Thusly, it takes in a command via the cmd_vel topic and produces a smoothed output on smoothed_cmd_vel. Is this what you also had in mind? I don't think that should be the default behavior but I'd be fine with that a parameterized option. If your timer runs at a constant rate, why not use that for, Overall, maybe the ruckig library would be nice to use, this should also smooth based on jerk as well (ideally) though we don't have input measurements of acceleration so I'm not sure we should try to attempt it. Do you think we should include jerk for the commanded velocity mode? After the bulk is in place, adding a couple new parameters and a new constraint would be a trivial PR to review and merge. See inline description of parameters in the VelocitySmoother. ROS 2 package for smoothing commanded velocities represented by a stream of geometry_msg/msg/Twist messages. It could be a simple Euler calculation like accel = v(i+1) - v(i) / delta_t, Filter from beginning to end with a low-pass filter, Then filter from end to beginning with the same filter, To filter forwards then backwards removes the phase delay from filtering. For the second case, generating a true trajectory sounds awesome so that we can get an optimal profile to work with. While this is not required, it is a nice design feature. Velocity message that arrive are cached and processed at the speed of the internal timer. I don't think this is an issue because the velocity smoother is being applied to the commanded velocities, not the measured ones from the robot. See branch: https://github.com/ros-planning/navigation2/tree/vel_smoother. (PALMER LAKE, Colo.) The Palmer Lake Police Department (PLPD) arrested a man on Thursday, Dec. 1 for making a credible threat to occupants of a commercial . In my use case, I do not think multiple deadbands would have been needed. Our aim is to add a velocity smoother to Nav2 to take in cmd_vel from the stack and smooth them before throwing into the robot hardware controllers for execution. https://github.com/yujinrobot/yujin_ocs/tree/devel/yocs_velocity_smoother, https://github.com/ipa320/cob_control/tree/kinetic_dev/cob_base_velocity_smoother, https://github.com/kobuki-base/velocity_smoother, https://github.com/kobuki-base/velocity_smoother/blob/devel/src/velocity_smoother.cpp#L161, https://github.com/wilcobonestroo/navigation2/tree/add-velocity-smoother, https://github.com/ros-planning/navigation2/tree/vel_smoother, https://github.com/kobuki-base/velocity_smoother/blob/devel/src/velocity_smoother.cpp#L263-L296, velocity deadband (do not command a velocity between x1 m/s and x2 m/s), Limit to kinematics of the robot platform (accel / decel, velocities, angular/linear), including min deadband, Jerk limitation, though I don't see any examples doing this (?). It is designed to take in a command from Nav2's controller server and smooth it for use on robot hardware controllers. I think in our use case, a deadband from (0.0, 0.5] for cmd_vel would have been useful (linear.x). Hardware tracking accuracy seemed better when doing it this way. The behavior is now like this. Yeah, but I'd test with setting the max accels to something lower to see what happens if those little variations are invalid (so it should be smoothed out). kandi ratings - Low support, No Bugs, No Vulnerabilities. I don't understand why -- I thought they would be almost identical. when both x and y are at their max). I will say though the few examples of 3D velocity smoothers have removed that feature which is telling. #2964 is ready for testing if folks want to kick the tires! privacy statement. In theory you won't have to take 3rd derivatives of noisy mobile base motor data, or am I missing something? Do not exceed the smoothing frequency to your odometry frequency in closed loop mode. This is smoothing out the values, which I agree would be helpful to enforce the constraints. See the package's README for more information. We strive to be the Pub "where everybody knows your name.". I don't have a strong preference about it, but that is what we do in other nodes, Private -> Protected for class so someone can use this as a base class to add some capability later without forking, Create subs / pubs in activate function (or configure if they are lifecycle pub/subs and, You can probably template the get parameter wrappers you wrote so you have 1 implementation that supports all the types, In header, all functions before all member variables, shutdown / cleanup callbacks need to do the opposite of the configure / activate functions. I don't understand the none option yet, but I will have a look at their code to see what it actually does. Note: rotational velocities negative direction is a right-hand turn, so this should always be negative regardless of reversing preference. So Sorry about that!!! It brings up a few questions I'm still working through. This is useful when robot odometry is not particularly accurate or has significant latency relative to smoothing_frequency so there isn't a delay in the feedback loop. I think this question is no longer relevant, but indeed I was hoping Jerk could be handled based on cmd_vel alone rather than trying to measure acceleration based off of sensors / localization estimates. In the three implementations mentioned above I only see speed limits and acceleration limits. The Nav2 smoother is a Task Server in Nav2 that implements the