The steps to tune are: There are some things to make sure are set properly if you are encountering issues with your characterization process: Now you need to make your robot project. I want show how trajectory generation and following actually happen. Your motor controllers and gyroscope/IMU should be instance variables that are initialized in the constructor. WPILib example projects demonstrate a large number of library features and use patterns. Having a function that can generate trajectories means that you can feed any set of points into your path planner and have it work. The kF feedforward value is added to the result, regardless of error. Are all of the sensors set to the correct inversion (sensor phase)? For this reason, you need to figure out the parameters for your control loop. In 2019, we decided to call off attempts at autonomous code in order to prioritize state machines and vision-based navigation (which we did not have enough time to put on the production robot). Before accurately following a path with a robot, it is important to have an accurate model for how the robot moves in response to its control inputs. 9 #include <wpi/SymbolExports.h> 10. . It is very important that the initial robot pose match the first pose in the trajectory. I've been working through the Trajectory Generation Tutorial from WPILib and I have hit a snag. Historically, the most common solution for this sort of task in FRC has been a "drive-turn-drive" approach - that is, drive forward by a known distance, turn by a known angle, and drive forward by another known distance. I am not going to go over the details of it, but FRC 4915 has a great video explaining how it works. The information about how to characterize the robot is below: Introduction to Robot Characterization FIRST Robotics Competition documentation. Determining such a model is a process called system identification. WPILibs System Identification tool can accurately determine such a model. The best way to start off is to learn your robot. drive subsystem method that returns the pose, drive subsystem method that returns the wheel speeds, drive subsystem method that passes the voltage outputs to the drive motors, Step 2: Entering the Calculated Constants, Step 4: Creating and Following a Trajectory. You signed in with another tab or window. Once the identification routine has been run and the data file has been saved, it is time to open it in the analysis pane. While the "drive-turn-drive" approach is certainly functional, in recent years teams have begun tracking smooth trajectories which require the robot to drive and turn at the same time. Regardless of whether All Users or Current User is chosen, the software is installed to C:\Users\Public\wpilib\YYYY where YYYY is the current FRC year. A short excerpt of our Constants.java file is below: After you have your vendor libraries, it is time to create a Subsystem with all of the configurations set. Remember: you can set your waypoints in RobotContainer.java like so: Another good tool, especially for the straight line, is using blue painters tape. This tutorial is intended to be approachable for teams without a great deal of programming expertise. You may need to tweak values a little to compensate for physical differences between the Romis, or better yet, characterize your own! The full code used in this tutorial can be found in the RamseteCommand example project ( Java, C++ ). // An example trajectory to follow. Trajectory Tutorial This is full tutorial for implementing trajectory generation and following on a differential-drive robot. We will first reset our robots pose to the starting pose of the trajectory. The full method from the RamseteCommand Example Project (Java, C++) can be seen below. Are you sure you want to create this branch? Accurately characterize their robot's drivetrain to obtain accurate feedforward calculations and approximate feedback gains. This gives us some headroom to deal with voltage sag during operation. We now record the feedforward gains calculated by the tool: Since our wheel diameter was specified in meters, our feedforward gains are in the following units: If you have specified your units correctly, your feedforward gains will likely be within an order of magnitude of the ones reported here (a possible exception exists for kA, which may be vanishingly small if your robot is light). The full code used in this tutorial can be found in the RamseteCommand example project (Java, C++). Now you have an autonomous path! Your configuration for each motor will depend on what motor controllers you use, but an example for a drivetrain with two Talon SRX motor controllers is below: As you can see, we set everything to values from Constants.java, so if we ever need to change something, we can easily find it there rather than searching through the untidy configuration code. 2. Generate a simple trajectory through a set of waypoints using WPILib's, Follow the generated trajectory in an autonomous routine using WPILib's. Most of the code should be self-documenting, but there will be commentary throughout explaining what is going on. If all has gone well, your robots autonomous routine should look something like this: Copyright 2022, FIRST and other WPILib Contributors. Feedforward gains do not, in general, transfer across robots. Trajectory Tutorial Overview Step 1: Characterizing Your Robot Drive Step 2: Entering the Calculated Constants FRC|reg| games often feature autonomous tasks that require a robot to effectively and accurately move from a known starting location to a known scoring location. With our drive subsystem written, it is now time to generate a trajectory and write an autonomous command to follow it. The transformed trajectory. Now that we have a trajectory, we can create a command that, when executed, will follow that trajectory. All units in meters. It turns a set of waypoints or an initial guess trajectory into a time optimal trajectory This eliminates a lot of hassle with waypoint heading adjustments in quintic splines, and supports keep-out zones Requires constraints based on an accurate model to be useful for high performance (same as our current approach with splines) Generate a simple trajectory through a set of waypoints using WPILib's TrajectoryGenerator class. I am not going to go over the details of it, but FRC 4915 has a great video explaining how it works. Cannot retrieve contributors at this time, :ref:`PID control `, :ref:`feedforward `, :ref:`trajectory `, :ref:`command-based `, :ref:`FRC Driver Station `, :ref:`WPILib `, :ref:`The System Identification Toolsuite `. This is where keeping track of your conversions matter. 7 #include <vector> 8. To do this, we use the RamseteCommand class (Java, C++). (e.g. For more information about transforming trajectories, see Transforming Trajectories. Configure a drive subsystem to track the robots pose using WPILibs odometry library. There are two main ways for feedback parameters on the robot. The constants defined in the Romi trajectory project were based off a stock Romi kit with no additional components. don't have overlapping packages, like wpilibj having classes in first.wpi.math) Improving error reporting in HAL General Revision 59195b9c. We used a new Command Subsystem structure (starting 2020) for our project. Are the SmartDashboard values updating to the motor controllers? FRC Java Tutorial - WPILib 2022 Command Based Programming Ep 1: Gentle Introduction & Installation - YouTube Basic introduction to what WPILib is, how it works, and how to install it. Quadrature encoders for measuring the wheel rotation of each side of the drive. 3 // the WPILib BSD license file in the root directory of this project. I think that having an understanding of the internals helps with getting the best performance out of wpilib trajectories. The tape allowed me to see that there was a slight turn to the left while driving, which a tiny bit more tuning was able to fix. One of our projects for the start of Build Season was learning the WPILib Trajectory feature which acts as a path planning and following library. 6. First, we must set some configuration parameters for the trajectory which will ensure that the generated trajectory is followable. Now that we have our voltage constraint, we can create our TrajectoryConfig instance, which wraps together all of our path constraints: With our trajectory configuration in hand, we are now ready to generate our trajectory. Feedback gains do not, in general, transfer across robots. These parameters will be involved in calculations to ensure reliable driving, so it is important to make sure that you put the proper values in. The command-based framework is strongly recommended for beginning and intermediate teams. Set a velocity to a realistic value (I chose 3000 ticks/100ms which was slow but visible for the robot we tested on), Gradually increase kF until the sensor velocity is very close to the desired velocity, Change the velocity, and re increase kF until it is close, Change the velocity again, and add a tiny bit of kP, Change the velocity, change kP (usually initially by a factor of 10, make smaller later) until it gets very close to the desired velocity without overshooting, If stability remains an issue, try adding a very tiny amount of kD, Test different velocity setpoints and see how close it can get to the setpoint. For this example, we will be generating a clamped cubic trajectory - this means we will specify full robot poses at the endpoints, and positions only for interior waypoints (also known as knot points). Since it is a velocity controller, only a P gain is required: Assuming we have done everything correctly, our proportional gain will be in units of Volts * Seconds / Meters. The list of WPILib-provided constraints is as follows: CentripetalAccelerationConstraint: Limits the centripetal acceleration of the robot as it traverses along the trajectory. