PX4-Avoidance | PX4 avoidance ROS node for obstacle detection and avoidance | Robotics library
kandi X-RAY | PX4-Avoidance Summary
kandi X-RAY | PX4-Avoidance Summary
PX4 computer vision algorithms packaged as ROS nodes for depth sensor fusion and obstacle avoidance. This repository contains three different implementations:. The three algorithms are standalone and they are not meant to be used together. The local_planner requires less computational power but it doesn't compute optimal paths towards the goal since it doesn't store information about the already explored environment. An in-depth discussion on how it works can be found in this thesis. On the other hand, the global_planner is computationally more expensive since it builds a map of the environment. For the map to be good enough for navigation, accurate global position and heading are required. An in-depth discussion on how it works can be found in this thesis. The safe_landing_planner classifies the terrain underneath the vehicle based on the mean and standard deviation of the z coordinate of pointcloud points. The pointcloud from a downwards facing sensor is binned into a 2D grid based on the xy point coordinates. For each bin, the mean and standard deviation of z coordinate of the points are calculated and they are used to locate flat areas where it is safe to land. Note The development team is right now focused on the local_planner. The documentation contains information about how to setup and run the two planner systems on the Gazebo simulator and on a companion computer running Ubuntu 18.04 (recommended), for both avoidance and collision prevention use cases.
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Community Discussions
Trending Discussions on Robotics
QUESTION
I have imported a urdf model from Solidworks using SW2URDF plugin. The model loads correctly on Gazebo but looks weird on RVIZ, even while trying to teleoperate the robot, the revolute joint of the manipulator moves instead of the wheels. Is there anyone who has faced this issue before or has a solution to it? Here is how it looks on Gazebo
Here is the URDF file of the Model:
...ANSWER
Answered 2022-Mar-22 at 13:41So, I realized two problems:
First, you have to change the fixed frame in the global options of RViz to world
or provide a transformation between map
and world
.
Second, your URDF seems broken. There is something wrong with your revolute
-typed joints. Changing their type to fixed
fixed the problem. I think, it's best if you ask a separate question with a minimal example regarding this second problem.
QUESTION
This question is related to my final project. In gazebo simulation environment, I am trying to detect obstacles' colors and calculate the distance between robot and obstacles. I am currently identifying their colors with the help of OpenCV methods (object with boundary box) but I don't know how can i calculate their distances between robot. I have my robot's position. I will not use stereo. I know the size of the obstacles. Waiting for your suggestions and ideas. Thank you!
My robot's topics :
- cameras/camera/camera_info (Type: sensor_msgs/CameraInfo)
- cameras/camera/image_raw (Type: sensor_msgs/Image)
- sensors/lidars/points (Type: sensor_msgs/PointCloud2)
ANSWER
Answered 2022-Feb-24 at 23:23You can project the point cloud into image space, e.g., with OpenCV (as in here). That way, you can filter all points that are within the bounding box in the image space. Of course, projection errors because of differences between both sensors need to be addressed, e.g., by removing the lower and upper quartile of points regarding the distance to the LiDAR sensor. You can use the remaining points to estimate the distance, eventually.
We have such a system running and it works just fine.
QUESTION
I’m a college student and I’m trying to build an underwater robot with my team.
We plan to use stm32 and RPi. We will put our controller on stm32 and high-level algorithm (like path planning, object detection…) on Rpi. The reason we design it this way is that the controller needs to be calculated fast and high-level algorithms need more overhead.
But later I found out there is tons of package on ROS that support IMU and other attitude sensors. Therefore, I assume many people might build their controller on a board that can run ROS such as RPi.
As far as I know, RPi is slower than stm32 and has less port to connect to sensor and motor which makes me think that Rpi is not a desired place to run a controller.
So I’m wondering if I design it all wrong?
...ANSWER
Answered 2022-Feb-12 at 15:18Robot application could vary so much, the suitable structure shall be very much according to use case, so it is difficult to have a standard answer, I just share my thoughts for your reference.
In general, I think Linux SBC
(e.g. RPi) + MCU Controller
(e.g. stm32/esp32) is a good solution for many use cases. I personally use RPi + ESP32 for a few robot designs, the reason is,
- Linux is not a good realtime OS, MCU is good at handling time critical tasks, like motor control, IMU filtering;
- Some protection mechnism need to be reliable even when central "brain" hang or whole system running into low voltage;
- MCU is cheaper, smaller and flexible to distribute to any parts inside robot, it also helps our modularized design thinking;
- Many new MCU is actually powerful enough to handle sophisticated tasks and could offload a lot from the central CPU;
QUESTION
In a formation robots are linked with eachother,number of robots in a neighbourhood may vary. If one robot have 5 neighbours how can I find the angle of that one robot with its other neighbour?
