The benefits of robot deception in search and rescue: Computational approach for deceptive action selection via case-based reasoning

By increasing the use of autonomous rescue robots in search and rescue (SAR), the chance of interaction between rescue robots and human victims also grows. More specifically, when autonomous rescue robots are considered in SAR, it is important for robots to handle sensitively human victims´ emotions. Deception can potentially be used effectively by robots to control human victims´ fear and shock as used by human rescuers. In this paper, we introduce robotic deception in SAR contexts and present a novel computational approach for an autonomous rescue robot´s deceptive action selection mechanism.