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Training and preparing first responders and humanitarian robots for MassCasualty Incidents (MCIs) often poses a challenge owing to the lack ofrealistic and easily accessible test facilities. While such facilities canoffer realistic scenarios post an MCI that can serve training and educationalpurposes for first responders and humanitarian robots, they are often hard toaccess owing to logistical constraints. To overcome this challenge, we presentHEROES- a versatile Unreal Engine simulator for designing novel trainingsimulations for humans and emergency robots for such urban search and rescueoperations. The proposed HEROES simulator is capable of generating syntheticdatasets for machine learning pipelines that are used for training robotnavigation. This work addresses the necessity for a comprehensive trainingplatform in the robotics community, ensuring pragmatic and efficientpreparation for real-world emergency scenarios. The strengths of our simulatorlie in its adaptability, scalability, and ability to facilitate collaborationbetween robot developers and first responders, fostering synergy in developingeffective strategies for search and rescue operations in MCIs. We conducted apreliminary user study with an 81% positive response supporting the ability ofHEROES to generate sufficiently varied environments, and a 78% positiveresponse affirming the usefulness of the simulation environment of HEROES.

HEROES: Unreal Engine-based Human and Emergency Robot Operation Education System