Development of an Autonomous Omnidirectional Robot for Obstacle Avoidance Using Potential Fields

This work presents the development of an omnidirectional mobile robot with four Mecanum wheels, implementing potential fields algorithm for trajectory generation and obstacle avoidance achieving autonomy on our robot. The processing unit is Nvidia Jetson Nano, a single-board computer compatible with Robot Operating System, enabling communication through topics and nodes. Additionally, an ESP32 microcontroller is used for motor control and a LiDAR sensor is incorporated to get information from environment. Communication between the processing unit and nodes through topics ensures efficient data transfer. This combination, along with effective design and construction, aims to develop an autonomous omnidirectional robot capable of obstacle evasion. Experimental results demonstrate the effectiveness of the evasion technique used.