Path Planning and Motion Control: Current Methods, Challenges, and Future Perspectives

Abstract

Path planning and motion control are two important engineering and technology disciplines that support the success of autonomous systems. Path planning calculates the best path for a vehicle or robot to take from its starting point to its goal, while motion control ensures that it is followed exactly. These methods have a wide range of applications, from autonomous vehicles to industrial robots, from drone technologies to spacecraft. In recent years, developments in artificial intelligence, machine learning, and sensor technologies have revolutionized these areas. In addition, real-time data processing accelerates decision-making processes and offers the opportunity for use in more complex environments. Path planning methods are handled with various algorithms depending on the structure of the environment and the requirements. Artificial intelligence-based methods come into play in solving more complex problems. Path planning and motion control play a critical role in the success of autonomous systems. Developing technologies enable these fields to provide solutions to more complex and dynamic problems. In the future, it is expected that smarter and safer systems will be developed through the integrated work of these two disciplines. This review article aims to address the development process of the subject in the literature, application areas, challenges encountered, and future trends.