Publication: Automated route planning with obstacle avoidance for unmanned aerial systems
Loading...
Date
2021-10-01
Authors
Debnath, Dipraj
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Autonomous unmanned aerial systems (UAS) are increasingly becoming a major focus of study in both academia and industrial sectors. With the aim of resolving the path planning issue, this study adopts the travelling salesmen problem (TSP) and solve it by applying an Improved Genetic Algorithm (IGA) that can identify the optimal way in terms of both distance and time. The outcome shows that the approach of the GA is relatively effective in finding not only the optimum path distance but also minimize and in some cases eliminate the crossing paths. Another value-added feature for UAS is to be equipped with a reliable obstacle detection and avoidance system especially when it operates in low-flying zone. The obstacles can be considered as a hindrance to the UAS flight path, and the algorithm should detect and avoid it through avoidance waypoints. The avoidance approach proposes here combines the linear equation and locating its intersection points between the diagonal lines within the square area. Based on that, the square areas are used to guide the algorithm to compute new safe avoiding waypoints. The size of the square areas is based on the safe avoidance distance defined based on the UAS specification such as size, speed and UAS type. All Algorithms here are created in MATLAB and then tested and assessed in several scenarios where the UAS must avoid obstacles during operation. The result from this research shows that the algorithms can provide reasonable solutions in finding the optimal path and avoiding obstacles based on the scenarios. Therefore, this approach is very helpful for any UAS that need a pre-plan mission prior to the actual flight operation.