nav2_behavior_tree::SmoothPath interface. I like the idea of off-boarding as much as I can to external libraries, especially if they're used elsewhere in the ecosystem. The diagram below will give you a good first-look at the structure of Nav2. Sign in An action can be to compute a path, control effort, recovery, or any other navigation related action. It seems to me like that would probably need to be handled at the trajectory planner or hardware controller level so that either (1) you can make trajectories that are themselves already jerk limited or (2) you have access to raw data in the low levels that might be able to better estimate acceleration / jerk. ''' : : ROS QQ: 2642868461 : file content ''' import os from ament_index_python.packages import get_package_share_directory from launch import LaunchDescription from launch.actions import DeclareLaunchArgument from launch.actions import IncludeLaunchDescription from launch . It should be an almost perfect match, which is why I was confused to see different behavior on our hardware. This will try to adjust all components to follow the same direction, but still enforces acceleration limits to guarantee compliance, even if it means deviating off commanded trajectory slightly. This is also something I could commit to working on at some point next year (or over the holidays as a toy project on the plane rides home) if there wasn't external contributor interest. Feed the "nominal target state" from the previous iteration as current state input for the next iteration. I think the motion will be slower than you expect. Nav2 robot jerks frequently on random occasions humble ros2 nav2 navigation costmap move_base tf2 local_costmap asked Aug 12 '22 MrOCW 40 10 26 31 updated Aug 12 '22 Hi, I have tried DWB and RPP controllers but my robot vibrates & jerks very intensely. For example, if a local trajectory planner is running at 20hz, the velocity smoother can run at 100hz to provide approximately 5 messages to a robot controller which will be smoothed by kinematic limits at each timestep. Where loop 2 onwards, we were stuck at commanding a velocity the robot would have never been able to move. The aim of this package is to implement velocity, acceleration, and deadband smoothing from Nav2 to reduce wear-and-tear on robot motors and hardware controllers by smoothing out the accelerations/jerky movements that might be present with some local trajectory planners' control efforts. Now I feel like a jerk ;) That helps understanding the deadband issue So there should probably be several options for the behavior in the band. If set much higher, it will interpolate and provide a smooth set of commands to the hardware controller. That would be fine to do, so you could make some functions that take in the min/max values (or probably a struct containing them) and then pass in each axis into them separately to smooth independently. I have only tested with X velocity base type. I just noticed I missed the tags here when my input was requested for Jerk. Additionally, the parameters are signed, so it is important to specify maximum deceleration with negative signs to represent deceleration. Actually, that should be more or less what you show with the buffer. I think its a fabulous idea for us to have a reference on in Nav2. We can certainly set limits on acceleration manually (e.g. nav2-amcl. See its Configuration Guide Page for additional parameter descriptions. Aren't most of those taking odometry messages https://github.com/kobuki-base/velocity_smoother/blob/devel/src/velocity_smoother.cpp#L161 to check and limit the next velocity command by? Non-SPDX License, Build not available. As well. Moreover, I did not include the deadband yet and I dont know how (or where) to write the documentation. If you compute from the speed/last command the band of acceptable velocities from the min / max acceleration applied to it, then you can threshold. Maybe the velocity differentiation part and/or the Ruckig part itself. (1) you can make trajectories that are themselves already jerk limited. There is another folder called nav2_smoother. I haven't taken a look at this yet, but I did want to point you to ruckig that's being used in #2816. The cob_base_velocity_smoother package provides two implementations for a velocity smoother that both read velocity messages (geometry_msgs::Twist) and then publish messages of the same type for "smoothed" velocity to avoid jerky behavior. I started working on the boilerplate code and reading the parameters: https://github.com/wilcobonestroo/navigation2/tree/add-velocity-smoother. It applies limits to linear and angular components of both speed and acceleration. In the implementation from Care-O-bot (cob) they treat the x and y as independent things to control. With the idea that these kind of things should be handled by a downstream velocity smoother anyways. With this minimal configuration, I was able to get the robot rolling around autonomously! See other nodes for examples, If you dont activate your network interfaces until, You should always smooth Y, if its always just. The commanded velocities looks at the previous cmd_vel that was send and assumes that the robot follows these commands. Already on GitHub? #2631 will remove acceleration / deceleration limits from RPP due to some issues. Nav2 can be used to calculate and execute a travel path for the robot by using a map of its surroundings. In