Robohub.org
 

Drive kinematics: Skid steer and mecanum (ROS twist included)


by
19 July 2016



share this:
Photo: Wikipedia

Photo: Wikipedia

I am often in need of the basic kinematic motion equations for skid steer vehicles. I have also recently been working with mecanum wheeled vehicles. The skid steer equations are fairly simple and easy to find, however, I will include it in different versions and include a ROS approach. The mecanum wheel equations are harder to find and there are different versions floating around. The first version I found had a lot of trig and mostly worked. The version I present here is easier to intuitively understand and seems to work better (I don’t need a random scale factor for this version), I also include a ROS approach for them.

Skid Steer / Differential Drive

Here is some math for 2 and 4 wheel differential drive vehicles, 2 wheels and a castor, or skid steer tracked vehicles.

Arc based commands

The basic skid steer equations are:

velocity_right = w(RADIUS_OF_ARC_TO_DRIVE + WHEEL_BASE/2)
velocity_left = w(RADIUS_OF_ARC_TO_DRIVE – WHEEL_BASE/2)

Where w is the angular rotation, RADIUS_OF_ARC_TO_DRIVE is the arc radius that the robot should drive, and the WHEEL_BASE is the distance from the center of the left wheel to the center of the right wheel (See image above).

This can also be written as:

w = (velocity_right-velocity_left)/WHEEL_BASE

There are two special cases:

IF velocity_right == velocity_left :
THEN the radius of the arc is infinite so the robot will drive straight.

IF velocity_right == -velocity_left :
THEN the radius of the arc is 0, and the robot rotates in place (ie. point turn)

Linear & Angular Velocity Commands for ROS

In ROS if using the Twist topic (which is the default for drive messages) (message name is often cmd_vel) you will often set linear_velocity in the linear.x field and angular_velocity in the angular.zfield.

velocity_left_cmd = (linear_velocity – angular_velocity * WHEEL_BASE / 2.0)/WHEEL_RADIUS;

velocity_right_cmd = (linear_velocity + angular_velocity * WHEEL_BASE / 2.0)/WHEEL_RADIUS;

Mecanum Wheel Math

 

Mecanum wheels from Andymark

Mecanum wheels from Andymark

In ROS if using the Twist message you will often set the linear.x, linear.y and angular.z fields. One unrelated note is that if you are operating on uneven terrain then doing mecanum type motions will fail and have a lot of slip. Skid steer type motions will often work better (using the mecanum wheels).

WHEEL_SEPARATION_WIDTH = DISTANCE_LEFT_TO_RIGHT_WHEEL / 2

WHEEL_SEPARATION_LENGTH = DISTANCE_FRONT_TO_REAR_WHEEL / 2

Forward kinematics

Wheel commands units are in rad/s

wheel_front_left = (1/WHEEL_RADIUS) * (linear.x – linear.y – (WHEEL_SEPARATION_WIDTH + WHEEL_SEPARATION_LENGTH)*angular.z);

wheel_front_right = (1/WHEEL_RADIUS) * (linear.x + linear.y + (WHEEL_SEPARATION_WIDTH + WHEEL_SEPARATION_LENGTH)*angular.z);

wheel_rear_left = (1/WHEEL_RADIUS) * (linear.x + linear.y – (WHEEL_SEPARATION_WIDTH + WHEEL_SEPARATION_LENGTH)*angular.z);

wheel_rear_right = (1/WHEEL_RADIUS) * (linear.x – linear.y + (WHEEL_SEPARATION_WIDTH + WHEEL_SEPARATION_LENGTH)*angular.z);

To drive a robot you will probably need to also invert one side since the motors are mounted opposite the other side. For example:

wheel_front_right = -1 * wheel_front_right

wheel_rear_right = -1 * wheel_rear_right

Also this gives an output in rad/s. If your motor controller is operating with encoder counts as the unit you will need to convert the units.

Inverse Kinematics

linear.x = (wheel_front_left + wheel_front_right + wheel_rear_left + wheel_rear_right) * (WHEEL_RADIUS/4)

linear.y = ( -wheel_front_left + wheel_front_right + wheel_rear_left – wheel_rear_right) * (WHEEL_RADIUS/4)

angular.z = ( -wheel_front_left + wheel_front_right – wheel_rear_left + wheel_rear_right) * (WHEEL_RADIUS/(4 * (WHEEL_SEPARATION_WIDTH + WHEEL_SEPARATION_LENGTH)))

Source for mecanum wheel math: here. There are other versions of how to compute the wheel velocities but this is the one I like best.

If you have any pressing questions, visit the Robots for Roboticists Forum.


The post “Drive Kinematics: Skid Steer & Mecanum (ROS Twist included)” appeared on Robots For Roboticists.



tags:


Robots for Roboticists David Kohanbash is a Robotics Engineer in Pittsburgh, PA in the United States. He loves building, playing and working with Robots.
Robots for Roboticists David Kohanbash is a Robotics Engineer in Pittsburgh, PA in the United States. He loves building, playing and working with Robots.

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

Table tennis robot defeats some of world’s best players – why this has major implications for robotics

  18 May 2026
Ace, from Sony AI, is the first robot to beat elite human players in competitive physical sport.

Robot Talk Episode 156 – Rugged robots for dangerous missions, with Gavin Kenneally

  15 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Gavin Kenneally from Ghost Robotics about robot dogs for defence, security, and public safety.

Developing active and flexible microrobots

  13 May 2026
This class of robots opens up possibilities for biomedical applications.

How to teach the same skill to different robots

  11 May 2026
A new framework to teach a skill to robots with different mechanical designs, allowing them to carry out the same task without rewriting code for each.

Robot Talk Episode 155 – Making aerial robots smarter, with Melissa Greeff

  08 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Melissa Greeff from Queen's University about autonomous navigation and learning for drones.

New understanding of insect flight points way to stable flapping-wing robots

  07 May 2026
The way bugs and birds flap their wings may look effortless, but the dynamics that keep them aloft are dizzyingly complex and difficult to quantify.

Robotically assembled building blocks could make construction more efficient and sustainable

  05 May 2026
Research suggests constructing a simple building from interlocking subunits should be mechanically feasible and have a much smaller carbon footprint.

Robot Talk Episode 154 – Visual navigation in insects and robots, with Andrew Philippides

  01 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Andrew Philippides from the University of Sussex about what we can learn from ants and bees to improve robot navigation.



AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence