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). 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. If you want to be even more organized, create subclasses in your file to separate different components. This can help slow down the robot around tight turns. Characterization works best if you are using feedback on the RoboRIO, rather than a motor controller like a Talon SRX, Talon FX, or Spark MAX. For the purposes of our example, the robot will be reliably starting at a position of (0,0) with a heading of 0. If all has gone well, your robots autonomous routine should look something like this: Copyright 2022, FIRST and other WPILib Contributors. There are two main ways for feedback parameters on the robot. For this reason, your robot should be able to drive fairly accurately with only kF (which will be mentioned later). This is very important, as the feedback gains will not be in the correct units if we do not select the correct preset: Finally, we calculate and record the feedback gains for our control loop. All you need is a function that takes in parameters and returns a Command. We begin by gathering our drive identification data. 9 #include <wpi/SymbolExports.h> 10. . First, we must set some configuration parameters for the trajectory which will ensure that the generated trajectory is followable. Our current plan for the production robot is to use REV Robotics Spark Max motor controllers with NEO motors, so we will have to do conversions to their native units rather than the Talon SRX ones, but other than that the idea is the same. 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. Is the RamseteCommand a Command itself? WPILib Programming Basics# Making FRC Programming Easy. Now that we have a trajectory, we can create a command that, when executed, will follow that trajectory. WPILib Example Projects; Trajectory Tutorial. We will first reset our robots pose to the starting pose of the trajectory. And the best thing is that I have already written one that you can use, based on the code from WPILib. Revision 59195b9c. 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. 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. If they are not, it is possible you specified one of your drive parameters incorrectly when generating your robot project. The robot drive: This is the drive subsystem itself, included to ensure the command does not operate on the drive at the same time as any other command that uses the drive. We had been talking for a while that we wanted to do path-planning in 2020, and we began work in the off-season. 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. For this reason, you need to figure out the parameters for your control loop. Generate a simple trajectory through a set of waypoints using WPILib's, Follow the generated trajectory in an autonomous routine using WPILib's. The command-based framework is strongly recommended for beginning and intermediate teams. 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. 3 // the WPILib BSD license file in the root directory of this project. 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. It can be helpful to understand some of the components of this code: TIP: Having debugging in the RamseteController can be a live-saver down the line, because you can see the errors (eX, eY, eTheta) that the calculator sees. 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. WPILib Examples and Tutorials. 6. 127 * start pose of the other trajectory match (if that is the desired behavior). 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). You signed in with another tab or window. You may have seen before that there are some functions that have conversion factors as one of their parameters. 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. Feedback gains do not, in general, transfer across robots. Do not use the gains from this tutorial for your own robot. 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. Instead of generating the trajectory on the roboRIO as outlined above, one can also import a PathWeaver JSON. Accurately characterize their robot's drivetrain to obtain accurate feedforward calculations and approximate feedback gains. Having your own class that extends will make your life a million times easier. 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. Feedforward gains do not, in general, transfer across robots. For the sake of ease for users, a RamseteCommand class is built in to WPILib. 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. Projects range from simple demonstrations of a single functionality to complete, competition-capable robot programs. This is full tutorial for implementing trajectory generation and following on a differential-drive robot. One is a PIDF controller, which should be used if you are using a motor controller for feedback (Talon SRX, Talon FX, Spark MAX). Once the identification routine has been run and the data file has been saved, it is time to open it in the analysis pane. Configure a drive subsystem to track the robots pose using WPILibs odometry library. 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). Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Step 2: Entering the Calculated Constants, Step 4: Creating and Following a Trajectory. Step 2: Entering the Calculated Constants, Step 4: Creating and Following a Trajectory. 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 `. If you wish to use a trajectory that has been defined in robot-centric coordinates in such a situation, you can transform it to be relative to the robots current pose using the transformBy method (Java, C++). We used a new Command Subsystem structure (starting 2020) for our project. The constants defined in the Romi trajectory project were based off a stock Romi kit with no additional components. The full robot code for this tutorial can be found in the RamseteCommand Example Project (Java, C++). The values returned will be voltage control constants. The kF feedforward value is added to the result, regardless of error. I think that having an understanding of the internals helps with getting the best performance out of wpilib trajectories. The other options are voltage feedback, which should be used if you are doing controls with a RoboRIO. // Reset odometry to the starting pose of the trajectory. If you have problems, I would recommend looking at the WPILib Trajectory Tutorial, WPILib JavaDoc, or Chief Delphi. Follow the generated trajectory in an autonomous routine using WPILib's RamseteCommand class with the calculated feedforward/feedback gains and pose. All of these examples are available in VS Code by entering Ctrl+Shift+P, then selecting WPILib: Create a new project and choosing example. What is the resolution of the encoders I am using? Some questions to ask yourself are: WPILib Trajectory relies on feedback to ensure that the drivetrain drives accurately. 