Much like competitors of the DARPA Grand Challenge, this robot was programmed to make its way through an outdoor course going to various GPS centered orange cones as waypoints. The vehicle must avoid obstacles while navigating to locations that are initially out of line-of-site.

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    The Robomagellan competition is probably one of the most involved and difficult competitions at Robogames. In 2018, I began building an RC-scale robot that could autonomously navigate and drive without any input from an operator. It avoided static and dynamic obstacles such as trees and people to arrive safely at its destination. Designing, construction, and programming required an enormous breadth of interdisciplinary engineering concepts. Pulling concepts from fields such as computer science, computer engineering, mechanical engineering, and electrical engineering, this vehicle relies on data acquisition, data analysis, perception, environment modeling, sensor fusion, and path planning. It’s almost as though there is not a single field of engineering this project did not touch on. This system is based on ROS (Robotic Operating System) and utilized common sensors such as GPS, LIDAR, USRF and machine vision for environment perception.