velocity smoother nav2

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. I think the motion will be slower than you expect. Thusly, it takes in a command via the cmd_vel topic and produces a smoothed output on smoothed_cmd_vel. support omni). so that you wouldn't be double differentiating noisy velocity data? It loads a map of potential smoother plugins to do the path smoothing in different user-defined situations. 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! This is smoothing out the values, which I agree would be helpful to enforce the constraints. I think there's some natural synergies here to use that for this work potentially. rosvelocity smoother. 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. Or can we completely drop the jerk issue? I started working on the boilerplate code and reading the parameters: https://github.com/wilcobonestroo/navigation2/tree/add-velocity-smoother. Where loop 2 onwards, we were stuck at commanding a velocity the robot would have never been able to move. You signed in with another tab or window. While this is not required, it is a nice design feature. Minimum acceleration to apply to each axis [x, y, theta]. nav2-amcl. That would make most sense to me. 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? Nav2 can be used to calculate and execute a travel path for the robot by using a map of its surroundings. Velocity message that arrive are cached and processed at the speed of the internal timer. In CLOSED_LOOP, it will use the odometry from the odom topic to estimate the robots current speed. The nav2_velocity_smoother is a package containing a lifecycle-component node for smoothing velocities sent by Nav2 to robot controllers. The diagram below will give you a good first-look at the structure of Nav2. I figure there must be a reason for that? Maximum velocities (m/s) in [x, y, theta] axes. 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. 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). 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. sphinx.ros indigo Packages. 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. If set approximately to the rate of your local trajectory planner, it should smooth by acceleration constraints velocity commands. Then I can take a look :)! 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. Most functionality is in place. It is possible to also simply run the smoother at cmd_vel rate to smooth velocities alone without interpolation. Another question: what is the logical way to have this node running? 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. Sign in 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. Merging imminent, thanks @vinnnyr for bringing up this gap. Our staff is friendly, courteous, and professional. 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 don't think that should be the default behavior but I'd be fine with that a parameterized option. This is signed and thus these should generally all be negative. 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. I'm not sure what (2) entails. Actually, that should be more or less what you show with the buffer. 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. It's not an input to Ruckig. I feel like this shouldn't be a technology mismatch, but might end up being. I.e. motion_velocity_smoother outputs a desired velocity profile on a reference trajectory. When acceleration limits are set appropriately, this is a good assumption. In theory you won't have to take 3rd derivatives of noisy mobile base motor data, or am I missing something? There doesn't seem to be any jerk limitation. The map can be loaded at launch or generated with SLAM while navigating. @wilcobonestroo can you put in a pr? 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. We don't have access to that information reliably unless we numerically differentiate the odometry which is unstable for closed-loop feedback. 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. 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. There are two primary operation modes: open and closed 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. I'm back from PTO now and will take a look tomorrow or the next day. Time (s) to buffer odometry commands to estimate the robot speed, if in CLOSED_LOOP operational mode. | privacy, https://github.com/ros-planning/navigation2.git. You signed in with another tab or window. to your account, These are being run in a Docker container (however, doesn't matter). 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). 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. Odometry makes sure that the new cmd_vel value is within bounds compared to the currently estimated odometry. These are each separate nodes that communicate with the behavior tree (BT) over a ROS action server. Already on GitHub? Well occasionally send you account related emails. Do you think we should include jerk for the commanded velocity mode? See other nodes for examples, If you dont activate your network interfaces until, You should always smooth Y, if its always just. Have a question about this project? Also, adding in a "if no command after X time, send 0" in case there's poorly implemented robot base controllers without timeout sequences. 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. We don't have access to that information reliably unless we numerically differentiate the odometry which is unstable for closed-loop feedback. Update: Yes, this should be resolved after next sync, Nav2-velocity-smoother not found as binary. Between me, @AlexeyMerzlyakov and @padhupradheep, you've got resources. I think that's also the role of the local trajectory planner. (1) you can make trajectories that are themselves already jerk limited. While we make it possible to specify these separately, most users would be wise to set these values the same (but signed) for rotation. Well occasionally send you account related emails. Apologies, I will edit to fit the template soon as possible. Do not exceed the smoothing frequency to your odometry frequency in closed loop mode. 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. 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). As well. Currently, it is almost following the noisy behavior of the input, because this is within the acceleration limits. There can be a timer-based check to see if there are messages coming in or not. ROS navigation stack with velocity . I was thinking to listen to the original cmd_vel topic and in the callback immediately publish the smoothed version. I can also do something like this with a buffer for the cmd_vel messages. (1) would be setting the new_{velocity, acceleration, pose} from the output as the input of the next iteration. However, they immediately stop once the goal has been reached. 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. Some only handle X, one of the things to make sure is that it supports omni robots in the Y velocity / acceleration direction. 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. This is signed and thus must be negative to reverse. So you only have to differentiate once to calculate acceleration. Feel free to poke me if I can be helpful on the moveit side. There can be a timer-based check to see if there are messages coming in or not. 