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Here is the first experimental test of my ROS/Python implementation of the dead reckoning algorithm for tracking mobile robot location and orientation in space. I am only using two-wheel encoder readings to reconstruct the position and orientation. Later on, I will integrate IMUs. I am also using RViz to display and visualize the reconstructed robot's position and orientation in real-time. The RVIZ real-time visualization is generated on the basis of the quaternions and coordinate transformations computed on the basis of the dead reckoning estimates. It took me at least a week to implement everything from scratch and to figure out what works. To do something like this, you have to understand robot kinematics, ROS, Python coding, and hardware, and most importantly, to be persistent.
The computer and robot communicate via a Bluetooth module. Both the computer and the robot run several ROS nodes. The computer runs a ROS node written in Python that implements the dead reckoning algorithm. All the communication is performed by using ROS topics. This is just the first test. Currently, the robot is kept as simple as possible since I do not want to waste time designing and optimizing hardware before testing basic principles. In the future, I will 3D print a larger robot and install more advanced sensors and computing hardware. The complete tutorial will come out soon.
Here is the dead reckoning algorithm I implemented:
https://lnkd.in/gKxtdQTf
Watch video First Test of ROS Implementation of Dead Reckoning and Real-Time Robot Visualization in RViz- online, duration hours minute second in high quality that is uploaded to the channel Aleksandar Haber PhD 01 February 2024. Share the link to the video on social media so that your subscribers and friends will also watch this video. This video clip has been viewed 1,238 times and liked it 41 visitors.