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White Paper | Building BVLOS Drone Programs that Scale

Writer: Shearwater Aerospace
Shearwater Aerospace
Aug 24
3 min read

Updated: Sep 16


In our newest white paper, in partnership with Embention, Shearwater explores the BVLOS scaling challenges that integrated autonomy is built to overcome. Armed with autonomous systems, organizations can scale BVLOS drone programs by unifying intelligent mission planning, flight control, real-time monitoring, compliance, and operational data — all into one single workflow. Using Shearwater Smart Flight™ combined with Embention’s Veronte ecosystem, for instance, operators can optimize routes around weather, terrain, airspace, and even aircraft performance. This reduces cognitive load, supports compliance, and allows for more repeatable missions spanning logistics, infrastructure inspection, defence, and ISR.

Drone Programs That Scale: Reducing BVLOS Complexity With Integrated Autonomy


In our latest white paper, in partnership with Embention, Shearwater explores how to minimize BVLOS challenges.


BVLOS drone missions have moved far beyond demos and are now critical to many commercial and defence applications, from reconnaissance to pipeline monitoring. Indeed, between 2020 and 2023 alone, FAA-approved BVLOS operations grew 22x, from 1,229 to 26,870, signalling significant market momentum. 


Although flying farther is now possible, scaling remains an immense challenge. Operators increasingly require repeatable models that incorporate and unify planning, execution, compliance, and data in one place, without increasing workloads.


BVLOS Industry Impact & Core Challenges


Conventional visual-line-of-sight operations simply can’t support many missions: from long-range infrastructure inspections and time-sensitive deliveries in hazardous locations to persistent ISR (intelligence, surveillance, and reconnaissance).


BVLOS, of course, offers much-needed range, but as range and mission duration increase, so do the many variables that demand better management:


  • Weather exposure can change across the entire route, not just at launch and recovery sites

  • Terrain, airspace boundaries, and urban populations that form ground-risk considerations

  • Aircraft endurance, energy reserves, payload effects, and communications reliability

  • Contingency planning and real-time changes in mission conditions

  • Documentation and approval requirements across jurisdictions


Such issues become even more challenging during recurring missions, multi-aircraft missions, and deployments involving different teams or locations.


This means that some programs may be technically capable but remain difficult to reproduce on a consistent basis.







Why BVLOS Programs Struggle to Scale


The core BVLOS scaling problem comes down to compounding complexity.


Because of this, operators typically have to address mission gaps manually across different tools. That fragmented approach (across mission planning, flight control, and data collection and reporting) can slow down operations or completely hold them back.


Ultimately, the goal of integrated autonomous solutions is to shift the role of the pilot from their mentally taxing manual control toward higher-level decision-making.


From introducing delays and likelihood of error to duplicate data entries and cross-checking, mental load can make it difficult to standardize operations across aircraft platforms, software environments, and locations.


What's more, longer and more dynamic missions also require that operators manage even more, all at once: route constraints, aircraft state, airspace, communications, weather, contingencies, and mission objectives. The result is an even higher-stakes decision environment. In such cases, cognitive load can impact mission consistency and, ultimately, mission outcomes.



Integrated Autonomy Creates Scalable Workflows and Systems


Scaling any BVLOS program now demands integration, and this becomes more true the more critical the mission is.


The ideal integration connects factors like planning, flight execution, monitoring, data, and compliance, making them all a part of one single workflow.


The Shearwater-Embention integration illustrates this model clearly.


Where Shearwater's Smart Flight™ platform supports more intelligent mission planning and optimization, Embention’s Veronte Ops and Veronte Autopilot support operators with flight control and an operational environment for mission execution and monitoring.


Rather than treating mission planning and flight control as separate stages, it's an approach that creates complete continuity: pre-flight assessment through to in-flight execution and post-mission review.



Where Integrated Autonomy Matters Most


The value of integrated planning and execution becomes especially clear in missions where repeatability, endurance, and risk management are critical.


USE CASE

CORE CHALLENGE

INTEGRATED AUTONOMY

Time-sensitive logistics

Tight delivery windows, payload and energy constraints, variable weather, urban ground-risk exposure

Optimizes routes, evaluates operating conditions, reduces coordination effort, and supports more repeatable delivery workflows

Defence and ISR

High operator workload, rapidly changing conditions, contested or degraded environments, mission-critical decisions

Supports risk-aware planning, reduces cognitive burden, and helps operators focus on changing mission priorities

Infrastructure inspection

Recurring routes, compliance requirements, worker-safety concerns, documentation needs

Standardizes repeat-flight paths, connects plans to execution, and improves traceability for inspection and audit workflows


From Flights to Programs


While aircraft and battery innovations remain key drivers of BVLOS capabilities, software — especially integrated autonomy — is now able to push those capabilities much further.


As missions become longer, more frequent, and more complex, disconnected systems and manual coordination will be unable to sufficiently support critical drone programs.


Today, integrated autonomy makes that transition possible.


  

 

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