Robotics, Drones & AI For Monitoring Energy Infrastructure

Operators Forum at the Energy, Drones, Robotics Summit in Houston, TX, June 22-24, 2026

InnovateEnergy

The Energy, Drone and Robotics Summit focused on monitoring downstream (exploration, extraction, transport, etc.) and upstream (refining, pipelines, etc.) infrastructure used for oil and gas operations. The Operators Forum (pictured above) featured participants from Evergy and Entergy (electric utilities), Chevron and Shell (major oil and gas companies) and Osprey Integrity (a infrastructure monitoring company that uses drones and robotics).

The Global oil and gas industry generated ~$6T/year in 2024, and is expected to grow to $8.5T/year by 2034. Economic growth, industrialization, population growth and price volatility drives this revenue expansion, with the United States, Russia and Saudi Arabia as the major suppliers of crude oil (40%) and the Asia Pacific region (China, India) consuming 35% of energy resources. Globally, ~12M people work in this sector.

The infrastructure supporting this is in the tens of $T, and includes equipment and facilities for drilling and processing, distribution pipelines, storage, refining and product transport. New infrastructure construction was in the ~$800B range in 2025, and is expected to grow to $1.2T by 2030.

Monitoring this infrastructure is a mammoth task, with environmental, security and economic impacts, and strict regulatory requirements. In the United States, regulation of oil and gas operations has existed in various forms for over 100 years, and is focused on protecting the environment (including air and water quality), cultural resources, workers’ and the public’s health and safety, and reducing wasted resources. A combination of agencies (state and federal) are involved with regulating extraction and processing on non-federal land (state agencies, Environmental Protection Agency), on federal land (Bureau of Land Management, National Park Service) and offshore (Bureau of Ocean Energy Management, the Coast Guard and The Bureau of Safety and Environmental Enforcement). These regulatory agencies have detailed requirements for monitoring and maintenance of infrastructure, typically on a periodic basis (monthly, semi-annually or annually). The growth of physical AI, sensing and data analytics solutions provides efficient, persistent, proactive and safe infrastructure monitoring.

InnovateEnergy - Where Robotics, Data and AI Meet

InnovateEnergy is an organization that brings together a global audience of over 20,000 energy executives, digital innovation and technology integration leaders to solve energy infrastructure monitoring on a global scale. Sean Guerre is the Managing Director. He is an experienced Founder/Advisor with a demonstrated history of building communities and working with digital media and live events in Technology, Energy & Workforce markets. As part of its effort, InnovateEnergy has been organizing the annual Energy, Drones and Robotics Summit for the past 10 years. The central focus of the 2026 event (an exhibition with ~200 companies, curated forums, and demonstrations) was on the use of autonomy, sensors, data and physical AI to assist humans in the task of monitoring energy infrastructure. Key themes included drones and robotics with specialized sensor stacks for monitoring and maintenance, data visualization, emergency dispatch, regulatory environment, workflow integration and data security. Drone operations in varied geographical environments was also discussed. It drew ~ 1600 attendees representing 400+ energy and utility companies, and ~200 exhibitors.

Key takeaways from the Summit:

