The battlefield is becoming more sophisticated, driving the development of advanced technologies both on the battlefield and in military simulation and training. One such technology is unmanned ground vehicles (UGVs), which are taking on an ever-expanding role in military operations, enhancing operational capabilities, increasing safety, and improving efficiency on the battlefield.
The technologies driving UGVs offer new possibilities for both supporting military forces and enhancing training capabilities.
It’s important to understand the differences between robotic, unmanned, and autonomous systems:
Robotic typically refers to machines that perform tasks manually but under human direction. These systems may be controlled remotely or operate autonomously in certain settings. Home Depot’s automated warehouse robots, which assist with inventory management and item picking, are an example of this.
Unmanned systems do not have human operators physically on board, but human involvement is still required, either remotely or through oversight. For example, remote-controlled, unmanned inspection devices are used in hazardous industrial environments, such as mines or damaged buildings.
Autonomous vehicles or systems can make decisions and perform tasks independently, without direct human intervention. They rely on artificial intelligence (AI), sensors, and algorithms to function in real time. A prime example is self-driving delivery vehicles used by companies to transport goods, where human oversight is minimal or nonexistent.
Unmanned ground vehicles (UGVs) are transforming military operations by enhancing efficiency and reducing human risk, especially in hazardous environments. These vehicles can perform a variety of critical functions that aid in both combat and non-combat scenarios.
The THeMIS by Milrem is a multi-role defense platform that demonstrates the versatility of UGVs. Its modular design makes it adaptable for a variety of missions, including transport, surveillance, and even direct combat support. With hybrid propulsion and intelligent AI systems, the THeMIS is a cutting-edge tool for military applications.
The U.S. Army’s Robotic Combat Vehicle (RCV) program is actively testing prototypes. By 2028, the program plans to integrate autonomous vehicles into future combat scenarios. These vehicles will enhance the military's capacity for ground combat by performing roles such as reconnaissance and combat support.
Although UGVs have been deployed for various military tasks, they are still evolving in specialized fields such as firefighting. With the growing complexity of wildland fire responses on military lands, the need for advanced ground robotics that can handle hazardous conditions is more pressing.
These systems will require collaboration between academia and industry to optimize their performance for wildfire response, improve safety, and support firefighting operations in risky environments.
In February 2025, Tech Grove executed a prize challenge to identify solutions that advance the use of advanced remotely operated equipment, ground-based autonomous vehicles, and other remote-operated technologies (excluding aircraft) for wildfire response in hazardous conditions. For this challenge, the benefits of participating include:
For information about upcoming prize challenges and other opportunities, join the Tech Grove Innovation Grower’s Alliance.
Autonomous capabilities in unmanned ground vehicles are rapidly advancing, with systems such as BAE’s ATLAS CCV already integrating autonomous features. However, the evolution of these capabilities requires continued development in several key areas:
To provide a comprehensive understanding of the environment, UGVs must combine data from multiple sensors, including LIDAR for precise 3D mapping, radar for detecting objects in challenging conditions, and cameras for visual recognition. This fusion of data allows UGVs to make informed decisions about their surroundings.
Advanced AI and machine learning, particularly deep learning and reinforcement learning, will be essential for UGVs to navigate complex environments like that seen in urban warfare. These systems must be capable of making real-time decisions in dynamic and unpredictable situations.
To handle edge cases — unusual or rare scenarios — UGVs must be equipped with systems that use experience-based learning to improve performance over time. The more the vehicle is used, the better it becomes at responding to unforeseen challenges.
UGVs must be equipped to identify and avoid obstacles in real time. This capability is crucial for reconnaissance missions or hazardous area assessments, such as detecting improvised explosive devices (IEDs).
SLAM technology allows UGVs to create accurate, real-time 3D maps of their environment while simultaneously determining their position within that space. This is vital for navigation and mission success in unpredictable terrain.
As unmanned ground vehicles become more prevalent in military operations, the need for specialized and innovative training programs grows.
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