Online planning of topologically distinctive autonomous drone trajectories

Abstract

Technology’s constant growth in robotics sensor, microcontroller and seams miniature based technology has helped drones develop quickly, reliably, and at low cost. This matters for making better transportation systems in smart cities. Autonomous drones are extensively employed for testing various algorithms and replicating the behavior of unmanned aerial vehicles (UAVs) in real-world scenarios. Over the past ten years [1], numerous methods have been put forward to tackle the challenge of avoiding obstacles in autonomous drones. The obstacle avoidance and path planning are indeed major challenges in the development and operation of autonomous drones. To handle these challenges by an obstacle mapping algorithm that utilizes techniques such as A-star and TEB (Time Elastic Band) parallel path planning within the Robot Operating System (ROS) to meticulously build a comprehensive 3D map of the environment. In this paper, Utilizing a Raspberry Pi and a Light Detection and Ranging (LIDAR) module, the autonomous drone can effectively navigate even in environments with low levels of combination. The comparison of the effectiveness of the proposed A-star and TEBparallel path planning. TEB is 10.624 percent better than A-star in a 30m range simulation environment.