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. // Run path following command, then stop at the end. The full robot code for this tutorial can be found in the RamseteCommand Example Project (Java, C++). Revision 59195b9c. This is useful for converting a field-relative trajectory into a robot-relative trajectory. While the WPILib library offers significant flexibility in the manner in which its trajectory-following features are implemented, closely following the implementation outlined in this tutorial should provide teams with a relatively-simple, clean, and repeatable solution for autonomous movement. In order to keep your code organized and configuration simple, it can be very helpful to have a file that tracks all constants. Follow the generated trajectory in an autonomous routine using WPILib's RamseteCommand class with the calculated feedforward/feedback gains and pose. By following this tutorial, readers will learn how to: Accurately characterize their robots drivetrain to obtain accurate feedforward calculations and approximate feedback gains. Due to the responsibilities of the Software sub-team in preparing a robot for CalGames and Madtown ThrowDown, path planning work primarily ended up occurring in the holiday break, and took a long time to get ready. A Pose2d is an object that contains information about where the robot is, which the RamseteController will use for calculations. The way we tuned this is by writing a simple app that has kP, kI, kD, kF, and Velocity for configuration on SmartDashboard, as well as the active sensor velocity and error for plotting. kF plays the role of keeping the robot on track, while kP, kI, and kD all play into error correction. Trajectory Tutorial. This method uses clamped cubic splines -- a method in which the initial pose, final pose, and interior waypoints are provided. Having your own class that extends will make your life a million times easier. It is based off of the 254 2018 autonomous and significantly reduces the computation time associated with path planning as well as accuracy. The RAMSETE controller: This is the RamseteController object (Java, C++) that will perform the path-following computation that translates the current measured pose and trajectory state into a chassis speed setpoint. This value should agree very closely with the kV measured by the tool - if it does not, you have likely made an error somewhere. Before following this tutorial, it is helpful (but not strictly necessary) to have a baseline familiarity with WPILibs PID control, feedforward, and trajectory features. FRC Java Tutorial - WPILib 2022 Command Based Programming Ep 3:Autonomous Trajectory & Path Planning 161 views Jul 27, 2022 6 Dislike Share Save Team2059 91 subscribers Learn how to program. Final release of the season Going to finish up work on main and then push 2022 alpha without breaking changes 2022 wpimath package moves: should we be aiming for Jigsaw compatibility? This is full tutorial for implementing trajectory generation and following on a differential-drive robot. WPILib includes a set of predefined constraints that users can utilize when generating trajectories. Thus, our calculated gain means that, for each meter per second of velocity error, the controller will output an additional 3.38 volts. Historically, the most common solution for this sort of task in FRC has been a drive-turn-drive approach - that is, drive forward by a known distance, turn by a known angle, and drive forward by another known distance. FRC Java Tutorial - WPILib 2019 Command Based Framework Ep 1: Overview 22,691 views Feb 2, 2019 399 Dislike Share Save Manning Robotics 512 subscribers Discussing the architecture and walking. All you need is a function that takes in parameters and returns a Command. The rest of the article will break down the different parts of the method in more detail. Instead of generating the trajectory on the roboRIO as outlined above, one can also import a PathWeaver JSON. To follow this tutorial, you will need ready access to the following materials: A tag already exists with the provided branch name. A Voltage controller needs three main values: FRC Characterization is an app from WPILib that lets you run software on your robot to identify the proper values for your robot. The goal of this tutorial is to provide end-to-end instruction on implementing a trajectory-following autonomous routine for a differential-drive robot. This makes sure that you know exactly what you are controlling. These functions, including our implementations, are below (note that some of the conversion factors will be added later). getTurnRate() returns the active rate at which the robot is turning, which is used for accounting for error in Trajectory. Learn more Insight The FTCLib FTCLib is the FTC library to end all libraries. If you dont have a project, open VS Code for your year, press CTRL + SHIFT + P at the same and create a new project. * @return the command to run in autonomous, // Create a voltage constraint to ensure we don't accelerate too fast, // Add kinematics to ensure max speed is actually obeyed. All of these examples are available in VS Code by entering Ctrl+Shift+P, then selecting WPILib: Create a new project and choosing example. 