Ergonomics-for-one in a robotic shopping cart for the blind

Abstract

Assessment and design frameworks for human-robot teams attempt to maximize generality by covering a broad range of potential applications. In this paper, we argue that, in assistive robotics, the other side of generality is limited applicability: it is oftentimes more feasible to custom-design and evolve an application that alleviates a specific disability than to spend resources on figuring out how to customize an existing generic framework. We present a case study that shows how we used a pure bottom-up learn-through-deployment approach inspired by the principles of ergonomics-for-one to design, deploy and iteratively re-design a proof-of-concept robotic shopping cart for the blind.