I have merged the omni_bot base with the torso of Robbie
The integration of three omni wheels with encoders has significantly enhanced and simplified the robot's odometry. Precise measurements of wheel rotations from the encoders enable accurate localization and mapping of the environment, resulting in more reliable navigation.
By leveraging Nav2 and slam_toolbox for navigation, the robot benefits from powerful out-of-the-box navigation capabilities. These robust ROS packages facilitate autonomous path planning, obstacle avoidance, and efficient goal-reaching, minimizing the need for extensive modifications.
The adoption of the differential drive plugin for navigation has greatly reduced fishing motion in the Y-space, resulting in smoother and more fluid movement
Replacing the RPI4 with an I5 mini PC running Ubuntu 22.4 and ROS Humble significantly boosts computing power and reliability. The I5 mini PC offers faster processing speeds, improved multitasking capabilities, and better software compatibility, simplifying installation and ensuring a stable platform. Eliminating the Timing Issues by Centralizing Nodes on I5: Centralizing all nodes on the I5 mini PC resolves timing issues observed in the previous setup. Improved synchronization and coordination between nodes result in smoother communication and minimized delays, enhancing performance and responsiveness.
Autodock functionality now incorporates strafing moves, enabling precise alignment with the docking beacon. This refinement enhances the accuracy and efficiency of the docking process.
The low power monitor program has been enhanced to incorporate additional functionality. Utilizing a QR marker and the rear-facing camera, the robot can accurately rotate to the correct angle before initiating Autodock. This improvement ensures precise alignment and eliminates potential errors during docking.
Control and day-to-day operation of the robot are seamlessly achieved using the existing chat bot, which now supports custom commands. Unknown commands are recorded for further integration into AIML, continuously improving the system's understanding and response capabilities. Text-based input simplifies interaction, enabling smooth communication between users and the robot platform.