Robot hands that mimic human hands represent one of the primary ways robots interact with their surroundings. My team aimed to develop an algorithm that precisely translates the movements of an operator, captured through a glove-type input device, into the robotic hand’s actions. We chose a joint-by-joint control approach, mapping the input data from each sensor in the glove to the corresponding joint in the robot hand. Our design process involved determining the proper constant values, considering variations in the number of joints, the number of fingers, and the length of each finger segment. This design ensures that the robotic hand mirrors the human operator’s movements and intentions, paving the way for more effective human-robot interactions.