Autonomous Navigation Using Partial Artificial Potential Fields On Differential Drive Turtlebot
Syed Ali Shahbaz, Abhijith Anil Anjana · 2018
Artificial Potential Fields algorithm has been around for quite some time as a satisfactory solution for Autonomous Navigation. It provides a smooth navigation of any robot from one point to another. It does, however, suffers from a prominent set-back commonly known as the Local Minima, where the robot tends to get stuck behind convex shaped obstacles. There are a few solutions to this set-back within Artificial Potential Fields, however their application and efficiency might vary depending on the hardware in use. This Paper proposes a novel algorithm which overcomes the Local Minima problem very effectively and works well with almost every hardware setup. The new algorithm was tested over 6 different scenarios, and in each scenario, the run was successful, overcoming the Local Minima problem with ease and a hundred percent success rate.