Many technological systems, including mobile robots, are being controlled by intelligent and skilled systems that are being created. On the other hand, a quick low-level control method that is frequently employed in control engineering jobs is the PID (Proportional-Integral-Derivative) controller. To determine the gains of PID controllers under certain operating circumstances, many tuning techniques from classical control theory have been used. This paper firstly conducts a thorough survey of modern strategies for adjusting PID parameters using metaheristic algorithms to improve the performance of autonomous robots. The problems in different scenarios of changing the parameters are considered including in specific robot models. The methods are classified and evaluated in details. The most common algorithms are considered to be able to change the parameters GA, PSO, FLC, and others. The methods are analyzed, simulated and evaluated in specific cases. Simulation results on Matlab show that the metaheuristic algorithms help reduce errors and increase the stability of mobile robots compared to other methods. Finally, some proposals and future research directions for the parameter optimization problem of PID will be discussed.