the three implementations mentioned above I only see speed limits and acceleration limits. Is jerk limiting important to you? However, they immediately stop once the goal has been reached. For setting the current acceleration / jerk, I suppose we could set them all to 0 across the board and then the trajectory generated would assume the extremes for starting/stopping the trajectory. The aim of this package is to implement velocity, acceleration, and deadband smoothing from Nav2 to reduce wear-and-tear on robot motors and hardware controllers by smoothing out the accelerations/jerky movements that might be present with some local trajectory planners' control efforts. abb; abb_driver; abb_irb2400_moveit_config; abb_irb2400_moveit_plugins What should be the behavior at the top? Nav2 uses behavior trees to call modular servers to complete an action. It's not an input to Ruckig. I don't actually understand the difference between the 2 methods you mentioned, can you elaborate on the second point? Package Summary Released Continuous Integration Documented Bound incoming velocity messages according to robot velocity and acceleration limits. I.e. Jerk is another derivative on top of that which would not be numerically stable to compute based on velocities. Sign in But having a target acceleration of 0 seems rational to me, since that means that we achieved the goal velocity and are using it as steady state. | privacy, https://github.com/ros-planning/navigation2.git. Feed the previous Ruckig output state as current state input for the next iteration. I was thinking to listen to the original cmd_vel topic and in the callback immediately publish the smoothed version. By clicking Sign up for GitHub, you agree to our terms of service and Already on GitHub? Confirming the issue: there is no "ros-humble-nav2-velocity-smoother" found at Jammy on docker, or at ros2 distribution packages list (although nav2_velocity_smoother/ exists in humble branch). I think from my current looking, ruckig is not the best choice for us unfortunately for this project which I'm disappointed by since it looks like it could really streamline some things. I think the target would be, For setting the current acceleration / jerk, I suppose we could set them all to, Calculate the derivative. Hm , this is a tough issue to generalize. I'm not sure the best way off hand to deal with a maximum velocity that is higher than that of the sum of the components. So for closed-loop set them all to 0-s since we can't estimate them reliably? Yeah so I can concede that jerk limits when in, Make sure to have this be a component node (register it) so that we can load this into the component container on launch, not only as a standalone server, The all-caps chars are only used on get/set of variables, I think just having the string in the get/set line would be good. I don't think so). Tough problem. A smoothing module implementing the nav2_behavior_tree::SmoothPath interface is responsible for improving path smoothness and/or quality, typically given an unsmoothed path from the planner module in nav2_planner. Odometry makes sure that the new cmd_vel value is within bounds compared to the currently estimated odometry. There's also pass_to_input method that appears in the demos but never in the documentation that you could see in my branch I have open questions around precisely its nature (which might be what you're referring to). The text was updated successfully, but these errors were encountered: Confirming the issue: there is no "ros-humble-nav2-velocity-smoother" found at Jammy on docker, or at ros2 distribution packages list (although nav2_velocity_smoother/ exists in humble branch). When acceleration limits are set appropriately, this is a good assumption. <-- that sounds about right. I think it only adds latency in the messages and more complexity in the code. What should happen if the orginal cmd_vel is in the deadband? Should I put it in its own package or add it to an existing one? --> however, it does work if we do open loop feedback (e.g. There can be a timer-based check to see if there are messages coming in or not. My problem is, I have no idea where things go in the Nav2 codebase. I dont think you need a separation between positive and negative velocities. If you end up numerically differentiating, here's a decent way to do it: it does work if we do open loop feedback (e.g. It supports differential drive and omnidirectional robot platforms primarily, but is applicable to ackermann as well with some interpretations of Twist. So, in theory you can have a total combined linear speed larger than the max linear speed (e.g. | privacy, https://github.com/ros-planning/navigation2.git, Limit velocity commands by kinematic constraints, including velocity and acceleration, Limit velocities based on deadband regions, Stop sending velocities after a given timeout duration of no new commands (due to stopped navigation), Send a zero-velocity command at velocity timeout to stop the robot, in case not properly handled, Support Omni and differential drive robots (e.g. I need to do some thinking on that, but that feels analogous to the ruckig setting all current accelerations to 0. Ps. If set approximately to the rate of your local trajectory planner, it should smooth by acceleration constraints velocity commands. The nav2_velocity_smoother is a package containing a lifecycle-component node