calculate the model parameters of the assembled multicopter and store the results into the database for subsequent use with convenient database management functions. Box (c) is the advanced function area, including swarm simulation, UE4 scene selection, and other functions, which will be described in detail later. Box (d) is mainly used to connect the Pixhawk autopilot and control the start and stop of the simulation. Box (e) is used to display the real-time message received from the Pixhawk autopilot as well as the position and attitude information of the simulated vehicle model.

../_images/Quan-app1-FigA.2.jpg Fig. 4.3 CopterSim interface after registration

1.4. Custom Multicopter Configuration

In the first line of the model configuration interface shown in Fig.4.3a, the configurable parameters include basic information such as the total weight, diagonal size, and flight altitude. In the second to the fifth rows of Fig.4.3a, readers can select the propulsion system components or parameters for the multicopter components, such as motors, propellers, ESCs, and batteries. CopterSim offers two options for selecting propulsion components. As shown in Fig.4.4, the first is to assemble a multicopter directly from the propulsion system branded model database which covers many common products on the market.

../_images/Quan-app1-FigA.3.jpg Fig. 4.4 Custom model parameter input interface

Since the propulsion system product database is difficult to cover all of the products in the world, CopterSim also provides a function to customize the component parameters which enables a more flexible way to configure a multicopter model. As shown in Fig.4.4a, click on the “Custom Design” option at the end of the first line to enter the component custom parameter interface shown in Fig.4.4b. In this interface, readers can customize the detailed parameters of motors (KV value, no-load voltage, internal resistance), ESCs, batteries, and propellers. In theory, by using the “Custom Design” function, readers can simulate any propulsion system components, even products that do not exist on the market.

After a multicopter model is configured, clicking on the “Calculate” button in Fig.4.3b will automatically analyze the feasibility of the inputted multicopter configuration. Unpractical multicopter configurations may cause simulation failures, such as insufficient thrust to take off, ESC and motor overheat due to excessive battery voltage, or the propeller size is too large for the fuselage. As shown in Fig.4.5, after checking the inputted multicopter configuration, CopterSim will prompt a warning dialog if the configuration is unpractical, and the reader needs to re-select a practicable multicopter configuration.

../_images/Quan-app1-FigA.4.jpg Fig. 4.5 Model configuration feasibility detection warning dialog

For beginners or readers who are not familiar with multicopter design, it is a difficult task to configure a multicopter that can work. So CopterSim also provides a convenient function to directly select vehicle configurations through a prepared model database. As shown in Fig.4.6, in the drop-down list of the “Model Database” item, the reader can select a usable multicopter configuration (or modify parameters based on it) to quickly obtain the multicopter model for simulations.

../_images/Quan-app1-FigA.5.jpg Fig. 4.6 Multicopter model selection from model database

After configuring a multicopter through the three methods mentioned above, clicking the “Add to Database” button shown in Fig.4.6 will store the new model into the model database for use in the future. Readers can also delete the current model from the database by clicking the “Delete from Database” button shown in Fig.4.6.

1.5. Set Initial States

As shown in Fig.4.3c, CopterSim provides an interface to modify the multicopter initial position and altitude. As shown in Fig.4.7, readers can enter the “x” and “y” coordinates (unit: m) of the multicopter and the value of the yaw angle (unit: degree), where the x-direction and y-direction point to the front and right of the multicopter, and the yaw angle is positive when rotating to right side.

../_images/Quan-app1-FigA.6.jpg Fig. 4.7 Setting initial simulation position

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2. Basic Features

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2.1. HIL Simulation for One Vehicle

You can open CopterSim and RflySm3D successively to start hardware-in-the-loop (HIL) simulation, or simple click the Desktop shortcut “HITLRun” and input the com number of the Pixhawk to start HIL simulation. The introduction of RflySim advanced platform and the method to start HIL simulation for one vehicle are presented in the following video:

../_images/Advanced3.png RflySim: How to use hardware-in-the-loop simulation for one vehicle

2.2. HIL Simulation for Multiple Vehicles

You can also connect multiple Pixhawks to start HIL simulation for multiple vehicles, the procedure is presented in the following video:

../_images/Advanced4.png RflySim Advance Function: How to use hardware-in-the-loop simulation for UAV swarm

2.3. SIL Simulation for One Vehicle

If you don’t have Pixhawk hardware, you can also run PX4 control software on Windows to form a software-in-the-loop simulation system with vehicle model in CopterSim through UDP network. The method to start a PX4&CopterSim SIL simulation for one vehicle is presented in the following video:

../_images/Advanced5.png RflySim Advance Function: How to quickly perform software-in-the-loop simulation for one UAV

2.4. SIL Simulation for Multiple Vehicles

You can also start multiple SIL simulation system by the procedure in the following video:

../_images/Advanced6.png RflySim Advance Function: How to quickly perform software-in-the-loop (SIL) simulation for UAV swarm

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3. Other Types of Vehicles

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3.1. Other Multicopter Types, e.g. Hexacopter

RflySim also supports to simulate other types of multicopters. You only need to select a desired multicopter configuration in CopterSim, and set Pixhawk to specific multicopter control mode through QGC.