5 #pragma once. Contribute to mcm001/frc-docs development by creating an account on GitHub. The tutorial and example code call for the use of a ADRXS450 Gyro for angle measurements, but my team is using a NavX-MXP for our gyro. What is the gearing ratio from the encoder to the wheel? A driver-station computer configured with: Copyright 2022, FIRST and other WPILib Contributors. Trajectory following with WPILibs RAMSETE controller uses velocity closed-loop control, so we first select Velocity mode in the identification tool: Since we will be using the WPILib PIDController for our velocity loop, we furthermore select the WPILib (2020-) option from the drop-down presets menu. While the drive-turn-drive approach is certainly functional, in recent years teams have begun tracking smooth trajectories which require the robot to drive and turn at the same time. In actual use, however, it is probably not desirable to base your coordinate system on the robot position, and so the starting position for both the robot and the trajectory should be set to some other value. WPILib Example Projects; Trajectory Tutorial. It is based off of the 254 2018 autonomous and significantly reduces the computation time associated with path planning as well as accuracy. Copyright 2022, FIRST and other WPILib Contributors. Beginning in 2020, WPILib now supplies teams with working, advanced code solutions for trajectory generation and tracking, significantly lowering the "barrier-to-entry" for this kind of advanced and effective autonomous motion. The right-side PIDController: This is the PIDController object (Java, C++) that will track the right-side wheel speed setpoint, using the P gain that we obtained from the drive identification tool. Trajectory following with WPILib's RAMSETE controller uses velocity closed-loop control, so we first select Velocity mode in the identification tool: Since we will be using the WPILib PIDController for our velocity loop, we furthermore select the WPILib (2020-) option from the drop-down "presets" menu. You should have been redirected. toctree:: :maxdepth: 1 trajectory-tutorial-overview characterizing-drive entering-constants creating-drive-subsystem creating-following-trajectory Configuring the Trajectory Constraints First, we must set some configuration parameters for the trajectory which will ensure that the generated trajectory is followable. I highly recommend you look over it, even though you dont need to know the details, because it is fascinating. This can help slow down the robot around tight turns. The Talon SRX can be controlled over the CAN bus or PWM interface. One is a PIDF controller, which should be used if you are using a motor controller for feedback (Talon SRX, Talon FX, Spark MAX). Do I have a master-follower setup on my drivetrain? The drivetrain needs some methods in order to be able to drive. Put sample points into your generation function, and see if it drives. If you want to be even more organized, create subclasses in your file to separate different components. For the sake of ease for users, a RamseteCommand class is built in to WPILib. The command-based framework is strongly recommended for beginning and intermediate teams. Follow the generated trajectory in an autonomous routine using WPILib's RamseteCommand class with the calculated feedforward/feedback gains and pose. We tried to get Jaci Pathfinder working in the past, but unreliable robots combined with a lack of control systems experience meant that it never took off. 127 * start pose of the other trajectory match (if that is the desired behavior). Generate a simple trajectory through a set of waypoints using WPILib's TrajectoryGenerator class. // Start at the origin facing the +X direction, // Pass through these two interior waypoints, making an 's' curve path, // End 3 meters straight ahead of where we started, facing forward, // RamseteCommand passes volts to the callback. Per the system identification guide, we first view the diagnostics to ensure that our data look reasonable: As our data look reasonably linear, and the fit metrics are within acceptable parameters, we proceed to the next step. Before following this tutorial, it is helpful (but not strictly necessary) to have a baseline familiarity with WPILib's :ref:`PID control `, :ref:`feedforward `, and :ref:`trajectory ` features. The drive identification process requires ample space for the robot to drive. Is the RamseteCommand a Command itself? The version below is a slightly modified version from the WPILib Docs: This code block takes an initial waypoint (Pose2d start), intermediate waypoints(List waypoints), and an end way-point (Pose2d end). The drive kinematics: This is the DifferentialDriveKinematics object (Java, C++) that we constructed earlier in our constants file, and will be used to convert chassis speeds to wheel speeds. We had been talking for a while that we wanted to do path-planning in 2020, and we began work in the off-season. The drive feedforward: This is a SimpleMotorFeedforward object (Java, C++) that will automatically perform the correct feedforward calculation with the feedforward gains (kS, kV, and kA) that we obtained from the drive identification tool. WPILib Trajectory is based the recommended way for pathfinding starting in 2020. There are classes to handle sensors, motor speed controllers, the driver station, and a number of other utility functions. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. To follow this tutorial, you will need ready access to the following materials: A differential-drive robot (such as the AndyMark AM14U4), equipped with: Quadrature encoders for measuring the wheel rotation of each side of the drive. 