Imitation of Arm Gestures by the Semi-Humanoid Robot NICO
2026-07-20 • Robotics
Robotics
AI summaryⓘ
The authors created a system that lets the small humanoid robot NICO copy human arm gestures by using a camera and special software to track body landmarks. They used MediaPipe to find key points on a person's arm from regular video, then calculated joint angles to move NICO's motors in the same way. Tests with six people showed the robot could imitate simple arm movements fairly well, but had trouble with more complex poses and wrist actions. This work helps robots understand and mimic human gestures using only standard video input.
human-robot interactionhumanoid robotpose estimationMediaPipe3D coordinatesjoint anglesRGB cameragesture imitationrobot motor controlanalytical geometry
Authors
Anastasiya Ihnatovich, Igor Farkaš
Abstract
Seamless human-robot interaction (HRI) requires a number of perceptual and motor abilities from the robot, one of them being the imitation of human gestures. Humanoid robots have an advantage in HRI thanks to their anthropomorphic features. In this work, we develop a system for imitation of human arm gestures by the semi-humanoid robot NICO based on analytical geometry and a pretrained MediaPipe pose-estimation model. For each input RGB frame, 3D coordinates of relevant human body landmarks, including arm joints and hand keypoints, are obtained using the MediaPipe framework. Joint angles are then computed from these coordinates using derived geometric relations. Finally, the computed angles are properly mapped to NICO's motor configuration and executed in a predefined motion sequence. Preliminary experiments on several representative arm gestures with six participants of different height indicate that the proposed method can produce meaningful imitative motions from monocular RGB input only, while also highlighting limitations in more complex poses and wrist-related movements.