Sequential gesture mapping into expanded meaning for robots
Wiljami Ahde · Tampere University Institutional Repository (Tampere University) · 2026
Robotics is continuously expanding and ways of interacting and controlling robots are always being explored. Gestures have emerged as one such method where the bodily motions of a person are captured using a sensor and then mapped into some meaning for the robot to follow. This thesis provides a pipeline for capturing sequences of gestures, which can be mapped into complex meaning. This is done simply by recognizing individual gestures and concatenating them into a sequence. This is built on top of open source methods. First is Google’s MediaPipe, which is used to recognize hands and gestures on a camera feed. Second is a Robot Operating System 2 integration of MediaPipe, which allows for the information to be passed into a node that handles sequence capturing. The experiments showed the method to be reliable and intuitive for users, although it was not implemented into an actual robot or human-robot setting.