...ANSWER
Answered 2021-Dec-15 at 10:03(Following a comment, I replaced the sequence of <face
+ read heading
> with just using towards
, wich I had overlooked as an option. For some reason the comment I am referring to has been deleted quickly so I don't know who gave the suggestion, but I read enough of it from the cell notification)
In NetLogo it is often possible to use turtles' heading
to know degrees.
Since your agents are linked, a first thought could be to use link-heading
, which directly reports the heading in degrees from end1 to end2.
However note that this might not be ideal: using link-heading
will work spotlessly only if you are interested in knowing the heading from end1 to end2, which means:
- If your links are directed, it reports the heading from the source to the target;
- If your links are undirected, it reports the heading from the older turtle to the younger turtle.
If that's something that you are interested in, fine. But it might not be so! For example, if you have undirected links and are interested in knowing the angle from turtle 1
to turtle 0
, using link-heading
will give you the wrong value:
QUESTION
Overlapping targetless stereo camera calibration can be done using feautre matchers in OpenCV and then using the 8-point or 5-point algoriths to estimate the Fundamental/Essential matrix and then use those to further decompose the Rotation and Translation matrices.
How to approach a non-overlapping stereo setup without a target?
Can we use visual odometry (like ORB SLAM) to calculate trajectory of both the cameras (cameras would be rigidly fixed) and then use hand-eye calibration to get the extrinsics? If yes, how can the transformations of each trajectory mapped to the gripper->base transformation and target->camera transformation? Or is there another way to apply this algorithm?
If hand-eye calibration cannot be used, is there any recommendations to achieve targetless non-overlapping stereo camera calibration?
...ANSWER
Answered 2021-Dec-08 at 03:13Hand-eye calibration is enough for your case. Just get the trajectory from each camera by running ORBSLAM. Then, calculate the relative trajectory poses on each trajectory and get extrinsic by SVD. You might need to read some papers to see how to implement this.
This is sometimes called motion-based calibration.
QUESTION
As a premise I must say I am very inexperienced with ROS.
I am trying to publish several ros messages but for every publish that I make I get the "publishing and latching message for 3.0 seconds", which looks like it is blocking for 3 seconds.
I'll leave you with an example of how I am publishing one single message:
...ANSWER
Answered 2021-Nov-29 at 18:44Part of the issue is that rostopic
CLI tools are really meant to be helpers for debugging/testing. It has certain limitations that you're seeing now. Unfortunately, you cannot remove that latching for 3 seconds message, even for 1-shot publications. Instead this is a job for an actual ROS node. It can be done in a couple of lines of Python like so:
QUESTION
A c++ novice here! The verbose in the terminal output says the problem is solved successfully, but I am not able to access the solution. What is the problem with the last line?
...ANSWER
Answered 2021-Nov-20 at 02:41You will need to change the line
QUESTION
I'm programming a robot's controller logic. On the controller there is 2 buttons. There is 3 different actions tied to 2 buttons, one occurs when only the first button is being pushed, the second when only the second is pushed, and the third when both are being pushed.
Normally when the user means to hit both buttons they would hit one after another. This has the consequence of executing a incorrect action.
Here is part of the code.
...ANSWER
Answered 2021-Oct-22 at 16:58You could use a short timer, which is restarted every time a button press is triggered. Every time the timer expires, you check all currently pressed buttons. Of course, you will need to select a good timer duration to make it possible to press two buttons "simultaneously" while keeping your application feel responsive.
You can implement a simple timer using a counter in your loop. However, at some point you will be happier with an event based architecture.
QUESTION
I'm trying to put together a programmed robot that can navigate the room by reading instructions off signs (such as bathroom-right). I'm using the AlphaBot2 kit and an RPI 3B+.
the image processing part works well, but for some reason, the MOTION CONTROL doesn't work. I wrote a simple PID controller that "feeds" the motor, but as soon as motors start turning, the robot turns off.
...ANSWER
Answered 2021-Oct-03 at 14:33It is probably not the software. Your power supply is not sufficient or stable enough to power your motors and the Raspberry Pi. It is a very common problem. Either:
- Use separate power supplies which is recommended
- Or Increase your main power supply and use some short of stabilization of power
What power supply and power configuration are you using?
