Research on spatial cognition and navigation of the visually impaired suggests that vision may be a primary sensory modality that enables humans to align the egocentric (self to object) and allocentric (object to object) frames of reference in space. In the absence of vision, the frames align best in the haptic space. In the locomotor space, as the haptic space translates with the body, lack of vision causes the frames to misalign, which negatively affects action reliability. In this paper, we argue that robots can function as interfaces to the haptic and locomotor spaces in supermarkets. In the locomotor space, the robot eliminates the necessity of frame alignment and, in or near the haptic space, it cues the shopper to the salient features of the environment sufficient for product retrieval. We present a trichotomous ontology of spaces in a supermarket induced by the presence of a robotic shopping assistant and analyze the results of robot-assisted shopping experiments with ten visually impaired participants conducted in a real supermarket.

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.

This paper presents RoboCart, a proof-of-concept prototype of a robotic shopping assistant for the visually impaired. The purpose of RoboCart is to help visually impaired customers navigate a typical grocery store and carry purchased items. The current hardware and software components of the system are presented. For localization, RoboCart relies on RFID tags deployed at various locations in the store. For navigation, RoboCart relies on laser range finding. Experiences with deploying RoboCart in a real grocery store are described. The current status of the system and its limitations are outlined.

We describe how radio frequency identification (RFID) can be used in robot-assisted indoor navigation for the visually impaired. We present a robotic guide for the visually impaired that was deployed and tested both with and without visually unpaired participants in two indoor environments. We describe how we modified the standard potential fields algorithms to achieve navigation at moderate walking speeds and to avoid oscillation in narrow spaces. The experiments illustrate that passive RFID tags deployed in the environment can act as reliable stimuli that trigger local navigation behaviors to achieve global navigation objectives.