Ackermann Steering ROS Robot Car Chassis with Dual Encoder Motors, Front Servo Steering, Finished Single-Layer Platform for Accurate Odometry, Motion Control, SLAM Mapping and Autonomous Navigation Learning

This Ackermann steering robot car chassis is designed as a professional robotics learning and development platform, built to simulate real vehicle steering behavior rather than simplified differential drive motion. By adopting true Ackermann steering geometry, the front wheels turn at different angles during cornering, closely matching real automotive kinematics. This makes the chassis highly suitable for ROS robot car development, autonomous navigation research, and robotics education that requires realistic motion modeling and steering control.

The chassis is equipped with dual encoder DC motors that provide precise wheel speed feedback and accurate distance measurement for advanced odometry calculation. Encoder data enables closed-loop motor control, real-time motion correction, and stable velocity regulation, which are essential for SLAM mapping, robot localization, and trajectory planning. Compared with open-loop motor systems, this encoder-based design significantly improves motion accuracy and long-distance stability during autonomous operation.

A front servo steering system delivers accurate angular control and smooth turning behavior, allowing learners to study steering kinematics, turning radius calculation, and path-following algorithms. The finished single-layer platform structure simplifies hardware integration, making it easy to mount controllers, sensors, and expansion modules while maintaining mechanical rigidity and accessibility for experimentation and modification.

This robot car chassis serves as a solid foundation for ROS navigation stack experiments, AI robot vehicle research, and programming robot projects that require realistic steering behavior. It is well suited for universities, laboratories, and STEM programs seeking to bridge theoretical robotics algorithms with real-world vehicle dynamics through hands-on learning and research-oriented development.