Mobil manipulatörlerin hassas konumkontrolü

Mobile robots function as robotic systems which enable movement through locomotion to execute tasks within unstructured and dynamic environments. The main control challenge of mobile manipulation tasks remains the motion coordination between the mobile base and the manipulator arm because of the complexity that makes simple control architectures impractical. The use of Mecanum wheels on omnidirectional platforms introduces additional challenges because their high maneuverability comes with mechanical wheel slippage which creates substantial uncertainty in position estimation. The proposed research implements an adaptive PID control algorithm that adjusts its control gains based on the size of the tracking error. The research developed an absolute positioning and orientation estimation system that functions in real-time without external sensors to enable closed-loop position tracking. A mobile manipulator system consisting of a mecanum-wheeled base and a 6-degree-of-freedom industrial robotic arm executed coordinated motion during the research. The evaluation of three trajectory types (trapezoidal, square, and circular) at four velocity levels from 100–400 mm/s was conducted through both simulated and physical experiments. The adaptive control technique achieves precise trajectory tracking at the millimeter level during low-speed operations. The synchronized motion approach which enables base and manipulator movement together reduces total task duration by 42.5% compared to stop-and-go execution. The research proves that adaptive gain control through error measurements delivers better results and demonstrates synchronized motion improves mobile manipulation performance.