A Bayesian tracker for synthesizing mobile robot behaviour from demonstration

نویسندگان

چکیده

Programming robots often involves expert knowledge in both the robot itself and task to execute. An alternative direct programming is for a human show examples of execution have perform based on these examples, scheme known as learning or from demonstration. We propose study generic simple learning-from-demonstration framework. Our approach combine demonstrated commands according similarity between sensory trajectories current replay trajectory. This tracking solely performed sensor values time completely dispenses with usually expensive step precomputing an internal model task. analyse behaviour proposed several simulated conditions test it two different robotic platforms. that can reproduce capabilities limited number meta parameters.

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ژورنال

عنوان ژورنال: Autonomous Robots

سال: 2021

ISSN: ['0929-5593', '1573-7527']

DOI: https://doi.org/10.1007/s10514-021-10019-4