In the following video, we present the procedure to use RflySim to simulate a Hexacopter.

../_images/Advanced7.png RflySim Advance Function: How to simulate other types of multicopters

More detailed setting methods for other types of multicopters are presented below.

3.2. HIL Simulation for Other Types of Multicopters

In the previous courses, readers need to set up the Pixhawk autopilot through QGC to enter the “HIL Quadcopter X” airframe mode. This mode only supports the quadcopter X configuration, which has strong limitations in practical usage. In addition to quadcopters, CopterSim can be used to all multicopter types supported by the PX4 autopilot software. The specific steps are presented as follows.

(1). Select a multicopter airframe in QGC

1). Correctly connect the Pixhawk autopilot with the QGC.

2). Select a required multicopter airframe in the “Airframe” tab (see Fig.4.8), such as hexacopters, octocopters, coaxial multicopters, etc.

3). Select a corresponding airframe size from the drop-down list of the airframe (e.g., F450, and 3DR DIY Quad).

4). Confirm that the Pixhawk is in the selected airframe mode applying the airframe and restarting.

Through the above steps, readers can set an airframe type that can be used for the actual flight with controller parameters matching the airframe size.

../_images/Quan-app1-FigA.12.jpg Fig. 4.8 Choosing a required multicopter airframe in QGC

(2). Set the HIL simulation mode in QGC As shown in Fig.4.9, after the QGC is properly connected to the Pixhawk autopilot, in the “Safety” tab of QGC, set the “HITL Enabled” option to “Enabled” and then re-plug the Pixhawk autopilot. After the above steps, any airframe can be set to enter the HIL simulation mode.

../_images/Quan-app1-FigA.13.jpg Fig. 4.9 Setting “HITL Enabled” option to “Enabled”

(3). Configure multicopter model in CopterSim There are two methods to set the multicopter airframe type in CopterSim. The first method is to select from the “Frame Type” drop-down menu (see Fig.4.10a) on the CopterSim UI; the other method is to open the “Model Parameters” dialog to set the number of arms, the number of rotors, and the head orientation.

../_images/Quan-app1-FigA.14.jpg Fig. 4.10 Setting multicopter airframe in CopterSim

(4). Start HIL simulation Taking a hexacopter as an example, set the Pixhawk airframe type to a general hexacopter in QGC (see Fig.4.8); enable the HIL mode in QGC (see Fig.4.9); then, configure hexacopter parameters in CopterSim, as shown in Fig.4.10b. Next, insert the Pixhawk autopilot into the computer, select the Pixhawk serial port in CopterSim, and click “Start Simulation” button to start the HIL simulation for the hexacopter.

3.3. Other Vehicle Types, e.g., Fixed-Wing Aircraft

RflySim also supports to convert any vehicle model in Simulink to a DLL model file, and imports it to CopterSim to perform HIL simulation. In the following video, we present the procedure to convert the Simulink model of a fixed-wing aircraft to Coptersim for hardware-in-the-loop simulation.

../_images/Advanced8.png RflySim Advance Function: How to simulate other types of multicopters

More detailed setting methods for other types of vehicles are presented below.

3.4. HIL Simulations of Other Models

As shown in Fig.4.8, a Pixhawk autopilot supports not only multicopters, but also fixed-wing aircraft, vertical take-off and landing aircraft, rovers, boats, and other types of vehicle. To support all vehicle types supported by Pixhawk autopilots, CopterSim also provides an interface to import the Simulink model as DLL model files to perform HIL simulations.

(1). Use DLL model files in CopterSim As shown in Fig.4.11a, copy the DLL model file generated by Simulink to the folder “CopterSimexternalmodel”. After re-opening the CopterSim, readers can see all available DLL model files in the “Use DLL Model” drop-down list in Fig.4.11b. These DLL model files can be used to simulate any aircraft or vehicles. Select a DLL model, configure the Pixhawk autopilot to the desired airframe in QGC, and finally start HIL simulation in CopterSim.

../_images/Quan-app1-FigA.15.jpg Fig. 4.11 Select DLL model for simulation

(2). Method to generate DLL model file in Simulink As shown in Fig.4.12, open the Simulink source code folder “MulticopterModel” (obtained with the serial number), and open the desired “.slx” Simulink file (multicopter, aircraft, etc.) in it. Then, modify the model parameters or replace some of the modules in Simulink to meet the simulation model requirements. Next, click the “compile” button in Simulink to generate C/C++ code. Finally, run the “GenarateModelDLLFile” command in MATLAB to generate the DLL model file in “.dll” format and copy it to the folder shown in Fig.4.11.

