Investment Analysis (5) — PreNav, enabling precise drone navigation in industrial uses
PreNav (http://www.prenav.com)
Founded: 2013, Funding: Seed round $1.2M in Aug 2015, Seed round $6.5M in Aug 2016
Seed investors: Michael Antonov, Crosslink Capital, Haystack, Liquid 2 Ventures, WI Harper Group
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With forthcoming FAA regulations and advancements in intelligent navigation technologies, commercial drones are expected to generate billions dollar of value for the US economy by significantly improving efficiency in various industries such as agriculture, construction, insurance, and film, while enabling data that have never been collected before. Prenav is a drone platform startup which can bring this value to the task of industrial inspection.
Industrial inspection is one of the most promising applications for commercial drones. In the US, over $3bn is spent on building inspection alone, and even more on larger infrastructures such as cell towers, wind turbines, and bridges. Meanwhile, the demand of maintenance is increasing as consumption grows. However, the traditional inspection process has been extremely inefficient, expensive, and dangerous. For example, an annual rope-access inspection at a wind farm can cost $1,500 in addition to the costs incurred from shutting off the turbines for at least half a day. It is also difficult to get consistently good imagery and complete coverage of the structures by climbing or using hand-flown drones.
While fundamental challenges in robotics generally deal with localization, planning, and computer vision, commercializing drones in industrial inspection faces the following major problems:
· Existing navigation systems typically rely on GPS data and collision sensors that result in slow communication between drones, fail to guarantee the precision needed for ultra-close views in maintenance inspection, and cannot support tasks indoor or in congested cities
· Most drones are manually controlled by skilled pilots which incurs greater costs for companies
· Most drone solutions don’t provide a complete workflow, leaving customers responsible for third party tools such as image processing
Prenav’s LiDAR-based 3D mapping and construction data analysis frees human operators from unsafe large infrastructure inspection and enables data-driven asset management. The system combines a drone, a ground-based guidance robot, as well as software to plan the project and analyze the resulting data. The robot performs an initial laser scan of a structure then creates a 3D point cloud to guide the drone through precise routes. This solution provides unprecedented business value in multiple aspects:
· With precise navigation, PreNav’s system allows close-up photographs of structures and provides final output of high-resolution 3D render that can be used for inspection purposes — more valuable for customers than the videos-and-images report provided by current solutions
· With laser-based sensors and guided by computer vision, PreNav drones are able to safely fly in complicated or GPS-denied environments with a high degree of precision and repeatability
· The fully automated system enables any existing workers to use without hundreds of hours of pilot training — an important added-value after FAA’s new rules.
· PreNav’s complete workflow makes it easy for customers to operate the system and utilize the data from the cloud. It also has the potential to retain this data advantage through machine learning
PreNav hasn’t released its pricing yet, but has signed contract with infrastructure companies like Senvion, OWBS and Spectrum services, saving customers an average of $500/inspection. The team has impressive 70+ years of experience in robotics, computer vision and aerospace, starring a few big players including former CTO of Bot & Dolly (acquired by Google) Nathan Schuett. With current funding, PreNav expects to officially launch product in late 2016, and push further into functional indoor jobs.