QUESTION
I have read multiple resources that say the InverseKinematics class of Drake toolbox is able to solve IK in two fashions: Single-shot IK and IK trajectory optimization using cubic polynomial trajectories. (Link1 Section 4.1, Link2 Section II.B and II.C)
I have already implemented the single-shot IK for a single instant as shown below and is working, Now how do I go about doing it for a whole trajectory using dircol or something? Any documentation to refer to?
ANSWER
Answered 2021-Oct-16 at 18:09The IK cubic-polynomial is in an outdated version of Drake. You can check out https://github.com/RobotLocomotion/drake/releases/tag/last_sha_with_original_matlab. In the folder drake/matlab/systems/plants@RigidBodyManipulator/inverseKinTraj.m
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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No vulnerabilities reported
Install PX4-Avoidance
Add ROS to sources.list: sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list' sudo apt-key adv --keyserver 'hkp://keyserver.ubuntu.com:80' --recv-key C1CF6E31E6BADE8868B172B4F42ED6FBAB17C654 sudo apt update
Install ROS with Gazebo: sudo apt install ros-melodic-desktop-full # Source ROS echo "source /opt/ros/melodic/setup.bash" >> ~/.bashrc source ~/.bashrc Note We recommend you use the version of Gazebo that comes with your (full) installation of ROS. If you must to use another Gazebo version, remember to install associated ros-gazebo related packages: For Gazebo 8, sh sudo apt install ros-melodic-gazebo8-* For Gazebo 9, sudo apt install ros-melodic-gazebo9-*
Install and initialize rosdep. # for ros-melodic install: sudo apt install python-rosdep # for ros-noetic install: sudo apt install python3-rosdep rosdep init rosdep update
Install catkin and create your catkin workspace directory. sudo apt install python-catkin-tools mkdir -p ~/catkin_ws/src
Install MAVROS (version 0.29.0 or above). Note: Instructions to install MAVROS from sources can be found here. sudo apt install ros-melodic-mavros ros-melodic-mavros-extras
Install the geographiclib dataset wget https://raw.githubusercontent.com/mavlink/mavros/master/mavros/scripts/install_geographiclib_datasets.sh chmod +x install_geographiclib_datasets.sh sudo ./install_geographiclib_datasets.sh
Install avoidance module dependencies (pointcloud library and octomap). sudo apt install libpcl1 ros-melodic-octomap-*
Clone this repository in your catkin workspace in order to build the avoidance node. cd ~/catkin_ws/src git clone https://github.com/PX4/avoidance.git
Actually build the avoidance node. catkin build -w ~/catkin_ws Note that you can build the node in release mode this way: catkin build -w ~/catkin_ws --cmake-args -DCMAKE_BUILD_TYPE=Release
Source the catkin setup.bash from your catkin workspace: echo "source ~/catkin_ws/devel/setup.bash" >> ~/.bashrc source ~/.bashrc
Clone the PX4 Firmware and all its submodules (it may take some time). Build the Firmware once in order to generate SDF model files for Gazebo. This step will actually run a simulation (that you can immediately close).
Clone the PX4 Firmware and all its submodules (it may take some time). cd ~ git clone https://github.com/PX4/Firmware.git --recursive cd ~/Firmware
Install PX4 dependencies. # Install PX4 "common" dependencies. ./Tools/setup/ubuntu.sh --no-sim-tools --no-nuttx # Gstreamer plugins (for Gazebo camera) sudo apt install gstreamer1.0-plugins-bad gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-ugly libgstreamer-plugins-base1.0-dev
Build the Firmware once in order to generate SDF model files for Gazebo. This step will actually run a simulation (that you can immediately close). # This is necessary to prevent some Qt-related errors (feel free to try to omit it) export QT_X11_NO_MITSHM=1 # Build and run simulation make px4_sitl_default gazebo # Quit the simulation (Ctrl+C) # Setup some more Gazebo-related environment variables (modify this line based on the location of the Firmware folder on your machine) . ~/Firmware/Tools/setup_gazebo.bash ~/Firmware ~/Firmware/build/px4_sitl_default
Add the Firmware directory to ROS_PACKAGE_PATH so that ROS can start PX4: export ROS_PACKAGE_PATH=${ROS_PACKAGE_PATH}:~/Firmware
Finally, set the GAZEBO_MODEL_PATH in your bashrc: echo "export GAZEBO_MODEL_PATH=${GAZEBO_MODEL_PATH}:~/catkin_ws/src/avoidance/avoidance/sim/models:~/catkin_ws/src/avoidance/avoidance/sim/worlds" >> ~/.bashrc
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