Introduction

Without the capacity to accomplish things on their own, robots would be quite worthless. Robots are on their approach to becoming totally autonomous today, thanks to ever more advanced machine learning algorithms. Planning, Controls, and State Estimation comprises Automation.

We must plan our actions from the minute we get up in the morning until our heads hit the pillow at night. A major challenge in developing autonomous robots is figuring out how to give them the ability to make their own decisions in a range of settings. The computational process of travelling from one location to another in the presence of barriers is known as motion planning.

A robot’s movements and sensory processing are controlled by the Robot control system.We require robot controllers since the dynamics (system plant) change over time. For example, when the robot travels up and down a slope, or when it travels on smooth concrete before moving to a carpeted floor.

Estimating a robot’s state, such as location and orientation, as it moves around the world is a fundamental part of robotics today. To locate themselves in a three-dimensional world, most robots and autonomous vehicles rely on noisy data from sensors such as cameras or laser rangefinders, or a combination of these.