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Within this work, we explore intention inference for user actions in thecontext of a handheld robot setup. Handheld robots share the shape andproperties of handheld tools while being able to process task information andaid manipulation. Here, we propose an intention prediction model to enhancecooperative task solving. The model derives intention from the user's gazepattern which is captured using a robot-mounted remote eye tracker. Theproposed model yields real-time capabilities and reliable accuracy up to 1.5sprior to predicted actions being executed. We assess the model in an assistedpick and place task and show how the robot's intention obedience or rebellionaffects the cooperation with the robot.

Rebellion and Obedience: The Effects of Intention Prediction in Cooperative Handheld Robots