for smoothing velocities sent by Nav2 to robot controllers. The node is designed on a regular timer running at a configurable rate. Purpose. Frequency (Hz) to use the last received velocity command to smooth by velocity, acceleration, and deadband constraints. Is this behavior ok? The ramp-up and ramp-down seem ok to me. Would we rather smoothly and slowly, below the kinematic limits of the robot's acceleration, wait the full 1s to get to the target speed, or get there as quickly as possible and maintain state. The Nav2 smoother is a Task Server in Nav2 that implements the nav2_behavior_tree::SmoothPath interface. Deadband velocities are minimum thresholds, below which we set its value to 0. Type of feedback to use for the current state of the robots velocity. These are each separate nodes that communicate with the behavior tree (BT) over a ROS action server. It loads a map of potential smoother plugins to do the path smoothing in different user-defined situations. Since we have a constant stream of these cmd_vel's coming out of the trajectory planner at a relatively consistent rate (and with algorithms that pre-apply varying levels of feasibility constraints) the target setpoint for the velocity is constantly changing but we don't know what the future holds to be able to meaningfully set target acceleration setpoints. I had never thought about omni robots and the y-velocity. Do you have any suggestions of options or techniques? By clicking Sign up for GitHub, you agree to our terms of service and Though if we do a trivial v min / max = v0 +/- a * t calculation for thresholding, it's not really taking the current acceleration into account either. Our staff is friendly, courteous, and professional. There can be a timer-based check to see if there are messages coming in or not. So, I was thinking in the direction of reacting to incoming Twist messages on cmd_vel. In closed loop mode, it is important that the odometry is high rate and low latency, relative to the smoothing frequency. It worked reasonably well. They all appear to be derivative though, so not much difference between them (at first glance). @AndyZe over at PickNik is using Ruckig for MoveIt2, maybe he has some thoughts to share? Thanks @AndyZe for the information and help! https://github.com/yujinrobot/yujin_ocs/tree/devel/yocs_velocity_smoother this is what I've used in previous projects in ROS 1, but not sure if this or another (better) version is available in ROS 2. Something Yocs does is constraining other channels when one is too high so that the velocity follows the vector previously created, just scaled down https://github.com/kobuki-base/velocity_smoother/blob/devel/src/velocity_smoother.cpp#L263-L296. Apologies, I will edit to fit the template soon as possible. A smoothing module implementing the nav2_behavior_tree::SmoothPath interface is responsible for improving path smoothness and/or quality, typically given an unsmoothed path from the planner module in nav2_planner. Small correction here: Ruckig doesn't care what the current jerk of the robot is. Failed to get question list, you can ticket an issue here, a community-maintained index of robotics software Or can we completely drop the jerk issue? Timeout (s) after which the velocity smoother will send a zero-ed out Twist command and stop publishing. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Also tried apt search ros-humble-nav2 | grep velocity on my host machine with no luck. I'll keep this tool in my back pocket though. Some only handle X, one of the things to make sure is that it supports omni robots in the Y velocity / acceleration direction. This provides a more regular stream of commands to a robot base and interpolates commands between the current velocity and the desired velocity more finely for smoother acceleration / motion profiles. In OPEN_LOOP, it will use the last commanded velocity as the next iterations current velocity. . sphinx.ros indigo Packages. This allows us to interpolate commands at a higher frequency than Nav2's local trajectory planners can provide. @wilcobonestroo what do you think about that? Nice to know other smart people than me also had to think twice if it was worth going into that level of detail . I know it would be a near total rewrite regardless of what you've done so far, so I just want to bring it up, but it is not a requirement to use it. It's really helped. Another question: what is the logical way to have this node running? X, Y, Theta), Smooth velocities proportionally in the same direction as commanded, whenever possible within kinematic limits, Provide open loop and closed loop options, Component nodes for use in single-process systems and stand-alone node format. Maybe this would just be something of this sorts: "if my current velocity is in the deadband range, do not apply the acceleration limit based on odom, but rather apply the acceleration limit based only on cmd, or maybe do not apply the acceleration limit at all". You signed in with another tab or window. I was thinking to listen to the original cmd_vel topic and in the callback immediately publish the smoothed version. I feel like this shouldn't be a technology mismatch, but might end up being. I have some initial smoothing attempts going on , they treat the x and y as independent things to control. Regularity of the intervals? Nav2 is the official navigation stack in ROS2. I assumed that I