CMakeLists.txt 仅有检测到安装了ROS且为ROS1时才编译main_ros_app目录下的应用程序
message(STATUS "ros_version:$ENV{ROS_VERSION}" " ros:$ENV{ROS_DISTRO}")
if( "$ENV{ROS_VERSION}" STREQUAL "1" AND DEFINED ENV{ROS_DISTRO} )
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/main_ros_app/)
message("Infor: found ROS1, ros app will be build!")
else()
message("Warning: Can't found ROS1, so ignore ros app!")
endif()
1、问题背景
数据发送端数据检测正常；rviz端能正确接收到nav_msgs::Path消息对应的topic，且状态显示OK,而且消息计数也在增加，
但就是不显示轨迹。
2、问题原因
nav_msgs::Path path_msg;
变量的定义在发送topic的函数内部，不是全局变量，意味着每次发送path_msg时都新建了一个nav_msgs::Path消息。
3、解决办法
nav_msgs::Path path_msg;
将上述变量移到函数之外，编程全局变量.
4、rostopic echo xxx
有问题时的topic
没有问题时看到的topic格式:
1、URL
https://control.ros.org/rolling/doc/ros2_controllers/doc/mobile_robot_kinematics.html
You're reading the documentation for a development version. For the latest released version, please have a look at Jazzy.
This page introduces the kinematics of different wheeled mobile robots. For further reference see Siciliano et.al - Robotics: Modelling, Planning and Control and Kevin M. Lynch and Frank C. Park - Modern Robotics: Mechanics, Planning, And Control.
Wheeled mobile robots can be classified in two categories:
which can move instantaneously in any direction in the plane, and
which cannot move instantaneously in any direction in the plane.
The forward integration of the kinematic model using the encoders of the wheel actuators — is referred to as odometric localization or passive localization or dead reckoning. We will call it just odometry.
The below explains the kinematics of omnidirectional drive robots using 3 or more omni wheels.It follows the coordinate conventions defined in ROS REP 103.
is the robot’s body-frame coordinate system, located at the contact point of the wheel on the ground.
is the world coordinate system.
is the robot’s linear velocity on the x-axis.
is the robot’s linear velocity on the y-axis.
is the robot’s angular velocity on the z-axis.
is the robot’s radius / the distance between the robot’s center and the wheels.
Red arrows on the wheel
.
is the number of wheels.
Inverse Kinematics
The necessary angular velocity of the wheels to achieve a desired body twist can be calculated using the below matrix:
Here are the angular velocities of the wheels and is the radius of the wheels.These equations can be written in algebraic form for any wheellike this:
Forward Kinematics
The body twist of the robot can be obtained from the wheel velocities by using the pseudoinverse of matrix
.
The below explains the kinematics of omnidirectional drive robots using four swerve modules, each with independently controlled steering and driving motors. It follows the coordinate conventions defined in REP-103.
is the robot’s body-frame coordinate system, located at the geometric center of the robot.
is the world coordinate system.
is the robot’s linear velocity on the x-axis.
is the robot’s linear velocity on the y-axis.
is the robot’s angular velocity on the z-axis.
is the wheelbase (distance between front and rear wheels).
is the track width (distance between left and right wheels).
Red arrows on wheel
.
Each swerve module
, for (typically front-left, front-right, back-left, back-right) is located atrelative to the center, typically:
Front-left:
Front-right:
Back-left:
Back-right:
Inverse Kinematics
For each module
at position, the velocity vector is:
The wheel velocity and steering angleare:
Odometry
The body twist of the robot is computed from the wheel velocities
and steering angles. Each module’s velocity components in the body frame are:
The chassis velocities are calculated as:
Odometry updates the robot’s pose (, ,) in the global frame using the computed chassis velocities. The global velocities are:
To define the coordinate systems (ROS coordinate frame conventions, the coordinate systems follow the right-hand rule), consider the following simple unicycle model
is the robot’s body-frame coordinate system, located at the contact point of the wheel on the ground.
is the world coordinate system.
are the robot’s Cartesian coordinates in the world coordinate system.
-axis.