126 * responsible for making sure that the end pose of this trajectory and the. On my first linear test, I told the robot to go nine feet forward, measured exactly nine feet with a tape measure, and put blue tape. WPILib Programming Basics# Making FRC Programming Easy. // Reset odometry to the starting pose of the trajectory. The full robot code for this tutorial can be found in the RamseteCommand Example Project (Java, C++). WPILib Examples and Tutorials. Finally, note that we append a final stop command in sequence after the path-following command, to ensure that the robot stops moving at the end of the trajectory. Creating a Voltage Constraint The first piece of configuration we will need is a voltage constraint. The headings are automatically determined at the interior points to ensure continuous curvature. For both Jaci Pathfinder and WPILib Trajectory, we did feedback using a PID loop on the motor controllers, so we did not use the voltage controls (which will be mentioned later on). I decided on January 6 to reevaluate path-planning from scratch using WPILib Trajectory, and got a working version much faster than Jaci Pathfinder. getWheelSpeeds() returns the current velocity of the drivetrain in WPILib units, resetOdometry() will reset all of the information about the robot being used in the Trajectory calculations from a given Pose2d, tankDriveVolts() will drive a tank drive (like a West Coast Drive) using volts (for RoboRIO Feedback) and tankDriveVelocity() will drive the robot using velocity closed-loop, resetEncoders() will reset the value of all of the encoders so that they dont affect running different paths, getAverageEncoderDistance() takes the mean of the encoder distances, which can be helpful for running the unicycle controller (which bases calculations based off of the center line), zeroHeading() will reset the gyroscope or IMU, so that Trajectory can have a clean slate for calculating angle, getHeading() will return the heading on a 0-360 scale (due to Math.IEEEremainder()) in degrees. This makes it super easy to find the values for your motor controller PID loop. If not, click here to continue. In the Trajectory Tutorial https://docs.wpilib.org/en/stable/docs/software/examples-tutorials/trajectory-tutorial/creating-following-trajectory.html, the technique . If you have problems, I would recommend looking at the WPILib Trajectory Tutorial, WPILib JavaDoc, or Chief Delphi. Configure a drive subsystem to track the robot's pose using WPILib's odometry library. Is there any way to get the NavX to work inside of the DifferenetialDriveOdometry Class? This tutorial is intended to be approachable for teams without a great deal of programming expertise. By following this tutorial, readers will learn how to: This tutorial is intended to be approachable for teams without a great deal of programming expertise. Hopefully this helps more teams learn about the joys of trajectory following, on a smaller scale. The first piece of configuration we will need is a voltage constraint. This article is going to outline the steps that my team took to get from nothing to working path-following using WPILib Trajectory. (A follower motor [like a Victor SPX] following the actions of a master [like a Talon SRX]). For Advanced Users Built in odometry, computer vision (OpenCV) pipelines, WPILib Trajectory and more at your disposal. * Use this to pass the autonomous command to the main {@link Robot} class. Does it make sense for us to control on the motor controller or RoboRIO? Hardware - Basics; Hardware Tutorials; Sensors; Robot . The other option, which works better for motor-controller based autonomous is to tune your own PID. The output consumer: This is a method reference (or lambda) to the drive subsystem method that passes the voltage outputs to the drive motors. pose - The pose that is the origin of the coordinate frame that the current trajectory will be transformed into. Do not use the gains from this tutorial for your own robot. The goal of this tutorial is to provide "end-to-end" instruction on implementing a trajectory-following autonomous routine for a differential-drive robot. I wont go over what each value does, but you can find it in CTRE documentation. This ensures that the robots location on the coordinate system and the trajectorys starting position are the same. A good test for this is to calculate the theoretical value of kV, which is 12 volts divided by the theoretical free speed of your drivetrain (which is, in turn, the free speed of the motor times the wheel circumference divided by the gear reduction). The last step is to test, and see if everything works. WPILib Trajectory is based the recommended way for pathfinding starting in 2020. . We begin by gathering our drive identification data. This will ensure that the generated trajectory never commands the robot to go faster than it is capable of achieving with the given voltage supply: Notice that we set the maximum voltage to 10V, rather than the nominal battery voltage of 12V. Everything up to now, besides PID tuning, has been off-robot and very theoretical. While this is a fundamentally more-complicated technical task, it offers significant benefits: in particular, since the robot no longer has to stop to change directions, the paths can be driven much faster, allowing a robot to score more game pieces