../_images/Quan-app1-FigA.16.jpg Fig. 4.12 Simulink source code to generate DLL model file

Since Simulink uses modular programming methods, in the provided “.slx” file, it is easy to obtain different vehicle configurations by changing parameters or some modules. For example, the multicopter types presented in Fig.4.12 can be easily applied by modifying the airframe type parameter ModelParam_uavType in the “Init.m” initialization script (see Fig.4.13) to a corresponding value. The default multicopter configuration of the previous experiment was uavType = 3, which is the conventional X-shaped quadcopter. [1] [#f1]_

../_images/Quan-app1-FigA.17.jpg Fig. 4.13 Model corresponding to uavType parameter in Simulink model

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4. Customization of 3D Scenarios

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4.1. Design and Import 3D Scenarios

RflySim3D also support to design and import your own 3D scenes, the basic principle is listed as follows:

Create a 3D Scene in 3Ds Max (or imported from AutoCAD, SketchUp by fbx file) -> imported to UE4 -> imported to RlfySim3D Procedure: UE4 build and package project to files -> copy the scene folder to RflySim3D content folder -> Copy terrain files to CopterSim In the following video, the procedure to import a quadcopter 3D model from 3Ds Max is introduced.

../_images/Advanced9.png RflySim Advance Function: How to import your own 3D vehicle models to the UE4-based RflySim3D program

The following figures present the built-in high-fidelity 3D scenes in RflySim3D:

../_images/Advanced10.png ../_images/Advanced11.png The following video presents how to use Python to send vehicle position&trajectory to RflySim3D’s city night scene to observe the light show effect.

../_images/Advanced12.png RflySim Advance Function: How to use RflySim3D to simulate light show of UAV swarm flying at city night

4.2. Design and Import Vehicle 3D Models

RflySim3D also support to design and import your own 3D vehicle models, the basic principle is listed as follows:

Support to import all vehicle/target/people/obstacle in UE4, then RflySim3D will detect and import UE4 model file and XML configuration file Create a 3D model in 3Ds Max (or imported from AutoCAD, SketchUp by fbx file), then import it to UE4 with writing an XML file, and finally recognized by RlfySim3D In the following video, we present the procedure to import the 3D model of a quadcopter from 3Ds Max with the XML file from our template.

../_images/Advanced13.png RflySim Advance Function: How to import your own 3D vehicle models to the UE4-based RflySim3D program

The figures below present the build-in high-fidelity vehicle/car/people/target 3D models in RflySim3D.

../_images/Advanced14.png ../_images/Advanced15.png ../_images/Advanced16.png

=============================## 5. UAV Swarm Control

5.1. Distributed Simulation Framework

RflySim adopts totally distributed framework, you can extend to any number of computers, vehicles, observation views, etc. The basic software structure is presented in the figure below.

../_images/Advanced17.png The hardware structure is presented in the following figure.

../_images/Quan-app1-FigA.21.jpg

5.2. Key Problems and Solutions

Problem 1: it is ineffective to create simulated vehicles&Pixhawks one by one Solution: One-key script to start and initialize all programs and parameters Problem 2: How to display all vehicles in the same 3D program Solution: we use UDP network to broadcast vehicle states, and RflySim3D dynamically create vehicle 3D model when receiving new data. Users can also create other 3D models such as obstacle, people, tracking target, checker board . Problem 3: The network become congested when vehicle number is too large Solution: we have multiple communication protocols, simplified message can be applied when vehicle number is large to improve the real-time performance of communication. Problem 4: It is too costly and inefficient to perform large scale swarm simulation with Pixhawk hardware. Solution: we provide PX4 SITL simulation mode, under which the PX4 Autopilot software is running in the windows instead of Pixhawk hardware. Problem 5: How much vehicle can be simulated on one computer? Answer: the QGroundControl and RflySim3D occupy most of the computing resource, and the CopterSim + PX4 SILT only need few computing resources. For normal high-performance PCs, we can run at least 15 vehicles with CopterSim + PX4 SITL, and at least 30 vehicles with CopterSim + PX4 HITL. The number will increase if the QGroundControl, RflySim3D, and MATLAB are not running on this computer Problem 6: Simulink will significantly slow down when too much vehicles to be controlled, which may affect the real-time performance Solution: we provide script to compile Simulink controller to exe file, which can control large-scale UAV swarm simulation system with few computing resource Problem 7: How to ensure controller can work in real system as in simulation Solution 1: All vehicle data received by Simulink is the actual data from Pixhawk through Mavlink instead of ideal data from simulator, and the output of Simulink is also Mavlink message to Pixhawk. Solution 2: Our swarm communication interfaces ensure the Simulink can control actual UAV swarm system when each UAV is connected to the same LAN through WIFI or radio telemetry. User can also generate the Simulink to C/C++ code to developing a swarm ground control system. 5.3. Simulink Control Swarm on One Computer ../_images/Advanced18.png RflySim Advance Function: How to use Simulink to control UAV swarms in software-in-the-loop (SIL) simulation mode