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! In closed-loop, the node will read from the odometry topic and apply a smoother over it to obtain the robot's current speed. See the packages README for more information. @wilcobonestroo what do you think about that? By default, the turtlebot3 configuration uses a 3x3 meter costmap, which is pretty small. We call this module motion_velocity_smoother because the limitations of the . It brings up a few questions I'm still working through. The minimum and maximum velocities for rotation (e.g. How do we set the target acceleration when given an input twist, or should we? But for the first, I don't think generating a trajectory would be any worse than just thresholding. Timeout (s) after which the velocity smoother will send a zero-ed out Twist command and stop publishing. 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. If it would help, I can write some of this. 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. It is designed to take in a command from Nav2's controller server and smooth it for use on robot hardware controllers. 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 . Yeah Jerk Limiting is important for us, although not as important as the deadband issue. I haven't taken a look at this yet, but I did want to point you to ruckig that's being used in #2816. If we added some machine learning or heavy sampling based trajectory planners, I think ruckig would really shine. 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. This is in contrast to simply computing a smoothed velocity command in the callback of each cmd_vel input from Nav2. 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. 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 =. 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 (?). 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? We strive to be the Pub "where everybody knows your name.". In essence, I want the smoother to either command 0.0 or 0.5. Hardware tracking accuracy seemed better when doing it this way. 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. 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. I see that the Kobuko package has 3 options for input: none, odometry and commanded velocities. Moreover, smoothly interpolating by having a higher rate is the best reason for having it that way. I could be wrong, though. By clicking Sign up for GitHub, you agree to our terms of service and 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. 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. There is another folder called nav2_smoother. Now I feel like a jerk ;) 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. 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. I think it only adds latency in the messages and more complexity in the code. 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? I think in our use case, a deadband from (0.0, 0.5] for cmd_vel would have been useful (linear.x). 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. Moreover, I did not include the deadband yet and I dont know how (or where) to write the documentation. It supports differential drive and omnidirectional robot platforms primarily, but is applicable to ackermann as well with some interpretations of Twist. Deadband velocities are minimum thresholds, below which we set its value to 0. 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. From that, ruckig doesn't quite make sense for our application. Using the deceleration constraints you need to make it stop slowly. ROS 2 package for smoothing commanded velocities represented by a stream of geometry_msg/msg/Twist messages. I will try to finish it this weekend and make a PR. Whether or not to adjust other components of velocity proportionally to a components required changes due to acceleration limits. See branch: https://github.com/ros-planning/navigation2/tree/vel_smoother. I just noticed I missed the tags here when my input was requested for Jerk. The velocity smoother in the version of Regulated Pure Pursuit (RPP) was in odometry mode. 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. In closed loop mode, it is important that the odometry is high rate and low latency, relative to the smoothing frequency. The Nav2 smoother is a Task Server in Nav2 that implements the nav2_behavior_tree::SmoothPath interface. An action can be to compute a path, control effort, recovery, or any other navigation related action. I think this is a good add for Nav2 to bring more basic navigation capacity 'in house'. @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. 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. to your account. Well another thing to point out is that these all assume independent X, Y, and Theta velocity channels. Location: 104 CO-105, Palmer Lake, Colorado 80133. Updated: Dec 1, 2022 / 08:22 PM MST. 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.  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? In the three implementations mentioned above I only see speed limits and acceleration limits. Maybe the velocity differentiation part and/or the Ruckig part itself. What should happen if the orginal cmd_vel is in the deadband? kandi ratings - Low support, No Bugs, No Vulnerabilities. When in doubt, open-loop is a reasonable choice for most users. 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 nav2_velocity_smoother is a package containing a lifecycle-component node for smoothing velocities sent by Nav2 to robot controllers. 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. So Sorry about that!!! Simply nav2_velocity_smoother? Sign in The deadband issue was inspired by issues we were fighting with RPP on a robot. I don't understand the none option yet, but I will have a look at their code to see what it actually does. Nav2 is the official navigation stack in ROS2. Small correction here: Ruckig doesn't care what the current jerk of the robot is. I wouldn't be opposed to adopting that in Nav2 (with obvious code quality / styling changes). What should be the behavior at the top? I'll keep this tool in my back pocket though. 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. 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. @vinnnyr what are your thoughts on jerk limiting, how are you measuring acceleration so that you wouldn't be double differentiating noisy velocity data? 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. 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). See the package's README for more information. (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 . 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. We can certainly set limits on acceleration manually (e.g. Nice to know other smart people than me also had to think twice if it was worth going into that level of detail . What should be the behavior at the top? In my use case, I do not think multiple deadbands would have been needed. Package Summary Released Continuous Integration Documented Bound incoming velocity messages according to robot velocity and acceleration limits. Is there a home for a velocity smoother in Nav2, either as a tutorial, or a full implementation? 