Review on Robot Path Planning using Nature-Inspired Algorithms

Abstract

Developing paths for robots is one of the most popular topics of study in robotics. Focus on the robot's movement from the starting or source point to the destination or target position, avoiding obstacles along the way, and finally paying special attention to reaching the destination with the optimal path. However, this process is not so simple because numerous conditions must be followed to achieve the desired outcome. Working in various situations, with known or unknown aims, etc., conservative methods are ineffective due to their limits. To address this issue, nature-inspired algorithms are utilized for path planning. These methods are well-suited for various optimization problems. Optimization is used for path-planning techniques that use algorithms inspired by nature that perform well in a wide variety of situations. , boosting the overall efficiency of these algorithms. Path planning is the process of determining the best or near-best route between two points in a given environment while avoiding barriers and other constraints. This is a big problem in several fields, including robotics, self-driving cars, computer graphics, and video games. The goal of path planning is to find practical solutions that meet the following requirements. Connect starting points and destination points, avoid obstacles and other environmental constraints, optimize specific performance metrics such as distance, time, and energy, and understand the dynamic nature of the environment and what might occur during execution. Consider a change in these insights that can be practically applied to active ingredients that are critical to achieving optimal performance.