A review on mobile robots motion path planning in unknown environments

Robotics sector have achieved enormous founds in recent years due to its high demands in factories to carry out high-precision jobs like riveting and welding. They are also often applied in special situations that would be hazardous for humans such as disposing toxic wastes or defusing bombs. Mobile robots alone however have gained much focus from researches relating optimization of their motion path planning. In this paper, a brief review on mobile robots motion path planning in unknown environment have been done based on recent founds. The paper categorizes motion path planning into two groups which is the Optimized Classic Approaches and Evolutionary and Hybrid Approaches. The optimized classic approaches represents the recent optimized motion path planning that implies the classic approaches such as A* search algorithm, Rapidly-exploring Random Trees (RRT), D* and D* Lite algorithm. The evolutionary and hybrid approaches are those adapts Artificial Intelligence (AI) such as neural networks (NN), genetic algorithms (GA), fuzzy systems and reinforced learning either acting alone or as hybrids together with other algorithms. Finally a comparison between these two categories are done differentiating their advantages and disadvantages.