# A Novel Potential Field Controller for Use on Aerial Robots

## TL;DR

This paper introduces an extended potential field controller (ePFC) for aerial robots that improves target tracking and obstacle avoidance, validated through simulations and laboratory experiments.

## Contribution

The paper presents a novel extended potential field controller that enhances drone navigation by ensuring smoother paths and faster settling times compared to traditional methods.

## Key findings

- ePFC achieves smoother tracking paths
- ePFC has shorter settling times
- Controller effectiveness demonstrated in lab experiments

## Abstract

Unmanned Aerial Vehicles (UAV), commonly known as drones, have many potential uses in real world applications. Drones require advanced planning and navigation algorithms to enable them to safely move through and interact with the world around them. This paper presents an extended potential field controller (ePFC) which enables an aerial robot, or drone, to safely track a dynamic target location while simultaneously avoiding any obstacles in its path. The ePFC outperforms a traditional potential field controller (PFC) with smoother tracking paths and shorter settling times. The proposed ePFC's stability is evaluated by Lyapunov approach, and its performance is simulated in a Matlab environment. Finally, the controller is implemented on an experimental platform in a laboratory environment which demonstrates the effectiveness of the controller.