Gain-scheduling Control of a Monocular Vision-based Human-Following Robot

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Abstract This paper presents a gain-scheduling controller for a human-following robot. Typical controllers use either a point-to-point approach where the relative orientation between human and platform is uncontrolled, or a direction-based approach which corrects orientation errors at the expense of additional actuation. We describe the flaws and benefits of each and argue that a gain-scheduling controller combining the two is better equipped to deal with the challenges of human-following. A model of our feature-based, single camera vision system is presented and used to show that the gain-scheduling controller offers better performance than its components, and actual responses to a human following task are used to corroborate this.