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). Feed the previous Ruckig output state as current state input for the next iteration. I don't understand why -- I thought they would be almost identical. Its still in development and incomplete. Purpose. Type of feedback to use for the current state of the robots velocity. Do you think we should stick to ruckig? Hm , this is a tough issue to generalize. They all appear to be derivative though, so not much difference between them (at first glance). <-- that sounds about right. 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. I don't actually understand the difference between the 2 methods you mentioned, can you elaborate on the second point? Should I put it in its own package or add it to an existing one? Minimum velocities (m/s) in [x, y, theta] axes. I don't actually understand the difference between the 2 methods you mentioned, can you elaborate on the second point? @AndyZe over at PickNik is using Ruckig for MoveIt2, maybe he has some thoughts to share? 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. Options to look at for porting / listing features to get the best of all worlds. It should be an almost perfect match, which is why I was confused to see different behavior on our hardware. Topic to find robot odometry, if in CLOSED_LOOP operational mode. But I could be totally wrong and definitely not opposed if there's a need. The behavior is now like 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. Code is at: https://github.com/wilcobonestroo/navigation2/tree/add-velocity-smoother, Awesome! Failed to get question list, you can ticket an issue here, a community-maintained index of robotics software So, I need to have the node running on its own timer anyway. As with all smoothing you get some delay in the signal. I've been testing https://github.com/kobuki-base/velocity_smoother with good results. Its more about the implementation details that some have bells and whistles others are lacking in. The node is designed on a regular timer running at a configurable rate. 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. Navigation assumes instantaneous response, so the closer to that we can give, the better performance of tracking would be. I think its a fabulous idea for us to have a reference on in Nav2. I know this is a usual need for manipulation and high-speed driving. For the second case, generating a true trajectory sounds awesome so that we can get an optimal profile to work with. This allows us to interpolate commands at a higher frequency than Nav2's local trajectory planners can provide. That helps understanding the deadband issue So there should probably be several options for the behavior in the band. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. 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. Applying to 3D (X, Y, Theta) is a pain though, will need to brush up on my vector / trig. So it might be that a more manual approach is more appropriate for us, like what @wilcobonestroo is working on? With the idea that these kind of things should be handled by a downstream velocity smoother anyways. Launching Navigation Launch files Nav Bringup: Launches Nav2 nodes, with the option to launch SLAM or Localization as well. What is/was your game plan there? 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. 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). plotting the cmd_vel shows the linear x jumping between +0.5 and -0.xx. Would be nice actually to have that abstracted architecturally. See the Navigation Plugin list for a list of the currently known and available smoother plugins. what are typical values? It was built by Steve Macenski while at Samsung Research. It looks like they all do that in one way or another (timer, while loop, etc). ''' : : 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 . #2631 will remove acceleration / deceleration limits from RPP due to some issues. See its Configuration Guide Page for additional parameter descriptions. Non-SPDX License, Build not available. It applies limits to linear and angular components of both speed and acceleration. After the bulk is in place, adding a couple new parameters and a new constraint would be a trivial PR to review and merge. 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. Also consider the odom_duration to use relative to your odometry publication rate and noise characteristics. Minimum velocities with negatives when moving backward, so backward movement can be restricted by setting this to 0. 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. I have to remove some buffering code. 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. I think we can add jerk limits as an option. In the meanwhile, odom messages can be cached to determine the best odom estimate once a Twist message arrives. So, I was thinking in the direction of reacting to incoming Twist messages on cmd_vel. In the other implementations, I also see an approach where the smoother has his own timer (and thus his own publish rate). Note: rotational velocities negative direction is a right-hand turn, so this should always be negative regardless of reversing preference. See its Configuration Guide Page for additional parameter descriptions. This package contains the Simple Smoother and Savitzky-Golay Smoother plugins. I need to do some thinking on that, but that feels analogous to the ruckig setting all current accelerations to 0. That would get around the numerical differentiation of odometry for closed loop feedback, but then would we be unable to support closed loop feedback? Already on GitHub? If given a reasonable acceleration limit ( that we would have wanted enforced when the robot was at speed), we would enter this situation. The two nodes available are: cob_base_velocity_smoother velocity_smoother Hardware Requirements nav2_velocity_smoother sounds good to me! 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. Feed the "nominal target state" from the previous iteration 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. I have only tested with X velocity base type. privacy statement. By clicking Sign up for GitHub, you agree to our terms of service and With this minimal configuration, I was able to get the robot rolling around autonomously! --> however, it does work if we do open loop feedback (e.g. move_basesmoother. The commanded velocities looks at the previous cmd_vel that was send and assumes that the robot follows these commands. I think this is a good idea. The buffer is an interesting idea. It's really helped. Is this what you also had in mind? | 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. @SteveMacenski , @AlexeyMerzlyakov or @padhupradheep? privacy statement. Regularity of the intervals? If set much higher, it will interpolate and provide a smooth set of commands to the hardware controller. So, in theory you can have a total combined linear speed larger than the max linear speed (e.g. Is jerk limiting important to you? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. when both x and y are at their max). In the implementation from Care-O-bot (cob) they treat the x and y as independent things to control. Also tried apt search ros-humble-nav2 | grep velocity on my host machine with no luck. 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