This study addresses the performance limitations of conventional PID controllers in omniwheel mobile robots navigating surfaces with different friction coefficients, a frequent challenge in industrial and logistics automation. The inflexibility of standard controllers on varying surfaces can lead to reduced operational stability and higher energy consumption. To improve adaptability, this research develops a hybrid Fuzzy-PID control system. This approach utilizes fuzzy logic to continuously modulate the PID parameters in real-time, using the system’s error and its rate of change as inputs. The proposed controller was evaluated on an omnidirectional robotic platform tested across two distinct surfaces: regular flooring and carpet, representing different frictional environments. Experimental results indicate that the Fuzzy-PID controller offers improvements in stability and responsiveness over the conventional PID method. It demonstrated an ability to maintain consistent velocity tracking and minimized steady-state error, even during transitions between surface types. The findings suggest that this adaptive control strategy can contribute to more consistent robotic navigation in dynamic settings. This work supports the application of intelligent control systems in areas such as smart warehouses, aligning with broader goals for sustainable and efficient automation solutions.
Sidharta et al. (Thu,) studied this question.