A South African-based researcher from Stellenbosch University has developed algorithms that can prevent unmanned aerial vehicle (UAV) collisions.
This, as automation has led to an increase in the use of UAVs, commonly known as drones, in many fields, ranging from the film industry to agricultural applications to military operations.
Stellenbosch University says this boom has created new challenges for automation to overcome, such as the need for UAVs to fly in crowded airspaces and avoid colliding with each other.
To help address the deficiency in inter-UAV collision avoidance capabilities, the varsity says Dr Lauren Meiring developed and evaluated co-operative collision avoidance algorithms for UAVs that are capable of avoiding short-term collisions with static and dynamic obstacles, as well as collisions between UAVs while communicating their positions, velocities and intended flight trajectories in complex environments.
Meiring recently obtained her doctorate in Electronic Engineering at Stellenbosch University. The title of her thesis was “Cooperative collision avoidance strategies for unmanned aerial vehicles”.
A recent report by IndustryArc found the South African small drones market is estimated to reach $134.5 million by 2025, growing at a CAGR of 22.35% from 2020 to 2025.
In South Africa, it says, the growth of the mining industry, developments in more data accurate drone technology, presence of the dominant players in hardware, as well as niche applications are driving the growth of the market.
“Currently, there is no commonly implemented collision avoidance system that prevents inter-UAV collisions,” Meiring says.
“Some commercially available UAVs do implement collision avoidance, but only for static obstacles. When UAVs are equipped with inter-UAV collision avoidance, it is normally to achieve a specialised task and, as such, is not applicable to independent UAVs performing individual tasks.
“These UAVs are assumed to be following long-term routes, such as flying between warehouses. When a collision is predicted along these routes, all UAVs cooperate to plan and execute short-term collision avoidance trajectories. The UAVs use horizontal, vertical, or three-dimensional manoeuvres to avoid collisions with one another, with static terrain and with dynamic obstacles.”
According to Meiring, current collision avoidance technologies used in commercial airspace − TCAS (Traffic Alert and Collision Avoidance System) and GPWS (Ground Proximity Warning System) − are rules-based, non-cooperative and decoupled approaches that are not suitable for UAV collision avoidance in an extremely congested airspace with complex terrain.
Meiring says her approach doesn’t require the UAVs to be working together towards the same goal; they merely have to be in communication with each other and only cooperate for long enough to avoid a collision.
“The two algorithms that I created are hybrids of the two most common approaches to collision avoidance, namely the centralised and decoupled approach.”
Meiring explains that in the centralised approach, all vehicles plan routes to avoid the collision together and in the decoupled approach it’s done individually.
Centralised strategies are the most reliable and optimal, but slow, whereas the decoupled strategies are less reliable but significantly faster, she notes.
“My approach creates smaller groups of UAVs and plans the groups independently. The simulations that I performed to test the effectiveness of my algorithms showed that both managed to improve on these strategies by eliminating some of their flaws, while mostly retaining their strengths.”
Meiring says her research could help to provide automatic collision avoidance for large numbers of drones delivering parcels to independent locations in a congested urban environment.
“Hopefully, this research will bring us a step closer to UAVs being integrated into more and more airspaces, especially commercial airspaces, by providing potential options to ensure collision avoidance. This type of strategy could help make UAVs become more common and safer and also more useful,” she concludes.
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