Real-Time Heuristic Framework for Safe Landing of UAVs in Dynamic Scenarios

TL;DR

This paper introduces a heuristic framework for UAVs to identify and select safe landing zones in dynamic environments, enhancing safety during critical landing scenarios.

Contribution

It proposes a novel multi-phase heuristic approach combining image processing and obstacle velocity analysis for safe UAV landing in real-time.

Findings

Effective detection of safe landing zones using canny edge algorithm

Dynamic obstacle velocity estimation improves landing safety

Real-world testing shows better performance than existing methods

Abstract

The world we live in is full of technology and with each passing day the advancement and usage of UAVs increases efficiently. As a result of the many application scenarios, there are some missions where the UAVs are vulnerable to external disruptions, such as a ground station's loss of connectivity, security missions, safety concerns, and delivery-related missions. Therefore, depending on the scenario, this could affect the operations and result in the safe landing of UAVs. Hence, this paper presents a heuristic approach towards safe landing of multi-rotor UAVs in the dynamic environments. The aim of this approach is to detect safe potential landing zones - PLZ, and find out the best one to land in. The PLZ is initially, detected by processing an image through the canny edge algorithm, and then the diameter-area estimation is applied for each region with minimal edges. The spots that have a higher area than the vehicle's clearance are labeled as safe PLZ. Onto the second phase of this approach, the velocities of dynamic obstacles that are moving towards the PLZs are calculated and their time to reach the zones are taken into consideration. The ETA of the UAV is calculated and during the descending of UAV, the dynamic obstacle avoidance is executed. The approach tested on the real-world environments have shown better results from existing work.