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. For Advanced Users Built in odometry, computer vision (OpenCV) pipelines, WPILib Trajectory and more at your disposal. Are all of the motor controller and feedback parameters set properly? 126 * responsible for making sure that the end pose of this trajectory and the. 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. 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. WPILib Trajectory is based the recommended way for pathfinding starting in 2020. (A follower motor [like a Victor SPX] following the actions of a master [like a Talon SRX]). * @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. Hardware - Basics; Hardware Tutorials; Sensors; Robot . Configure a drive subsystem to track the robot's pose using WPILib's odometry library. . pose - The pose that is the origin of the coordinate frame that the current trajectory will be transformed into. I am not going to go over the details of it, but FRC 4915 has a great video explaining how it works. 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. 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. If we were to implement it in a command, what would we put in each function? 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. 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. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. 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 full code used in this tutorial can be found in the RamseteCommand example project (Java, C++). Thus, our calculated gain means that, for each meter per second of velocity error, the controller will output an additional 3.38 volts. 2. I would recommend starting with a straight line test, then adding curves later. 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. Are all of the sensors set to the correct inversion (sensor phase)? The full method from the RamseteCommand Example Project (Java, C++) can be seen below. 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. The last step is to test, and see if everything works. As elsewhere, all distances are in meters. With our drive subsystem written, it is now time to generate a trajectory and write an autonomous command to follow it. 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. Configuring the Trajectory Constraints First, we must set some configuration parameters for the trajectory which will ensure that the generated trajectory is followable. This value should agree very closely with the kV measured by the tool - if it does not, you have likely made an error somewhere. What is the gearing ratio from the encoder to the wheel? Are you sure you want to create this branch? In order to keep your code organized and configuration simple, it can be very helpful to have a file that tracks all constants. 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. 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). The headings are automatically determined at the interior points to ensure continuous curvature. Contribute to mcm001/frc-docs development by creating an account on GitHub. I want show how trajectory generation and following actually happen. 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. 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. I've been working through the Trajectory Generation Tutorial from WPILib and I have hit a snag. Be sure to have at least a 10 stretch (ideally closer to 20) in which the robot can drive during the identification routine. The output consumer: This is a method reference (or lambda) to the drive subsystem method that passes the voltage outputs to the drive motors. Most of the code should be self-documenting, but there will be commentary throughout explaining what is going on. Learn more Insight The FTCLib FTCLib is the FTC library to end all libraries. I wont go over what each value does, but you can find it in CTRE documentation. This tutorial is intended to be approachable for teams without a great deal of programming expertise. 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. getTurnRate() returns the active rate at which the robot is turning, which is used for accounting for error in Trajectory. WPILib Released 2021.3.1! The Talon SRX can be controlled over the CAN bus or PWM interface. 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. toctree:: :maxdepth: 1 trajectory-tutorial-overview characterizing-drive entering-constants creating-drive-subsystem creating-following-trajectory For detailed instructions on using the System Identification tool, see its dedicated documentation. Generate a simple trajectory through a set of waypoints using WPILib's TrajectoryGenerator class. If you dont have a project, open VS Code for your year, press CTRL + SHIFT + P at the same and create a new project. If not, click here to continue. Is there any way to get the NavX to work inside of the DifferenetialDriveOdometry Class? 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. 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. 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. Before following this tutorial, it is helpful (but not strictly necessary) to have a baseline familiarity with WPILibs PID control, feedforward, and trajectory features. 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). A driver-station computer configured with. WPILib includes a set of predefined constraints that users can utilize when generating trajectories. 5 #pragma once. 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. The RAMSETE controller needs the current pose measurement to determine the required wheel outputs. The robot code in this tutorial uses the :ref:`command-based ` framework. Are all of the motors set to the correct inversion? The first piece of configuration we will need is a voltage constraint. There is good documentation on how to use the wpilib trajectory generator, but little documentation on how it works. 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. * 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? 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. A Pose2d is an object that contains information about where the robot is, which the RamseteController will use for calculations. 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). A PIDF controller needs four main values: These values will all be factored into the computation. This tutorial is intended to be approachable for teams without a great deal of programming expertise. There are classes to handle sensors, motor speed controllers, the driver station, and a number of other utility functions. 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 is useful for converting a field-relative trajectory into a robot-relative trajectory. 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