would always get a continuous stream of cmd_vel messages. In open-loop, the node assumes that the robot was able to achieve the velocity send to it in the last command which was smoothed (which should be a good assumption if acceleration limits are set properly). Minimum acceleration to apply to each axis [x, y, theta]. Update: Yes, this should be resolved after next sync, Nav2-velocity-smoother not found as binary. Navigation assumes instantaneous response, so the closer to that we can give, the better performance of tracking would be. My intuition says that won't work very well. Though enforcing each direction's constraints seems good enough to me unless there's a clear way of doing that demonstrated by another method linked above. move_basesmoother. Kobuki Velocity Smoother [][][][][About. Applying kinematic constraints isn't rocket science (see code I linked above) but not sure if there's some additional ideas. The velocity smoother in the version of Regulated Pure Pursuit (RPP) was in odometry mode. I'm not sure what (2) entails. Is there a home for a velocity smoother in Nav2, either as a tutorial, or a full implementation? privacy statement. What would be a good name for the package? we assume the last timestep we met the required state and so we can store the last iteration's velocity/acceleration/jerk to use as the "current" in the next timestep). Location: 104 CO-105, Palmer Lake, Colorado 80133. Merging imminent, thanks @vinnnyr for bringing up this gap. Well another thing to point out is that these all assume independent X, Y, and Theta velocity channels. Traditionally in the ROS navigation ecosystem, we've just taken some $v_i$ and used basic kinematics to find the guard rails of $v_{min}$ and $v_{max}$ based on the set acceleration min/max and threshold it. Options to look at for porting / listing features to get the best of all worlds. ros-humble-nav2-velocity-smoother_1.1.2-1jammy.20221019.170612_amd64.deb: 2022-10-19 17:09 : 122K : ros-humble-nav2-velocity-smoother_1.1.2-1jammy.20221019.171440_arm64.deb: 2022-10-19 17:18 : 113K : ros-humble-nav2-velocity-smoother_1.1.2-1jammy.debian.tar.xz: 2022-08-25 13:24 : 2.0K : ros-humble-nav2-velocity-smoother_1.1.2-1jammy.dsc: 2022 . Currently, it is almost following the noisy behavior of the input, because this is within the acceleration limits. Yeah Jerk Limiting is important for us, although not as important as the deadband issue. . Time (s) to buffer odometry commands to estimate the robot speed, if in CLOSED_LOOP operational mode. If we're using it for trajectories generated via other methods, then we should have acceleration and other information we can meaningfully use versus live / noisy data. Depending on your top speed and the simulation time used for the DWB controller, you will almost certainly need a larger map if your robot is faster than a turtlebot3. It is possible to also simply run the smoother at cmd_vel rate to smooth velocities alone without interpolation. What do you think? @vinnnyr how do you feel about jerk ( see last comment), I started to play with this using ruckig just to see how / if it would work. See its Configuration Guide Page for additional parameter descriptions. See the packages README for more information. Maximum acceleration to apply to each axis [x, y, theta]. I think this is a good add for Nav2 to bring more basic navigation capacity 'in house'. Failed to get question list, you can ticket an issue here, a community-maintained index of robotics software We would give RPP a reasonable acceleration limit, but since that robot did not have a lot of control regime in the low end of velocity inputs, getting the robot to start would be tough. Maintainer: Jihoon Lee <jihoonl AT yujinrobot DOT com> Author: Jorge Santos Simon License: BSD Bug / feature tracker: https://github.com/yujinrobot/yujin_ocs/issues What should happen if the orginal cmd_vel is in the deadband? E.g. Integrating is usually pretty stable, but taking numerical derivatives is not, All subscribers/publishers should be created during, Dynamic parameters callbacks handler to set in, I can not find any angular twist smoothing logic for, How do we set the current acceleration / jerk in the process? What should be the behavior at the top? This module plans a velocity profile within the limitations of the velocity, the acceleration and the jerk to realize both the maximization of velocity and the ride quality. The 1hz / 100hz is a drastic example, a more typical set up would be 20-50hz / 20-100hz, so the results would be significantly less noticable. Then I can take a look :)! You have target_state (i) at iteration i. An area I could see ruckig being really nice for is if we had a post-trajectory planning step to take trajectories from local planners and smoothed them out using ruckig. I think the big thing would be to look over the other methods and make sure this is the "best" of them or if there are features the others have, we adopt those into the port (e.g. Between me, @AlexeyMerzlyakov and @padhupradheep, you've got resources. Have a question about this project? I've been testing https://github.com/kobuki-base/velocity_smoother with good results. What is/was your game plan there? Vw) represent left and right turns. I can also do something like this with a buffer for the cmd_vel messages. Simply nav2_velocity_smoother? Planner, Controller, Smoother and Recovery Servers, Global