ShopTalk, a proof-of-concept system designed to assist individuals with visual impairments with finding shelved products in grocery stores, is built on the assumption that simple verbal route directions and layout descriptions can be used to leverage the O&M skills of independent visually impaired travelers to enable them to navigate the store and retrieve shelved products. This paper introduces ShopTalk and summarizes experiments performed in a real-world supermarket.

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.

We will demonstrate the iWalker, a three-sensor rollatormounted wayfinding system for the elderly with cognitive and visual impairments. Unlike several previous and ongoing research efforts, iWalker emphasizes a smart world (SW) perspective. A SWis a physical space equipped with embedded sensors. One implication of the SW perspective is the simplification of the onboard computing machinery needed to make iWalker operational.

This paper examines the appropriateness of natural language dialogue (NLD) with assistive robots. Assistive robots are defined in terms of an existing human-robot interaction taxonomy. A decision support procedure is outlined for assistive technology researchers and practitioners to evaluate the appropriateness of NLD in assistive robots. Several conjectures are made on when NLD may be appropriate as a human-robot interaction mode.

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.

Abstract Automated information retrieval relies heavily on statistical regularities that emerge as terms are deposited to produce text. This paper examines statistical patterns expected of a pair of terms that are semantically related to each other. Guided by a conceptualization of the text generation process, we derive measures of how tightly two terms are semantically associated. Our main objective is to probe whether such measures yield reasonable results. Specifically, we examine how the tendency of a content bearing term to clump, as quantified by previously developed measures of term clumping, is influenced by the presence of other terms. This approach allows us to present a toolkit from which a range of measures can be constructed. As an illustration, one of several suggested measures is evaluated on a large text corpus built from an on‐line encyclopedia.

Abstract The equivalence of semantic networks with spreading activation and vector spaces with dot product is investigated under ranked retrieval. Semantic networks are viewed as networks of concepts organized in terms of abstraction and packaging relations. It is shown that the two models can be effectively constructed from each other. A formal method is suggested to analyze the models in terms of their relative performance in the same universe of objects.