Walmart and Drone-Up Turn to Iris Automation to Improve the Safety and Scalability of their Delivery Operations
Walmart and its drone delivery partner, Drone-Up, want to make their Beyond Visual Line of Sight (BVLOS) operations safer than ever – and just as important, fully scalable to ensure profitability. Their recently-announced collaboration with Iris Automation could well bring this long-sought goal to fruition.
Currently, Drone-Up assists Walmart with remote package delivery operations at 34 Walmart store outlets in six US states – Arizona, Texas, Utah, Arkansas, North Carolina and Virginia. The flights are “last mile” deliveries – exclusive to select Walmart customers living in small towns and cities close to a Walmart outlet.
Customers can choose from thousands of store items and can receive packages weighing up to 10 pounds. Walmart boasts that their drone deliveries arrive at their customer’s doors within as little as 30 minutes.
But the restrictions on the number of drones that can fly at one time and their short flight distances makes the operation far less competitive than it might be if Drone-Up could fly multiple drones concurrently, coordinating their flights over longer distances and near larger population centers, and without the need for constant visual monitoring.
From a regulatory stand-point, one of the key operational issues is safety. Can drones be prevented from crashing into each other or with humans on the ground if they are given a relatively carte blanche authority to fly BVLOS?
Iris Automation, which specializes in “obstacle avoidance” technology, has just the answer: A network of ground-based sensors that monitors airspace and detects obstacles in a drone’s flight path. Once obstacles are detected, the system known as Casia G, provides the drone operator with sufficient advance warning to avoid a possible collision.
The Casia G surveillance system uses camera nodes to monitor airspace in 360° fields of view. The nodes start at the drone’s launch point – a store outlet – but are also strung along its projected flight paths. Not all flight paths will be known in advance precisely, as customer destinations may vary. But most flight trajectories near populated areas will be pre-programmed and the Casia G’s sensor capabilities are sufficiently broad to accommodate additional variation, company officials insist.
Jon Damush CEO of Iris Automation said, “Through the use of Casia G, DroneUp will be able to remove visual observers – creating a path to more economical scaling of their operations while simultaneously improving safety.”
John Vernon, CTO of DroneUp added: “The technology behind Casia G for BVLOS has the potential to be a game-changer in demonstrating that delivery in more populated areas can be as convenient and secure as it currently is in rural environments. Through this partnership DroneUp can dramatically scale operations, freed from restrictions.”
Casia G is not quite ready for prime time, however. The FAA, which continues to harbor serious reservations about BVLOS flights near populated areas, needs to size the system up, and extend its formal regulatory approval. That could take months.
The introduction of Casia G is part of a new effort by Drone-Up and other major drone companies to develop the infrastructure to improve the scalability of long-distance remote package deliveries. Walmart has made just 6,000 drone deliveries at its 34 sites to date, mostly consisting of smaller food items. Amazon, meanwhile, has struggled for years to secure FAA approval for BVLOS flights but its package delivery drones still operate under strict visual oversight.
A report by McKinsey Corporation released last December found that current “last mile” drone delivery operations – conducted one at a time by a single drone – were more sustainable but less cost-effective than existing road vehicle systems using cars and bicycle couriers. The report estimated that major cost reductions would result from expanded FAA approval for multiple drone flights coordinated by a single remote operator over an expanded geographic area.
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