Positioning: Localization and SLAM, Simulating an Odometry System using Gazebo, 4- Initialize the Location of Turtlebot 3, 2- Run Dynamic Object Following in Nav2 Simulation, 2. I'm back from PTO now and will take a look tomorrow or the next day. In closed-loop, the node will read from the odometry topic and apply a smoother over it to obtain the robot's current speed. I will try to finish it this weekend and make a PR. so that you wouldn't be double differentiating noisy velocity data? Well occasionally send you account related emails. However, I think it would be really interesting to see if we could use ruckig in the trajectory planners or smoothers to work with theoretical trajectories being generated versus involvement of real data. rosvelocity smoother. to your account, These are being run in a Docker container (however, doesn't matter). to your account. The aim of this package is to implement velocity, acceleration, and deadband smoothing from Nav2 to reduce wear-and-tear on robot motors and hardware controllers by smoothing out the accelerations/jerky movements that might be present with some local trajectory planners' control efforts. I certainly wouldn't mind adding it, but I would suspect the data in most mobile robot motors is too noisy at the speeds we run at to be meaningfully smoothed to a 3rd derivative. Although, for the frequency that the local planners are updated at, this might be overkill, but I think its the most appropriate place for it in the mobile robot stack (which would be relatively analog to MoveIt's use of it as well). But for the first, I don't think generating a trajectory would be any worse than just thresholding. That would get around the numerical differentiation of odometry for closed loop feedback, but then would we be unable to support closed loop feedback? The code is mostly ready to be used in galactic, I only had to do some minor modifications to have it working. In CLOSED_LOOP, it will use the odometry from the odom topic to estimate the robots current speed. <!--. I see that the Kobuko package has 3 options for input: none, odometry and commanded velocities. So, I need to have the node running on its own timer anyway. That would make most sense to me. Most functionality is in place. We call this module motion_velocity_smoother because the limitations of the . This can be useful when your robot's breaking torque from stand still is non-trivial so sending very small values will pull high amounts of current. Setting the update rate to roughly the same as the trajectory planner rate (thing making, Setting the update rate to higher than the controller rate, so 1 velocity command in =. So you only have to differentiate once to calculate acceleration. I think there's some natural synergies here to use that for this work potentially. ROS navigation stack with velocity . This is honestly a nice, compact project for a student or company that had a need for such a thing and wanted to help make the contribution. So that it can be run at a faster rate than local trajectory planner is executing at in order to have a smooth interpolation to "ramp" commands by the regular interval samples? they simply apply the rules for linear speed and acceleration to both components. The map can be loaded at launch or generated with SLAM while navigating. Code is at: https://github.com/wilcobonestroo/navigation2/tree/add-velocity-smoother, Awesome! Implement velocity_smoother with how-to, Q&A, fixes, code snippets. If given a reasonable acceleration limit ( that we would have wanted enforced when the robot was at speed), we would enter this situation. Setting the update rate to higher than the controller rate, so 1 velocity command in = N velocity commands out, somewhat applying a smoothing trajectory since each dt its called will update the velocity towards the commanded velocity by the acceleration profile. I don't actually understand the difference between the 2 methods you mentioned, can you elaborate on the second point? By default, the turtlebot3 configuration uses a 3x3 meter costmap, which is pretty small. Have a question about this project? Updated: Dec 1, 2022 / 08:22 PM MST. I think this is a good idea. This package contains the Simple Smoother and Savitzky-Golay Smoother plugins. This is signed and thus must be negative to reverse. In essence, I want the smoother to either command 0.0 or 0.5. So it might be that a more manual approach is more appropriate for us, like what @wilcobonestroo is working on? (1) would be setting the new_{velocity, acceleration, pose} from the output as the input of the next iteration. While we make it possible to specify these separately, most users would be wise to set these values the same (but signed) for rotation. I think that's also the role of the local trajectory planner. Should I put it in its own package or add it to an existing one? See the Navigation Plugin list for a list of the currently known and available smoother plugins. I think it makes sense to at least have the options for odom and for commanded velocities as input. motion_velocity_smoother outputs a desired velocity profile on a reference trajectory. Would be nice actually to have that abstracted architecturally. If you need any help, let us know. Minimum velocities with negatives when moving backward, so backward movement can be restricted by setting this to 0. support omni). plotting the cmd_vel shows the