In the following, we want to command the robot with a desired body twist
where is the linear velocity of the robot in its body-frame, andis the angular velocity of the robot in its body-frame. As we consider steering robots on a flat surface, it is sufficient to give
axis.
axis.
as desired system inputs. The forward kinematics of the unicycle can be calculated with
We will formulate the inverse kinematics to calculate the desired commands for the robot (wheel speed or steering) from the given body twist.
Citing Siciliano et.al - Robotics: Modelling, Planning and Control:
A unicycle in the strict sense (i.e., a vehicle equipped with a single wheel)is a robot with a serious problem of balance in static conditions. However,there exist vehicles that are kinematically equivalent to a unicycle but morestable from a mechanical viewpoint.One of these vehicles is the differential drive robot, which has two wheels, each of which is driven independently.
is the wheel track (the distance between the wheels).
Forward Kinematics
The forward kinematics of the differential drive model can be calculated from the unicycle model above using
Inverse Kinematics
The necessary wheel speeds to achieve a desired body twist can be calculated with:
Odometry
We can use the forward kinematics equations above to calculate the robot’s odometry directly from the encoder readings.
The following picture shows a car-like robot with two wheels, where the front wheel is steerable. This model is also known as the bicycle model.
-axis.
is the velocity of the rear and front wheel.
is the wheelbase.
We assume that the wheels are rolling without slipping. This means that the velocity of the contact point of the wheel with the ground is zero and the wheel’s velocity points in the direction perpendicular to the wheel’s axis. The Instantaneous Center of Rotation (ICR), i.e. the center of the circle around which the robot rotates, is located at the intersection of the lines that are perpendicular to the wheels’ axes and pass through the contact points of the wheels with the ground.
As a consequence of the no-slip condition, the velocity of the two wheels must satisfy the following constraint:
Forward Kinematics
The forward kinematics of the car-like model can be calculated with
Inverse Kinematics
The steering angle is one command input of the robot:
For the rear-wheel drive, the velocity of the rear wheel is the second input of the robot:
For the front-wheel drive, the velocity of the front wheel is the second input of the robot:
Odometry
We have to distinguish between two cases: Encoders on the rear wheel or on the front wheel.
For the rear wheel case:
For the front wheel case:
The following image shows a car-like robot with three wheels, with two independent traction wheels at the rear.
is the wheel track of the rear axle.
Forward Kinematics
The forward kinematics is the same as the car-like model above.
Inverse Kinematics
The turning radius of the robot is
Then the velocity of the rear wheels must satisfy these conditions to avoid skidding
Odometry
The calculation of
from two encoder measurements of the traction axle is overdetermined.If there is no slip and the encoders are ideal,
holds. But to get a more robust solution, we take the average of both , i.e.,
The following image shows a four-wheeled robot with two independent steering wheels in the front.
is the wheel track of the front axle, measured between the two kingpins.
To prevent the front wheels from slipping, the steering angle of the front wheels cannot be equal.This is the so-called Ackermann steering.
Note
Ackermann steering can also be achieved by a mechanical linkage between the two front wheels. In this case the robot has only one steering input, and the steering angle of the two front wheels is mechanically coupled. The inverse kinematics of the robot will then be the same as in the car-like model above.
Forward Kinematics
The forward kinematics is the same as for the car-like model above.
Inverse Kinematics
The turning radius of the robot is
Then the steering angles of the front wheels must satisfy these conditions to avoid skidding
Odometry
The calculation of
from two angle measurements of the steering axle is overdetermined.If there is no slip and the measurements are ideal,
holds. But to get a more robust solution, we take the average of both , i.e.,
The following image shows a four-wheeled car-like robot with two independent steering wheels at the front, which are also driven independently.
is the distance from the kingpin to the contact point of the front wheel with the ground.
Forward Kinematics
The forward kinematics is the same as the car-like model above.
Inverse Kinematics
To avoid slipping of the front wheels, the velocity of the front wheels cannot be equal and
with turning radius of the robot and the left/right front wheel
This results in the following inverse kinematics equations
with the steering angles of the front wheels from the Ackermann steering equations above.
Odometry
The calculation of
from two encoder measurements of the traction axle is again overdetermined.If there is no slip and the encoders are ideal,
holds. But to get a more robust solution, we take the average of both , i.e.,
