A Brief Introduction to Robotic IoT

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The IoT (Internet of Things) is the ecosystem of sensor-enabled devices that are connected to the internet. The demand and capability of sensor-powered monitoring, tracking, and analyzing devices is growing across commercial and industrial markets. In fact, researchers at Gartner anticipate that by 2020 there will be 26 times more devices connected to the internet than there will be people.

Paired with the piles of data we continually cite on the ever-growing market impact of robotics, it should be no surprise that the Robotic Internet of Robotic Things (RIoT) has emerged as a formidable and innovative hybrid field. Given that sensors play such a vital role in both robotics and IoT devices, it is being researched and invested in on a global level as a solution for security and surveillance, healthcare, and disrupting industrial automation.

Lock, Stock, and Two Smoking Industries 

IoT-based initiatives focus on equipping devices to collect, transfer, and analyze data over a network – reducing the role humans play in data analysis while equipping teams to optimize their workflow. Robotics-based initiatives focus on the action, interaction, and autonomous behavior of robot systems. These symbiotic goals are the driving force behind RIoT.

Initial applications of RIoT resulted in cloud robotics emerging within the robotic ecosystem. With the capability to support real-time processing and storage for hardware components, cloud computing redefined the way the IoT community collected and processed data.

RIoT Basics

RIoT hinges on the three foundational elements of IoT: sensors, sensor-friendly devices, and their capability to communicate via machine-to-machine (M2M) communication, and data analytics technologies which process raw sensor data. These elements function as the glue between the digital and physical worlds. By bridging the gap between robotic software and hardware, robotic systems are capable of heightened perception, mobility, object manipulation, and decisional autonomy.

Lower-level robotic features like mobility, perception, and manipulation are supported by IoT, specifically M2M communications, as the robotic acts as a sensor that publishes its data to any IoT subscriber needing that information.

The primary value of RIoT technologies is the autonomy a system has to make informed decisions to determine an action. Higher-level functions are powered by Machine Learning – the statistical patterns, algorithms, and neural networks the equip a robot to perform actions without explicit instructions from a programmer.

Scientists rely on this branch of Artificial Intelligence (AI) to equip robots to make the best possible decisions. For instance, accurate models are vital for robots to plan and navigate paths. To enhance a robot’s decision-making ability, predictive models are used to depict an environment and the possible outcomes of engaging the environment. Robots, as a result of analyzing large data sets and algorithms, can successfully navigate and adapt to the physical world


While the development of these two merging fields is still in its infancy, their symbiotic goals have already resulted in industry-changing technologies. Tomahawk Robotics has the distinction of developing the world’s first robotic IoT control system for enterprise customers. With the capability of unifying UAS/UGV systems via a single platform for multi-domain unmanned applications, Kinesis is singular and unique as a robotics extension to IoT. To learn more about this innovative technology, please visit tomahawkrobotics.com.

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