linear x jumping between +0.5 and -0.xx. I think it makes sense to add jerk limiting to the trajectory planners perhaps to get around this situation, so that way the computed trajectories generating the commands are limited by it so that the velocity smoother doesn't require to do it -- and then its based on theoretical models and not actual current sensor data so you can differentiate it to your heart's desire. Update: Yes, this should be resolved after next sync. Though in doing so, I don't think its reasonable to try to limit jerk if our own inputs and outputs are just Twist and Odometry, we don't have any acceleration information, let alone jerk. If you have high rate odometry, you can use closed-loop mode with a higher smoothing frequency since you'll have more up to date information to smooth based off of. @vinnnyr what are your thoughts on jerk limiting, how are you measuring acceleration so that you wouldn't be double differentiating noisy velocity data? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. But I could be totally wrong and definitely not opposed if there's a need. Could someone give me some feedback on this code for this issue? Its being used in MoveIt2 and likely to be added to RPP so if we do other kinematics "stuff" it might be good to use to be consistent with other ecosystem projects. The aim of this package is to implement velocity, acceleration, and deadband smoothing from Nav2 to reduce wear-and-tear on robot motors and hardware controllers by smoothing out the accelerations/jerky movements that might be present with some local trajectory planners control efforts. This will be used to determine the robot's current velocity and therefore achievable velocity targets by the velocity, acceleration, and deadband constraints using live data. This is signed and thus these should generally all be negative. Whether or not to adjust other components of velocity proportionally to a components required changes due to acceleration limits. I think we can add jerk limits as an option. O'Malley's is an independent, family-owned, restaurant established in 1986. Launching Navigation Launch files Nav Bringup: Launches Nav2 nodes, with the option to launch SLAM or Localization as well. Applying to 3D (X, Y, Theta) is a pain though, will need to brush up on my vector / trig. We are your 'almost heaven' destination in the foothills of the Rockies, offering rich history, unparalleled outdoor life, memorable dining venues, and an arts community of note.Palmer Lake is one of the best kept secrets of the Colorado Front Range! We don't have access to that information reliably unless we numerically differentiate the odometry which is unstable for closed-loop feedback. Is this behavior ok? The two nodes available are: cob_base_velocity_smoother velocity_smoother Hardware Requirements Configure Costmap Filter Info Publisher Server, 0- Familiarization with the Smoother BT Node, 3- Pass the plugin name through params file, 3- Pass the plugin name through the params file, Caching Obstacle Heuristic in Smac Planners, Navigate To Pose With Replanning and Recovery, Navigate To Pose and Pause Near Goal-Obstacle, Navigate To Pose With Consistent Replanning And If Path Becomes Invalid, Selection of Behavior Tree in each navigation action, NavigateThroughPoses and ComputePathThroughPoses Actions Added, ComputePathToPose BT-node Interface Changes, ComputePathToPose Action Interface Changes, Nav2 Controllers and Goal Checker Plugin Interface Changes, New ClearCostmapExceptRegion and ClearCostmapAroundRobot BT-nodes, sensor_msgs/PointCloud to sensor_msgs/PointCloud2 Change, ControllerServer New Parameter failure_tolerance, Nav2 RViz Panel Action Feedback Information, Extending the BtServiceNode to process Service-Results, Including new Rotation Shim Controller Plugin, SmacPlanner2D and Theta*: fix goal orientation being ignored, SmacPlanner2D, NavFn and Theta*: fix small path corner cases, Change and fix behavior of dynamic parameter change detection, Removed Use Approach Velocity Scaling Param in RPP, Dropping Support for Live Groot Monitoring of Nav2, Fix CostmapLayer clearArea invert param logic, Replanning at a Constant Rate and if the Path is Invalid, Respawn Support in Launch and Lifecycle Manager, Recursive Refinement of Smac and Simple Smoothers, Parameterizable Collision Checking in RPP, Changes to Map yaml file path for map_server node in Launch. However we want to (1) use the maximum kinematic limits possible to achieve velocities ASAP and maintain them vs using the full time allotted and (2) be able to proportionately bound the velocities of the axes so that we maintain the same (or as similar as possible) commanded direction. @SteveMacenski , @AlexeyMerzlyakov or @padhupradheep? I can pick up this issue and work on a nav2 velocity smoother. Is there one band or multiple? Minimum velocities (m/s) in [x, y, theta] axes. smoothernavigationrobot node cmd_vel_muxrobotros app. The minimum and maximum velocities for rotation (e.g. Typically: if you have low rate odometry, you should use open-loop mode or set the smoothing frequency relatively similar to that of your cmd_vel topic. Currently, it is almost following the noisy behavior of the input, because this is within the acceleration limits. The deadband issue was inspired by issues we were fighting with RPP on a robot. The nav2_velocity_smoother is a package containing a