A Unified simulation and hardware framework for path planning in wheeled mobile robots with 2D augmented reality-based sensing

This paper presents an interactive robotic test platform simulator for developing and evaluating path planning algorithms in wheeled mobile robots. The framework operates in three modes—simulation, predefined waypoint testing, and real-time execution—providing flexibility for both research and education. In simulation mode, the platform models differential drive and mecanum robots with modular forward and inverse kinematics, enabling customizable dimensions and velocity inputs. Waypoint testing mode supports repeatable path evaluation for benchmarking algorithms. In real-time mode, an overhead camera with ArUco marker-based pose estimation maps robot motion into a 2D environment, using camera calibration and homography to convert frame waypoints into real-world coordinates. A key feature of the system is its 2D augmented reality capability, which enables the creation of virtual obstacles and sensor fields that interact with the robot as if they existed physically, enhancing experimentation without additional hardware. Waypoints can be generated algorithmically or interactively and transmitted as wheel velocity commands to the robot. By combining simulation, structured testing, augmented reality, and hardware integration, the platform bridges the gap between theoretical algorithm design and practical implementation.