5.4. Simulink Control Swarm on Multiple Computer

../_images/Advanced19.png RflySim Advance Function: How to quickly perform distributed software-in-the-loop simulation (SIL) for UAV swarm with multiple computer

5.5. Apply Control Algorithm to Real Swarm System

../_images/Advanced20.png RflySim Advance Function: How to quickly apply the UAV swarm control algorithms to real UAV systems for indoor flight tests

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6. UAV Vision/AI Control

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6.1. Key Problems and Solutions

Problem 1: How to capture images from UE4-based program RflySim3D with high frame rate Solution: we use Python/C/Simulink to directly read screen images from windows API which is independent from RflySim3D, so our interface will not slow down the efficiency of RflySim3D, and we can read the images with a very high frame rate (within 5ms, more than 200Hz ) outside the RflySim3D Problem 2: How to obtain multiple camera views in the same time Solution: users can open multiple RflySim3D windows to display different views. Problem 3: How to change the image size, camera position and angle, and select cameras on the desired vehicles. Solution: users can set these parameters through mouse and keyboard, or send commands through our UDP interface Problem 4: How to ensure the algorithm can run successfully on real vehicles？ Solution: Our programming language is Python (we will support MATLAB soon) which is cross-platform, and our communication interface is based on Mavlink which can be processed by Pixhawk directly. So the algorithms can run on onboard computer without modification

6.2. Control with Monocular Camera

../_images/Advanced21.png RflySim Advance Function: How to use Python/OpenCV to perform vision-based control of a multicopter UAV

6.3. Control with Binocular Camera

../_images/Advanced22.png RflySim Advance Function: How to perform binocular vision control and apply to real multicopter system

6.4. Apply Vision Algorithm

We also provide a serial of multicopter vision flight platform to ensure algorithm can be successfully applied to real vehicle systems.

../_images/Advanced23.png

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Future Plan

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RflySim provide a unified solution for development, test and assessment of unmanned control systems, and we have more wonderful features are coming soon:

1. More high-fidelity 3D scenes and vehicle models will be released on our website with control demos for users.

2. More sensors will be supported, e.g., Lidar, depth cameras.

3. Simulink interface for computer vision and machine learning, so users can train their vehicle control algorithms on RflySim

4. More types of vehicle to be supported, e.g., driverless cars, fixed-wing aircraft, VTOL, unmanned boat, etc.

5. Standard modeling module database to quickly develop vehicle model

6. More experimental courses will be released on our website Notes

PDF base-code

lesson	pdf links	code links
Lesson 01:	Introduction [pdf](pdf/gcs/rfly_code/	RflySim_Lesson_01_Introduction.pdf)	*
Lesson 02:	Flight Control Experiments pdf	*
Lesson 03:	External Control Interface pdf	*
Lesson 04:	Other Types of Vehicles pdf	*
Lesson 05:	UE4 3D Scene Development pdf	*
Lesson 06:	Vision Based Control pdf	*
Lesson 07:	UAV Swarm Control pdf	*
		*
Lesson01: Course Introduction.	:download:pdf	*
Lesson02: Experimental Platform Configuration.	:download:`pdf	*
Lesson03: Experimental Platform Usage.	:download:pdf	:download:e0
Lesson04: Experimental Process.	:download:pdf	*
Lesson05: Exp.1 Propulsion System Design.	:download:pdf	:download:e1
Lesson07: Exp.3 Sensor Calibration.	:download:pdf	:download:e3
Lesson08: Exp.4 State Estimation and Filter Design.	:download:pdf	:download:e4
Lesson09: Exp.5 Attitude Controller Design.	:download:pdf	:download:e5
Lesson10: Exp.6 Set-Point Controller Design.	:download:pdf	:download:e6
Lesson11: Exp.7 Semi-autonomous Control Mode Design.	:download:pdf	:download:e7
Lesson12: Exp.8 Failsafe Logic Design.	:download:pdf	:download:e8
		*

course contents overview source_code

[1] These configurations correspond to the multicopter models supported by the PX4 autopilot. Readers can refer to the official website: http://dev.px4.io/master/en/airframes/airframe_reference.html.