1. The energy business is complex. Infrastructure spans large areas, with climate and environmental impacts, temperature, pressure, corrosion, varying regulatory requirements, pricing dynamics and political factors constantly at play. But these companies do make tons of money.
2. Depending on the energy company needs, the physical AI monitoring infrastructure is either done in-house (through capital spend and internal workforce) or contracted to Robotics as a Service (RaaS) providers.
3. The decision on deciding whether to deploy internal capital or using RaaS providers depends on whether periodic or persistent surveillance is required, the specific task and the location of the infrastructure.
4. Data analysis from AoT® (Autonomy of Things) platforms is typically done in-house by the energy companies, with data security as a critical driver. Human review of the processed data is a critical requirement, required by regulation. AI is used to learn from the large amounts of past and current data, to improve operations and infrastructure, and universalize solutions across infrastructure. As the amount of data grows exponentially, secure data storage costs are a key issue.
5. The central goal is safety - performing the monitoring task with minimal exposure of human personnel to hazardous situations (temperatures, gases, equipment accessibility). Productivity and universal, persistent coverage over large geographical areas are other advantages.
6. Advances in sensors, AoT®, drone and robotics technology have been key drivers, pushing energy companies to increasingly deploy these technologies in various operational aspects. Mobile sensing technologies are replacing or augmenting stationary sensors, to provide more coverage. Proactive and persistent sensing provides faster responses on identified anomalies.
7. Asset identification and equipment inspection (reading gauges on equipment) is a key initiative, as is monitoring leaks (methane, oil, etc.) and corrosion on various pieces of infrastructure.
8. Drone and robot mounted sensors include RGB cameras, thermal cameras, laser spectroscopy (for Optical Gas Imaging or OGI for methane detection) and acoustic/ultrasonic (for crack detection, structural integrity). A host of machine mounted gauges that monitor physical parameters (temperature, pressure, etc.) are also used to ensure optimal operation. Drone-mounted LiDAR (Light Detection and Ranging) sensors are also being used to create 3D maps of facilities and inventory to speed up new construction. Bathymetric LiDAR is being used to map riverbed terrain for laying pipelines and drilling equipment. Calibration of these sensors for operation under a range of lighting and temperature conditions is critical.
9. Drone pilot certification for energy companies and RaaS providers is a critical element of drone operation for VLOS (Visual Line of Sight) and BVLOS (Beyond Visual Line of sight operations. BVLOS is allowed in certain locations (private property) and altitudes. The FAA has proposed a new rule, which is currently in the public comment phase. Once passed, it would establish a process for eligible critical infrastructure owners and operators to request drone flight restrictions over their facilities. This is critical for energy security.

Figure 2 shows some images of robotics and drones in action.

BrightAI - Physical AI for our
World’s Essential Services

BrightAI was one of the exhibitors at the EDR Summit. A previous article discussed how BrightAI transforms critical infrastructure management (electric transmission and distribution, water distribution, sewage management) by replacing outdated reactive practices with proactive sensor and artificial intelligence (AI) driven operations. It partners with owners and operators (private and public) to boost their productivity, capital efficiency, and sustainability. Through cutting-edge AI, sensor and autonomous technology, BrightAI reduces infrastructure failure risks, future-proofs systems, and ensures infrastructure resilience. On display at the exhibition were robotics and drone-powered sensor systems for energy infrastructure monitoring (Figure 3), an area where they are leveraging their utility infrastructure experience.

Figure 3 (L) shows drone imagery (flying at 50 ft.) of compression tanks and other infrastructure for asset identification and tagging. Figure 3 (M) shows the mapping and thermal/temperature imaging of separation tanks using low altitude drones equipped with thermal cameras. It shows the estimated oil layer thickness using surface temperature and thermal stratification. The thermal gradients are correlated to the physical pad thickness, and addresses cleanout avoidance and optimal oil recovery from water and sand. Figure 3 (R) was acquired by a ground robot to read and transmit gauge readings on equipment.

In general, BrightAI’s customer layout and accessibility determines the choice of the physical AI platform used for different tasks. For example, winterization metal walls may not allow a drone to fly close, in which case a robot is used. Curated training data is acquired first in concert with the customer, and used to label assets in other locations, using BrightAI’s AI powered software. According to BrightAI’s Vice President of Marketing, Jennifer MacDonald, “Its clear that energy companies are embracing AI, but many are still figuring out how to translate the right data and insights from these tools into action, by applying AI to specific use cases”.

(Disclosure: I am a consultant for BrightAI)

LiDAR News recently posted an interesting article discussing the use of manned, higher altitude, fixed wing aircraft, equipped with a 3D LiDAR system to do a survey of approximately 400 acres near Shawnee, Oklahoma for a large-scale energy development project. The processed point clouds are fused with RGB data to create a topological map of the terrain to aid in infrastructure construction, from planning to life cycle management. The mapping was done at altitudes of 800-1000 m, enabling a more rapid and efficient process over a large area. The sensor stack from Phoenix LiDAR Systems, and uses a 1550 nm LiDAR developed by Riegl. The survey was carried out by Blew and Associates, a 135-year old, Arkansas-based surveying company that operates across the United States.