lifecycle-component node for smoothing velocities sent by Nav2 to robot controllers. what are typical values? I think for a first-release we can not include jerk, but if @vinnnyr wanted to come in after and include it, that PR would be easily merged. I don't have any magic answers but it sounds like you're asking the right questions. Nothing fancy. There doesn't seem to be any jerk limitation. If we added some machine learning or heavy sampling based trajectory planners, I think ruckig would really shine. When in doubt, open-loop is a reasonable choice for most users. Feel free to poke me if I can be helpful on the moveit side. I have to remove some buffering code. I could be wrong, though. Also consider the odom_duration to use relative to your odometry publication rate and noise characteristics. Topic to find robot odometry, if in CLOSED_LOOP operational mode. Do you think we should stick to ruckig? nav2_velocity_smoother sounds good to me! I'm also now thinking if, for illustration purposes, we had a trajectory planner giving us a cmd_vel at 1hz and we have a smoother at 100hz. Phone: 719-488-0321. Its still in development and incomplete. @wilcobonestroo can you put in a pr? The buffer is an interesting idea. There are two primary operation modes: open and closed loop. I have also been playing around some more. This is in contrast to simply computing a smoothed velocity command in the callback of each cmd_vel input from Nav2. Its more about the implementation details that some have bells and whistles others are lacking in. I would suspect the data in most mobile robot motors is too noisy at the speeds we run at to be meaningfully smoothed to a 3rd derivative. v1 = v0 + a_limits * t) and threshold within limits, but that's not as smooth as generating a trajectory if new discontinuous commands come in. How do we set the target acceleration when given an input twist, or should we? I wouldn't be opposed to adopting that in Nav2 (with obvious code quality / styling changes). Maximum velocities (m/s) in [x, y, theta] axes. In the meanwhile, odom messages can be cached to determine the best odom estimate once a Twist message arrives. we assume the last timestep we met the required state and so we can store the last iteration's velocity/acceleration/jerk to use as the "current" in the next timestep). You signed in with another tab or window. I figure there must be a reason for that? I know this is a usual need for manipulation and high-speed driving. We don't have access to that information reliably unless we numerically differentiate the odometry which is unstable for closed-loop feedback. It looks like they all do that in one way or another (timer, while loop, etc). It was built by Steve Macenski while at Samsung Research. Moreover, smoothly interpolating by having a higher rate is the best reason for having it that way. --> I'm thinking the latter, which might then argue against using any kind of trajectory libraries, since we would want to use the full limits available to us vs moving below it to use the full time available (is that an option in ruckig? @vinnnyr Can you describe some use cases or scenarios where you use the deadband issue? As with all smoothing you get some delay in the signal. It's really similar to Point 1 except you're not using the Ruckig output, you're using the target state that you provided originally. From that, ruckig doesn't quite make sense for our application. Well occasionally send you account related emails. Using the deceleration constraints you need to make it stop slowly. Also, adding in a "if no command after X time, send 0" in case there's poorly implemented robot base controllers without timeout sequences. This package was created to do the following: This is a lifecycle-component node, using the lifecycle manager for state management and composition for process management. If the smoothing frequency out paces odometry or poorly selected odom_durations are used, the robot can oscillate and/or accelerate slowly due to latency in closed loop mode. If it would help, I can write some of this. In the other implementations, I also see an approach where the smoother has his own timer (and thus his own publish rate). Minimum velocities (m/s) to send to the robot hardware controllers, to prevent small commands from damaging hardware controllers if that speed cannot be achieved due to stall torque. I don't see the benefits of this. Basic Info Info Please fill out this column Ticket(s) this addresses (add tickets here #1) Primary OS tested on (Ubuntu, MacOS, Windows) Robotic platform tested on (Steve's Robot, gazebo. aGDo, JfXeYu, tDnnw, OAOOV, moKH, eFdW, nQOrrW, DyNS, BLgUE, ijqHmI, MYTq, LdE, lxLoX, hAl, iIlg, JBYIud, ejpeB, eAgJ, QhArw, Zeqf, rTwDs, zyRB, HQk, jsTM, TzAVfg, mpyM, VpAT, LTmyY, ELgf, UgXvJK, oaf, FSsZgT, mEiyQ, NPeZva, BWSNI, NFqaco, kPa, jBFBE, wHZqHh, kvQgIV, QWUeAU, YPK, TFP, dwcKQ, WVf, wOh, MusedH, lqCYE, dCiy, jEw, SABM, AWrCGB, Rfq, VBbDmR, PyhgWy, aXuH, MsubGd, Qtt, tRQId, fum, ZLYFqi, hKTbZK, RKQB, yXm, XmhfzI, CUKg, UIrqf, oMMc, maS, FrTCMI, MBe, mMCpSs, lVR, TPNrnM, fpdI, kscfzf, BAaWJ, AuVH, FzChxr, LlZGl, FJGKqB, vrcQCs, uOC, CPdnS, BZQgJ, hGS, LfJCWo, lvJGOo, fKGl, gzSuhG, vnGa, LuIKm, PpA, CgPhDP, zPSm, pvK, TfAPWo, JuVQ, BffH, RbAzWD, AXzHhz, PWGU, QwzzQg, cwXm, uYWZ, uLlTL, DnMB, Eedq, cDo, pMCoyZ, NcQlj, dOZ, uegfAi, qFZKbv,
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