Motion Planning
Motion planning is a computational problem in robotics and autonomous systems that involves determining a sequence of valid configurations or states to move an object from a start to a goal while avoiding obstacles and satisfying constraints. It is fundamental for enabling robots, vehicles, and virtual agents to navigate and manipulate objects in complex environments. Algorithms for motion planning typically consider factors like kinematics, dynamics, and environmental uncertainty to generate safe and efficient paths.
Developers should learn motion planning when working on robotics, autonomous vehicles, video game AI, or industrial automation, as it is essential for creating systems that can move intelligently in real-world or simulated spaces. It is particularly valuable for applications requiring pathfinding, collision avoidance, and multi-agent coordination, such as self-driving cars, drone navigation, or robotic arms in manufacturing.