The Phoenix sensor stack (Ranger -U240) used for the Oklahoma survey is a lightweight airborne laser scanner. Apart from fixed wing, manned aircraft, it can also be used with drone or helicopter platforms.

Xplorobot - Advanced Leak Detection. In the Palm of Your Hand

Founded in 2019 by Dr. Oleg Mikhailov, the company is headquartered in Houston, Texas, and focuses on compact, handheld methane detection LGI sensors (Laser Gas Imager) based on proprietary Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology. The device also incorporates anemometers (wind speed) and thermometers. Software to tag emissions for specific equipment and components is also integrated in the handheld unit, which can be used by trained personnel or mounted on drones. Real-time visualizations powered by artificial intelligence, pinpoints leaks down to individual components. Xplorobot’s LGI sensors are deployed globally in 23 countries and ~5400 facilities by 80 customers. Figure 4 shows the capabilities of the LGI:

The handheld sensor can also be mounted on a low-cost drone (Figure 5):

Xplorobot has trialed their LGI sensors on commercial robots (4 different suppliers) on offshore, tankers drill rigs and fracturing fleets, some of the most demanding industrial environments in the world. These trials used robots with their own sensor and compute payloads for perception, localization and motion planning, and are very expensive (~$200K-$400K). Customer feedback was that deploying such robots was not commercially feasible. The key learning was that locomotion and navigation would eventually be solved and available at affordable prices, so the real value is in vision-based attribution and fusion for multi-spectral information.

The current initiative is on using very low cost robots, integrated with the LGI sensor, an iPhone 17 Pro (~$2K), and custom software. The imaging sensors in the iPhone (cameras and LiDAR) are adequate to provide the perception and localization functions. IMU sensors on the iPhone are used to navigate the robot. Xplorobot’s software application (running on the iPhone processor) provides the path planning and equipment recognition function, and controls the location at which methane scanning needs to occur. The iPhone application sends commands to control the gimbal-mounted LGI sensor’s orientation to make the measurement. With this solution, Xplorobot aims to disrupt the robotics monitoring space, with a low cost (an order of magnitude below the $200K-$400K price points referenced above), precise, easy to deploy solution.

According to Dr. Mikhalov: "Xplorobot IP and products are focus on multispectral information fusion and attribution to real objects in physical space. We deploy our sensors and AI on the most modern autonomous platforms, and deliver value to our clients at scale by managing data acquisition, analysis and alerts at scale”.

What’s The Deal with Methane?

Methane is a key component of natural gas, and a lot of effort is focused on monitoring methane leaks in energy infrastructure. Its fair to raise a question though - can these leaks be prevented by better process, component and equipment design?

According to an ExxonMobil report, the key sources of such leaks are:

1. Flaring: the burning of excess natural gas for safety or other reasons.
2. Venting: the release of excess methane to reduce pressure in pneumatic devices, storage tanks, dehydration units, and other components of our operations to help ensure safety.
3. Fugitive emissions: unintentional leaks from equipment.
4. Combustion slip: un-combusted methane in the exhaust of natural gas engines.

Fugitive emissions and combustion slip are certainly key reasons that proactive methane monitoring is needed. Flaring and venting are conscious choices, although major energy companies are developing proactive solutions to minimize or eliminate these effects. For example, ExxonMobil has a target of zero routine flaring in upstream assets by 2030. The company also is replacing traditional natural gas-powered pneumatic compressors with electrical compressors, improving the seal design on centrifugal compressors to prevent leaks, retrofitting tanks at existing sites to reroute emissions sources through vapor recovery units, and using pressurized, closed-system vessels instead of traditional tanks in new builds.