The global trend of urbanization that began after World War II continues to grow rapidly. In 2014, 54 percent of the world’s population resided in urban areas, compared to only 30 percent in 1950, and the United Nations estimates that by 2050, that number will reach 66 percent. This global trend necessarily contributes to a shift in the characteristics of any future potential conflicts, and as a result, in the way urban warfare would be conducted.
Fighting in urban areas is extremely complex and challenging. The third dimension in urban areas, such as subterranean and multi-story structures, affects the line of sight and engagement conditions, thus increasing the complexity of the environment. In addition, the presence of civilians introduces constraints, such as reduced air or artillery support for ground troops, to minimize non-combatant causalities and collateral damage. The complexity of the environment requires better situational awareness, equipment, and training to overcome these challenges.
Technological advancements in recent years have equipped armed forces to meet these challenging demands. Such advancements include military robotic platforms, which are now frequently employed by troops for explosive ordinance disposal, loading and carrying heavy items, and repairing ground conditions under fire. Furthermore, according to the 2011 unmanned ground systems roadmap report by the Robotic Systems Joint Project Office (RS JPO) of the United States Department of Defense (DoD), there are plans to develop armed unmanned ground vehicles (UGV) with combat abilities within the next 25 years. The figure shows a variety of the UGVs being developed.
One of the emerging concepts that the RS JPO is actively tracking is the Multi- Mission Unmanned Ground Vehicle (MM-UGV). MM-UGVs possess armed unmanned capability as well as the capability to deal with improvised explosive devices. It is evident that full autonomy for an unmanned combat ground vehicle such as the MM-UGV is a far-term capability anticipated by the U.S. Army.
To meet the future capabilities requirement as identified in the U.S. Army UGV campaign plan, unmanned ground vehicles require further technological advancement. For the micro- and nano-bots depicted in the figure, swarming is considered to be one of the most promising capabilities to be developed. Swarm intelligence is an artificial intelligence discipline that consists of a multi-agent system that takes inspiration from the behavior of colonies of social insects and animal societies, such as flocks of birds or schools of fish. The word “swarm” is an appropriate word because it has special characteristics not found in related terms such as “group.”
The three key special characteristics of a swarm are decentralized control, lack of synchronicity, and the simplicity and homogeneity of the swarm; additionally, the swarm’s algorithms run in an asynchronous and decentralized fashion.
This research explores the area of UGV autonomy, investigating the effects of kinematics inputs (e.g. movement behavior, swarm size, detection range) and engagement inputs (e.g. sensors and weapon range) with an assumption that the hardware and software capabilities requirements mentioned previously are met.