Autonomous heavy assault vehicle
Autonomous heavy assault vehicles, abbreviated AHAV, are robotic war machines capable of operating autonomously and making independent decisions on the battlefield. Originally the brand name of an early model produced by Ironfire Industries on Absalom Station shortly after the Gap, the term AHAV has since entered the colloquial language to refer to all similar war machines.1
Appearance
AHAVs appear as vaguely humanoid-shaped, heavily armored tanks covered in heavy weapons and sensory equipment. They move either on hovertreads or legs.1
Function
AHAVs are built with various kinds of sensors capable of detecting heat, vibration, and more, though rarely all at the same time. Bound to their programming to absolutely obey their orders, AHAVs have little room for independent thought and nuance and can be tricked if the enemy can figure out their literal orders and work around them.1
Before they are programmed, AHAVs are outfitted with Mission Dependent Loadouts (abbr. MODELs), which are special abilities and equipment tailor-fitted to the individual AHAV's mission. These can include a sophisticated sensor suite and stealth capability for reconnaissance models or specific weapons loadouts for attacking specific targets. It is possible to figure out the objective of an AHAV by carefully observing its MODEL.1
AHAVs are built to last and sometimes continue to obey their objectives long after their necessity has ended. If an AHAV's mission becomes inconsistent or unachievable, its programming often becomes glitched, resulting in erratic behaviour. A mechanic that can discover such an AHAV's purpose can reason with it, but this is difficult due to the robot's confrontational worldview. If this is successful, the AHAV will shut down.1
Production
AHAVs are difficult and expensive to construct and maintain, so they are usually only purchased by rich militaries and collectors. Due to their overly literal programming, the popularity of AHAVs has declined over the past few decades, forcing producers to work to improve this problem.1
References
- ↑ 1.0 1.1 1.2 1.3 1.4 1.5 Alien Archive, 8–9. Paizo Inc., 2017 .