during the autonomous period. There is good documentation on how to use the wpilib trajectory generator, but little documentation on how it works. What is WPILib# The WPI Robotics library (WPILib) is a set of software classes that interfaces with the hardware and software in your FRC RoboRIO. Much of my increase in speed was due to my recent experience with Jaci Pathfinder. WPILib Released 2021.3.1! As elsewhere, all distances are in meters. Do not use the gains from this tutorial for your own robot. And the best thing is that I have already written one that you can use, based on the code from WPILib. My team has struggled with path-following for a long time. Are all of the motors set to the correct inversion? For example, the trajectory tutorial touches on it, and even has you make a full drive subsystem, but then the RamseteCommand is made directly in GetAutonomousCommand instead of having it be done in a separate command class. With our Command-based Framework, your robot code will be clean, extensible and easy to re-use from season to season. This declaration is fairly substantial, so well go through it argument-by-argument: The trajectory: This is the trajectory to be followed; accordingly, we pass the command the trajectory we just constructed in our earlier steps. While the WPILib library offers significant flexibility in the manner in which its trajectory-following features are implemented, closely following the implementation outlined in this tutorial should provide teams with a relatively-simple, clean, and repeatable solution for autonomous movement. Be sure to have at least a 10 stretch (ideally closer to 20) in which the robot can drive during the identification routine. This. Revision 59195b9c. Step 2: Entering the Calculated Constants, Step 4: Creating and Following a Trajectory. Better FRC documentation using ReadTheDocs. The left-side PIDController: This is the PIDController object (Java, C++) that will track the left-side wheel speed setpoint, using the P gain that we obtained from the drive identification tool. It usually is a good idea to start of by adding any vendor libraries that are needed. Follow the generated trajectory in an autonomous routine using WPILibs RamseteCommand class with the calculated feedforward/feedback gains and pose. The wheel speed supplier: This is a method reference (or lambda) to the drive subsystem method that returns the wheel speeds. You may have seen before that there are some functions that have conversion factors as one of their parameters. What is the resolution of the encoders I am using? In this post, I will cover what we did to achieve path planning using WPILib Trajectory. For detailed instructions on using the System Identification tool, see its dedicated documentation. Adding vendor libraries early on will allow you to have autocomplete throughout the entire testing process. The Ramsete Controller is a trajectory tracker that is built in to WPILib. Note. Are all of the motor controller and feedback parameters set properly? Beginning in 2020, WPILib now supplies teams with working, advanced code solutions for trajectory generation and tracking, significantly lowering the barrier-to-entry for this kind of advanced and effective autonomous motion. The robot code in this tutorial uses the :ref:`command-based ` framework. The values returned will be voltage control constants. Some questions to ask yourself are: WPILib Trajectory relies on feedback to ensure that the drivetrain drives accurately. We added Phoenix for our project, since CTRE devices were the only non-WPILib-supported devices on our minibot test-bed. For a full tutorial on implementing a path-following autonomous using RamseteCommand, see . By creating functions with our conversions, it is very clear what we are doing, and we can change all of our logic in one place if we do not write implement a conversion properly. Our conversion is fairly simple to see, such as below (at the time of writing, the JavaDoc comments were not done for the project, which is why some methods are missing a JavaDoc comment): Make sure that everything is in the correct units throughout the entire process, and conversion factors for a Spark MAX/NEO will be different. I would recommend starting with a straight line test, then adding curves later. Projects range from simple demonstrations of a single functionality to complete, competition-capable robot programs. The pose supplier: This is a method reference (or lambda) to the drive subsystem method that returns the pose. Generate a simple trajectory through a set of waypoints using WPILibs TrajectoryGenerator class. 4. In this test (which was my first with the auto and used a straight line), the back of the robot shouldve lined up with the blue tape, and it got very close. The identification data for this tutorial has been generously provided by Team 5190, who generated it as part of a demonstration of this functionality at the 2019 North Carolina State University P2P Workshop. A PIDF controller needs four main values: These values will all be factored into the computation. The other options are voltage feedback, which should be used if you are doing controls with a RoboRIO. 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