  This paper presents the development of a novel ethical reasoning framework
for robots. "Robots Can Feel" is the first system for robots that utilizes a
combination of logic and human-like emotion simulation to make decisions in
morally complex situations akin to humans. The key feature of the approach is
the management of the Emotion Weight Coefficient - a customizable parameter to
assign the role of emotions in robot decision-making. The system aims to serve
as a tool that can equip robots of any form and purpose with ethical behavior
close to human standards. Besides the platform, the system is independent of
the choice of the base model. During the evaluation, the system was tested on 8
top up-to-date LLMs (Large Language Models). This list included both commercial
and open-source models developed by various companies and countries. The
research demonstrated that regardless of the model choice, the Emotions Weight
Coefficient influences the robot's decision similarly. According to ANOVA
analysis, the use of different Emotion Weight Coefficients influenced the final
decision in a range of situations, such as in a request for a dietary violation
F(4, 35) = 11.2, p = 0.0001 and in an animal compassion situation F(4, 35) =
8.5441, p = 0.0001. A demonstration code repository is provided at:
https://github.com/TemaLykov/robots_can_feel
